sg.inflibnet.ac.in · ii DECLARATION BY THE CANDIDATE I declare that the thesis entitled “DEVELOPMENT AND VALIDATION OF IN-VITRO AND IN-VIVO CORRELATIONS FOR PREGABALIN AND PRAMIPEXOLE

DEVELOPMENT AND VALIDATION OF IN-VITROAND IN-VIVO CORRELATIONS FORPREGABALIN AND PRAMIPEXOLE

FORMULATIONS

A THESIS

Submitted by

M. MANIMALA

in partial fulfillment for the award of the degreeof

DOCTOR OF PHILOSOPHY

Department of Biotechnology

Interdisciplinary of Chemistry / BiotechnologyFACULTY OF HUMANITIES AND SCIENCES

Dr.M.G.R.EDUCATIONAL AND RESEARCH INSTITUTE

UNIVERSITY(Declared as Deemed to be University u/s. 3 of UGC Act 1956)

CHENNAI 600095

FEBRUARY 2016

ii

DECLARATION BY THE CANDIDATE

I declare that the thesis entitled “DEVELOPMENT AND VALIDATION

OF IN-VITRO AND IN-VIVO CORRELATIONS FOR PREGABALIN AND

PRAMIPEXOLE FORMULATIONS” submitted by me for the Doctor of

Philosophy is a bonafide record of work carried out by me during the period from

August 2007 to August 2014 under the guidance of Dr. Karpagam.S and has not

formed the basis for the award of any degree, diploma, associate-ship, fellowship,

titles in this or any other University or other similar institution of higher learning and

without any plagiarism.

I have also published my papers in International Journals (Scopus rated) as

per list of publications in the Annexure.

Signature of Research Scholar

iii

BONAFIDE CERTIFICATE

Certified that the thesis entitled “DEVELOPMENT AND VALIDATION OF

IN•VITRO AND IN-VIVO CORRELATIONS FOR PREGABALIN AND

PRAMIPEXOLE FORMULATIONS” is the bonafide work of

Mrs. M. MANIMALA who had carried out the research under my supervision and

without any plagiarism to the best of my knowledge. Certified further, that to the best

of my knowledge, the work reported herein does not form part of any other thesis or

dissertation on the basis of which a degree or diploma was conferred on an earlier

occasion on this or any other scholar.

Signature of SupervisorDr. S. Karpagam, Ph.D.,

Associate ProfessorQueen Mary’s College

Chennai 600 004

iv

ABSTRACT

In recent years, the concept and application of the in-vitro and in-vivo

correlation (IVIVC) for pharmaceutical dosage forms have been a main focus of

attention of pharmaceutical industry, academia, and regulatory sectors. Development

and optimization of formulation is an integral part of manufacturing and marketing

of any therapeutic agent which is indeed a time consuming and costly process.

Optimization process may require alteration in formulation composition,

manufacturing process, equipment and batch sizes. Certainly, implementation of

these requirements not only halts the marketing of the new formulation but also

increases the cost of the optimization processes. It would be, desirable, therefore, to

develop in-vitro tests that reflect bioavailability data. The main objective of an

IVIVC is to serve as a surrogate for in-vivo bioavailability and to support bio-

waivers. Thus the need for a tool to reliably correlate in-vitro and in-vivo drug

release data has exceedingly increased.

The drug candidates Pramipexole and Pregabalin are water soluble drugs that

are predominantly ionized in gastrointestinal pH ranges and are well absorbed after

oral administration and are categorized as high solubility/high permeability drugs

under the proposed Class I Biopharmaceutical Classification System (BCS). Hence it

becomes necessary to determine the in-vitro and in-vivo correlations for Pramipexole

and Pregabalin. A proliferation of modified-release products of Pramipexole and

Pregabalin, it becomes necessary to examine the concept of IVIVC of these drugs in

greater depth.

A single dose, randomized, complete, two treatment cross over study was

conducted in healthy human subjects for each drug formulation. The subjects were

selected and were screened based on the inclusion criteria of the study. On the basis

of this preliminary screening, 24 volunteers were selected and their liver and renal

5

functions and hematological parameters such as hemoglobin content, RBC and WBC

counts, blood sugar, cholesterol, bilirubin and ECG were examined by standard

clinical and biochemical investigations.

In each dosing session, volunteers received either immediate or modified

release formulations. The order of treatment administration was randomized in three

sequences (AB, BA) in blocks of two. Blood samples (4 ml) were collected using

disposable syringes in pre-heparinised centrifugal tubes at 0 (before drug

administration), 0.50, 1.0, 1.5, 2.0, 3.0, 4.0, 6.0, 8.0, 12.0, 18.0 and 24.0 h post

dosing. The samples were centrifuged at 3500 rpm for 10 minutes to separate plasma.

A similar procedure adopting cross over design in drug treatment was repeated after

7 days of wash out period.

The LC-MS/MS instrument was calibrated with polypropylene glycol standard

in positive and negative ion mode. The sensitive and selective LC-MS/MS method

was developed and validated. The Method development involves evaluation and

optimization of the various stages of sample preparation, chromatographic

separation, detection and quantification. The source parameters namely gas

temperature, gas flow, nebulizer, sheath gas temperatures, sheath gas flow, capillary

voltage, charging voltage were optimized. Different reverse phase columns, different

mobile phases with different ratios and mobile phase flow rates were optimized.

Extraction of the drugs from the plasma sample was tried with Liquid-Liquid

Extraction (LLE) and Solid Phase Extraction procedure with various cartridges.

The standard stock solutions, standard solutions, Calibration curve samples

(CC), Quality control (QC) Samples, blank plasma samples were prepared. The

standard solutions, CC samples, QC samples and plasma sample solutions were

injected with the optimised chromatographic conditions and the chromatograms were

recorded. The quantification of the chromatogram was performed using peak area

ratios (response factor) of the drug to internal standard. The calibration curves are

constructed routinely for spiked plasma containing drug and internal standard during

the process of pre-study validation and in-study validation.

6

The Pharmacokinetic parameters were determined for individual drug

treatments from the observed plasma concentration-time data. The area under the

plasma concentration-time curves (AUC) were calculated by trapezoidal rule from

time zero to the last observed concentration. The statistical analysis was carried out

for Cmax, AUC (0-t) and AUC (0-∞).

The release characteristics of selected drugs in their formulations is carried out

using USP XXIII dissolution apparatus (type I, basket; type II, paddle), at different

rpm, with the media of pH 1.2, 4.5, 6.8, distilled water and 7.4 buffers maintained at

37±0.5˚C. Dissolution tests were performed on twelve tablets. Percentage drug

release at various time intervals was calculated and compared. Difference factor (f1)

and a similarity factor (f2) were calculated.

The Wagner-Nelson method was used to calculate the percentage of the

selected drugs dose absorbed. The percent absorbed is determined by dividing the

amount absorbed at any time by the plateau value, ke,AUC (0-ω) and multiplying this

ratio by 100. The percentage of drug dissolved was determined using the

aforementioned dissolution testing method and the fraction of drug absorbed was

determined using the method of Wagner-Nelson. Linear regression analysis was used

to examine the relationship between percentage of drug dissolved and the percentage

of drug absorbed. The percentage of drug un-absorbed was calculated from the

percentage absorbed. The slope of the best-fit line for the semi-log treatment of this

data was taken as the first order rate constant for absorption. The dissolution rate

constants were determined from percentage released Vs the square root of time.

Linear regression analysis was applied to the in-vitro and in-vivo correlation plots

and coefficient of determination (r2), slope and intercept values were calculated.

The predictability of the IVIVC was examined by using the mean in-vitro

dissolution data and mean in-vivo pharmacokinetics of the selected modified release

formulations. These two data points, along with the zero-zero intercept were used to

calculate the expected absorption rate constants and predicted plasma concentration.

To further assess the predictability and the validity of the correlations, IVIVC

model-predicted Cmax and AUC values were determined for each formulation. The

percent prediction errors for Cmax and AUC were calculated. Level A correlation was

observed at the in-vitro dissolution conditions developed. These dissolution methods

predicted also the best absorption rate for the selected modified release formulations.

The target to find out a predictive in-vitro dissolution method was reached gradually.

The validity of the correlation was also assessed by determining how well the IVIVC

model could predict the rate and extent of absorption as characterized by Cmax and

AUC. The percent prediction error of ≤ 10 % for Cmax and AUC was obtained, which

establishes the predictability of the developed IVIVC model. The developed

dissolution methods using Apparatus I, pH 6.8 at 75 rpm for Pregabalin and

Apparatus I, pH 1.2 at 75 rpm for Pramipexole found to yield acceptable IVIVC. The

developed dissolution methods can surrogate for human bioequivalence studies and

also to discriminate batches which are non-bioequivalent.

vii

888

ACKNOWLEDGEMENT

First and foremost, praises and thanks to the God Almighty, for his love and

showers of blessings throughout my life and to complete my research work

successfully.

I extend my profound thanks to Thiru. A.C. Shanmugam, Founder,

Mr. A.C.S. Arun Kumar, President, Dr. Meer Mustafa Hussain,

Vice Chancellor, Dr. C.B. Palanivelu, Registrar, Dr. A. Thirunavukkarasu,

Dean Research and Dr. T.S. Saravanan, Research Coordinator and

Dr. Rajeshwari Hari, Head of Department, Biotechnology of Dr. MGR

Educational and Research Institute University for providing the wonderful

opportunity and for supporting me all through my research work.

My deepest gratitude is to my Guide, Dr. S. Karpagam, Associate Professor,

Queen Mary’s College, Chennai for providing invaluable guidance throughout this

research.

I would like to express my special thanks to my Co-guide,

Prof. Dr. M. Deecaraman, Senior Professor, Department of Biotechnology for his

guidance and encouragement.

I heartfelt thanks to my research committee member

Dr. M. Vijayalakshmi, Professor, Department of Biotechnology for her comments

and suggestions.

I am extending my heartfelt thanks to my beloved husband

Dr. M. Vasudevan, my children Mr. V. Yeshwanth and Ms. V. Geethanjali and

also all my family members and friends for their love, prayers, understanding and

support to complete this research work and in general.

Though only my name appears on the cover of this dissertation, a great many

people have contributed to its production. I owe my gratitude to all those people who

have made this dissertation possible and because of whom my graduate experience

has been one that I will cherish forever.

9

TABLE OF CONTENTS

Chapter No. Title Page No.

1

ABSTRACT

LIST OF TABLES

LIST OF FIGURES

LIST OF ABBREVATIONS AND SYMBOLS

INTRODUCTION

iv

xiv

xviii

xxi

1

1.1 In-vitro and in-vivo Correlations 1

1.2 Bio-pharmaceutics Classification System (BCS) 2

1.3 Bio-availability Studies for Development of IVIVC 3

1.4 In-vitro dissolution 5

1.5 IVIVC Models 7

1.5.1 Level A Correlation 7

1.5.2 Level B Correlation 8

1.5.3 Level C Correlation 8

1.5.4 Multiple-level C correlation 8

1.5.5 Level D correlation 9

1.5.6 IVIVC Model Development 9

1.5.7 IVIVC Model Validation 9

1.6 Drug Profile 11

1.6.1 Pregabalin 11

1.6.2 Pramipexole 12

1.7 Scope and Object of the Present Study 13

1.7.1 Bioequivalence study design and data handling 14

1.7.3 Development of in-vitro dissolution studies 15

1.7.4 In-vitro and in-vivo data analysis 15

1.7.5 Development of IVIVC correlations 16

2 LITERATURE SURVEY 17

3 MATERIALS AND METHODS 40

3.1 Reagents, Chemicals and Instruments 40

3.1.1 Reagents and Chemicals used 40

3.1.2 Instruments used 40

3.2 Bioequivalence study 41

3.2.1 Study Design 41

3.2.2 Product for Evaluation 41

3.2.3 Subjects 41

3.2.4 Ethics Review Procedure 42

3.2.5 Drug Administration 42

3.2.6 Subject Monitoring 43

3.2.7 Meals and Food Restrictions 43

3.2.8 Extraction of drugs from plasma 43

3.2.9 Estimation of Pharmacokinetic Parameters 44

3.3 Analytical Method Development 44

3.3.1 Selection of Molecular Ions 44

3.3.2 Selection of Source Parameters 44

3.3.3 Column Selection 46

3.3.4 Selection of Mobile Phase 46

3.3.5 Effect of Injection Volume 46

3.3.6 Effect of Flow Rate 46

3.3.7 Selection of Internal standard 47

3.3.8 Selection of Extraction Procedure 47

3.4 Method Validation 49

10


1.7.2 Development of LC-MS/MS methods for the 14

estimation of selected drugs in plasma samples.

11


3.4.1 System Suitability 49

3.4.2 Linearity 50

3.4.3 Accuracy and Precision 50

3.4.4 Recovery 50

3.4.5 Selectivity 51

3.4.6 Sensitivity 51

3.4.7 Matrix Effect 51

3.4.8Carry over Test 51

3.4.9 Stability 52

3.5 Estimation of Pregabalin in Plasma Samples 53

3.5.1 Preparation of standard Stock Solution 53

3.5.2 Preparation of Calibration Curve Samples Stock 53

Dilutions

3.5.3 Internal standard stock solution 53

3.5.4 Preparation of QC Samples 55

3.6 Estimation of Pramipexole in Plasma Samples 57

3.6.1 Preparation of Pramipexole Calibration Curve 57

Samples Stock Dilutions

3.6.2 Stock Dilution for Pramipexole Quality Control 58

Sample

3.6.3 Preparation of Quetiapine Stock Solution 58

3.6.4 Preparation of Quetiapine Stock Dilutions 58

3.6.5 Pramipexole Calibration Standards in Human 59

plasma

3.6.6 Preparation of Quality Control Samples of 60

Pramipexole

3.7 Determination of Pharmacokinetic Parameters 60

3.8 Development of in-vitro dissolution studies 61

3.9 In-vitro and in-vivo correlation 61

3.9.1 Validation of IVIVC 63


4 RESULTS AND DISCUSSION 65

4.1 Bioequivalence study design and data handling 65

4.2 Development of LC-MS/MS Methods for the Estimation of 66

Pregabalin and Pramipexole in Plasma Samples

4.3 Method Validation for Pregabalin 69

4.3.1 Linearity 69


4.3.3 Matrix Selectivity 71


4.3.5 Matrix effect 71

4.3.6 Carry over Test 72

4.3.7 Stability 72

4.4 Validation of Pramipexole 82

4.4.1 Linearity 82


4.4.3 Matrix Selectivity 83


4.4.5 Matrix effect 84

4.4.6 Carry over Test 84

4.4.7 Stability 84

4.5 Estimation of Pregabalin and Pramipexole in plasma 96

samples

4.6 In-vitro and in-vivo correlations for Pregabalin 107

4.6.1 In-vivo data analysis 107

4.6.2 In-vitro data analysis 109

4.6.3 In-vitro and in-vivo correlations 109

4.6.4 Internal validation 110

4.6.5 External validation 111

4.7 In-vitro and in-vivo correlations for Pramipexole 135

4.7.1 In-vivo data analysis 135

xii

13


4.7.2 In-vitro data analysis 137

4.7.3 In-vitro and in-vivo correlations 137

4.7.4 Internal validation 139

4.7.5 External validation 139

5 SUMMARY AND CONCLUSION 164

REFERENCES 168

LIST OF PUBLICATIONS 174

14

LIST OF TABLES

Table No. Title Page No.

3.1 Source Parameters for Pregabalin 45

3.2 Source Parameters for Pramipexole 45

3.3 Liquid – Liquid Extraction of Pregabalin 47

3.4 Preparation of Pregabalin Standards for Calibration Curve 54

3.5

(Dilution I)

Preparation of Pregabalin Standards for Calibration Curve 55

3.6

(Dilution II)

Preparation of Pregabalin QC Samples (Dilution-I) 56

3.7 Preparation of Pregabalin QC Samples (Dilution-II) 56

3.8 Stock Dilution for Pramipexole Calibration Standard 57

3.9 Stock Dilution for Pramipexole Quality control Samples 58

3.10 Pramipexole Calibration standards in Human plasma 59

3.11 Pramipexole Quality Control samples in Human Plasma 60

4.1 Intercept, Slope and Correlation Coefficient Values for 73

4.2

Pregabalin Calibration curve

Intra-batch Accuracy and Precision of Pregabalin 74

4.3 Inter-batch Accuracy and Precision of Pregabalin 75

4.4 Recovery of Pregabalin 76

4.5 Recovery of Tramadol (lnternal Standard) 77

4.6 Matrix Selectivity of Pregabalin 78

4.7 Lower Limit of Quantitation (LLOQ) 78

4.8 Matrix Effect of Pregabalin 79

4.9 Carry over test of Pregabalin 79

4.10 Freeze and Thaw Stability of Pregabalin 80

4.11 Bench Top stability of Pregabalin 81

15


4.12 Intercept, Slope and Correlation coefficient values for

Pramipexole Calibration curve

86

4.13 Intra-batch Accuracy and Precision of Pramipexole 87

4.14 Inter-batch Accuracy and Precision of Pramipexole 88

4.15 Recovery of Pramipexole 89

4.16 Recovery of Quetiapine (Internal Standard) 90

4.17 Matrix Selectivity of Pramipexole 91

4.18 Lower Limit of Quantitation (LLOQ) of Pramipexole 92

4.19 Matrix Effect of Pramipexole 93

4.20 Carry over test of Pramipexole 94

4.21 Freeze and Thaw stability of Pramipexole 94

4.22 Bench Top stability of Pramipexole 95

4.23 Individual Plasma Concentrations (mcg/ml) and

Pharmacokinetic Parameters for Pregabalin Immediate Release

113

4.24

Formulation

Individual Plasma Concentrations (Mcg/Ml) and Pharmacokinetic 115

Parameters for Pregabalin Modified Release Formulation

4.25 Mean Plasma concentrations (mcg/ml) for Pregabalin 117

4.26 Pharmacokinetic Profile of Pregabalin 119

4.27 Statistical data for Pregabalin Immediate Release Vs Modified

Release Formulations

120



121



122

4.30 Paired Sample Test for Pregabalin 123

4.31 Cumulative percentage dissolved at 50 rpm for Pregabalin 124

4.32

formulations

Cumulative percentage dissolved at 75 rpm for Pregabalin 126

formulations

16


4.33 Similarity factors for Pregabalin modified release dosage forms

in Various dissolution condition

128

4.34 IVIVC model regression of % absorbed vs. % dissolved for

Pregabalin Formulation using pH 6.8 at 50 and 75 rpm

129

4.35 Observed and IVIVC model predicted Cmax and AUC values

for Pregabalin

132

4.36 Prediction errors (%) associated with Cmax and AUC for

Pregabalin

132

4.37 IVIVC model linear regression plots of % absorbed vs %

dissolved for Pregabalin tablets using pH 6.8, at 75 rpm

134

4.38 Individual plasma concentrations (mcg/ml) and pharmacokinetic

parameters for Pramipexole Immediate Release Formulation

141

4.39 Individual plasma concentrations (mcg/ml) and pharmacokinetic

parameters for Pramipexole Modified Release Formulation

143

4.40 Plasma concentrations (mcg/ml) of Pramipexole 145

4.41 Pharmacokinetic profile of Pramipexole 147

4.42 Statistical data for Pramipexole Immediate Release Vs Modified 148

4.43

Release Formulation

Statistical data for Pramipexole Immediate Release Vs Modified 149

4.44

Release Formulation

Statistical data for Pramipexole Immediate Release Vs Modified 150

4.45

Release Formulation

Paired Sample Test for Pramipexole 151

4.46 Cumulative percentage dissolved at 50 rpm for Pramipexole test

formulations

152

4.47 Cumulative percentage dissolved at 75 rpm for Pramipexole test

formulations

154

4.48 Similarity Factors for Pramipexole Modified Release

Formulations in Various Dissolution Conditions

156

xvii



Pramipexole Formulations using pH 1.2 and 4.5 at 50 rpm

157



159

4.51 Observed and IVIVC model predicted Cmax and AUC values

for Pramipexole

161

4.52 Prediction errors (%) associated with Cmax and AUC for

Pramipexole

163

181818

LIST OF FIGURES

Figure No. Title Page No.

4.1 Calibration Curve of Pregabalin 73

4.2 Calibration Curve of Pramipexole 86

4.3 Mass Spectrum of Pregabalin (Parent Ion) 97

4.4 Mass Spectrum of Pregabalin (Product Ion) 97

4.5 Mass Spectrum of Tramadol (Parent Ion) 98

4.6 Mass Spectrum of Tramadol (Product Ion) 98

4.7 Representative chromatogram of processed blank plasma 99

4.8 Typical chromatogram obtained from LLOQ 99

4.9 Typical chromatogram obtained from LQC 100

4.10 Typical chromatogram obtained from MOQ 100

4.11 Typical chromatogram obtained from HQC 101

4.12 Typical chromatogram obtained from ULOQ 101

4.13 Mass Spectrum ofPramipexole(Parent Ion) 102

4.14 Mass Spectrum of Pramipexole(Product Ion) 102

4.15 Mass Spectrum of Quetiapine (Parent Ion) 103

4.16 Mass Spectrum of Quetiapine (Product Ion) 103

4.17 Representative chromatogram of processed blank plasma 104

4.18 Typical chromatogram obtained from LLOQ 104

4.19 Typical chromatogram obtained from LQC 105

4.20 Typical chromatogram obtained from MOQ 105

4.21 Typical chromatogram obtained from HQC 106

4.22 Typical chromatogram obtained from ULOQ 106

4.23 Mean Concentration Time Curve for Pregabalin 118

4.24 Cumulative Pregabalin Release Vs Time Profile for 125

Immediate and Modified Release Formulations at 50 RPM

19


4.25 Cumulative Pregabalin Release Vs Time Profile for


127

4.26 IVIVC model Linear Regression Plot of % Absorbed Vs %

Dissolved for Immediate and Modified Release Pregabalin

130

4.27

Formulations using pH 6.8 Buffer at 50 RPM

IVIVC model Linear Regression Plot of % Absorbed Vs % 130

Dissolved for Immediate and Modified Release Pregabalin


4.28 Cumulative Pregabalin Release Vs Square Root of Time

Profile for Immediate and Modified Release Pregabalin

131

4.29


Cumulative Pregabalin Release Vs Square Root of Time 131

Profile for Immediate and Modified Release Pregabalin


4.30 Observed and Predicted Pregabalin Plasma Concentration for

the Immediate Release Pregabalin Formulations using IVIVC

Modeland Modified Release Formulations at 50RPM

133


the Modified Release Pregabalin Formulations using IVIVC

133

4.32

Model

Mean Concentration Time Curve for Pramipexole 146



153



155


Dissolved for Immediate and Modified Release Pramipexole

158


20




158

4.37


IVIVC model Linear Regression Plot of % Absorbed Vs % 160





160

4.39


Observed and Predicted Pregabalin Plasma Concentration for 162

the Immediate Release Pregabalin Formulations using IVIVC

Model


the Modified Release Pregabalin Formulations using IVIVC

162

Model

21

LIST OF ABBREVATIONS AND SYMBOLS

ANOVA : Analysis of variance

AQ : Aqueous

AR : Analytical reagent

BA : Bioavailability

BCS : Bio-pharmaceutics Classification System

BE : Bioequivalence CC

: Calibration curve CS :

Comparison sample

CV : Coefficient of variation

c(t) : plasma concentration

oC : Degree centigrade

F : Fraction absorbed

FAB : Fast atom bombardment

FD : Field desorption

FT : Freeze thaw

g : Gram

GC : Gas chromatography

GC-MS : Gas chromatography-mass spectrometry

GR : General reagent

HPLC : High performance liquid chromatography

HQC : High Quality control

ICH : International conference on harmonization

ID : Identity

IS : Internal standard

IV : Intravenous

IVIVC : In-vitro and in-vivo Correlations

ka : absorption rate constant

xxii

ke : elimination rate constant

K2EDTA : Dipotassium ethylene Diamine tetra acetic acid

LC-MS : Liquid Chromatography-Mass Spectrometry

LLOQ : Lower limit of quantification

LOD : Loss on drying

LOQ : Limit of quantification

LOQQC : Limit of quantification of quality control

LQC : Lower quality control

m/z : mass-to-charge ratio

MALDI : Matrix assisted laser desorption ionisatoin

µg/mL : Microgram per mille litre

µm : Micrometer

mg : milligram

mL : milliliter

msec : Millisecond

mM : milli Molar

mm : millimeter

MQC : Middle quality control

MRM : Multiple Reaction Monitoring

MS : Mass Spectrometry

NDA : New drug application

ng/mL : nanogram per milliliter

NMR : Nuclear magnetic resonance

P&A : Precision and accuracy

% : Percentage

Pg/mL : pictogram/milliliter

ppm : Parts per million

QC : Quality Control

QMS : Quadrupole mass spectrometer

R.S.D. : Relative standard deviation

RIA : Radio immune assay

RP : Reverse phase

xxiii

Rpm : Revolutions per minute

rabs : Absorption rate time course

SAS : Statistical analysis system

SD : Standard Deviation

SS : Stock solution

STD : Standard

tmax : Time to reach maximum peak plasma

t1/2 : Half life

UPLC : Ultra performance liquid chromatography

USFDA : United States Food and Drug Adminstration

USP : United States of Pharmacopoeia

UV : Ultra violet

Vd : volume of distribution

V/V : Volume by volume W

% : Weight percentage

WS : Working standard

µL/min : Micro liter per minute

CHAPTER 1

INTRODUCTION

1.1 In-vitro and in-vivo Correlations

In recent years, the concept and application of the in-vitro and in-vivo

Correlation (IVIVC) for pharmaceutical dosage forms have been a main focus of

attention of pharmaceutical industry, academia, and regulatory sectors. Development

and optimization of formulation is an integral part of manufacturing and marketing

of any therapeutic agent which is indeed a time consuming and costly process.

Optimization process may require alteration in formulation composition,

manufacturing process, equipment and batch sizes (Dickinson et al. 2008). If these

types of changes are applied to a formulation, studies in human healthy volunteers

may be required to prove that the new formulation is bioequivalent with the old one.

Certainly, implementation of these requirements not only halts the marketing of the

new formulation but also increases the cost of the optimization processes. It would

be, desirable, therefore, to develop in-vitro tests that reflect bioavailability data. A

regulatory guidance for both immediate and modified release dosage forms has been,

therefore, developed by the regulatory authorities to minimize the need for

bioavailability studies as part of the formulation design and optimization.

IVIVC can be used in the development of new pharmaceuticals to reduce the

number of human studies during the formulation development (Chakshu

Bhatia et al. 2012). The main objective of an IVIVC is to serve as a surrogate for

in•vivo bioavailability and to support bio-waivers. IVIVCs could also be employed

to establish dissolution specifications and to support and/or validate the use of

dissolution methods. This is because the IVIVC includes in-vivo relevance to in-vitro

dissolution specifications. It can also assist in quality control for certain scale-up and

2

post-approval changes, for instance, to improve formulations or to change production

processes (Jost 2010). There must be some in-vitro means of assuring that each batch

of the same product will perform identically in-vivo.

The term correlation is frequently employed within the pharmaceutical and

related sciences to describe the relationship that exists between variables.

Mathematically, the term correlation means interdependence between quantitative or

qualitative data or relationship between measurable variables and ranks. From

biopharmaceutical standpoint, correlation could be referred to as the relationship

between appropriate in-vitro release characteristics and in-vivo bioavailability

parameters.

IVIVC is a predictive mathematical model describing the relationship between

an in-vitro property of a dosage form and a relevant in-vivo response (Elena Soto et

al. 2010). Generally, the in-vitro property is the rate or extent of drug dissolution or

release while the in-vivo response is the plasma drug concentration or amount of drug

absorbed.

A successful IVIVC model can be developed, if in-vitro dissolution is the rate-

limiting step in the sequence of events leading to the appearance of the drug in the

systemic circulation following oral or other routes of administration. Thus, the

dissolution test can be utilized as a surrogate for bioequivalence studies (involving

human subjects) if the developed IVIVC is predictive of in-vivo performance of the

product (Koenen-Bergmann et al. 2008). For orally administered drugs, IVIVC is

expected for highly permeable drugs or drugs under dissolution rate-limiting

conditions as supported by the Biopharmaceutical Classification System (BCS).

1.2 Bio-pharmaceutics Classification System (BCS)

Bio-pharmaceutics Classification System (BCS) is a fundamental guideline

for determining the conditions under which in-vivo and in-vitro correlations are

expected. In the BCS, a drug is classified as one of the following four classes based

solely on its solubility and intestinal permeability;

3

Class I(High solubility/High permeability) drugs exhibit a high Absorption

number and a high Dissolution number. The rate limiting step to drug absorption is

the drug dissolution or gastric emptying rate if dissolution is very rapid.

Class II (Low solubility/High permeability) drugs have a high Absorption

number but a low Dissolution number. In-vivo drug dissolution is then a rate limiting

step for absorption (except at very high Dose number). The absorption for Class II

drugs are usually slower than Class I and occur over a longer period of time.

Class III (High solubility/Low permeability) drugs exhibit a high variability in

rate and extent of drug absorbed. Since the dissolution is rapid, the variation is due to

alteration of GI physiological properties and membrane permeation rather than

dosage form factors.

Class IV (Low solubility/Low permeability) drugs have low solubility and low

permeability and exhibit a lot of problems for effective oral administration.

IVIVC are usually expected for Class I and Class II drugs.

1.3 Bio-availability Studies for Development of IVIVC

A bioavailability study should be performed to characterize the plasma

concentration versus time profile for each of the formulation. Bioavailability studies

for IVIVC development should be performed with sufficient number of subjects to

characterize adequately the performance of the drug product under study (Quinones

et al. 2010). In prior acceptable data sets, the number of subjects has ranged from 6

to 36. Although crossover studies are preferred, parallel studies or cross-study

analyses may be acceptable. The latter may involve normalization with a common

reference treatment. The reference product in developing an IVIVC may be an

intravenous solution, an aqueous oral solution, or an immediate release product.

IVIVCs are usually developed in the fasted state. When a drug is not tolerated in the

fasted state, studies may be conducted in the fed state.

Drug absorption from GI tract following ingestion of an oral dosage form could

be influenced by a number of in-vivo variables. For the determination of reproducible

4

in-vivo parameters and consequently useful in-vitro and in-vivo relationship, it is

imperative that such variables be identified. As a result, the study should be designed

appropriately that as many variables as possible be eliminated or controlled to

prevent or minimize their disturbance of IVIVC. Control or standardization of a

number of variables including subject selection criteria such as age, gender, physical

condition, etc., and the abstinence by the subject from coffee and other xanthene’s

containing beverages or food, alcohol, irregular diets and smoking before and during

the study should be taken in to consideration. Food, posture and exercise may

influence hepatic blood flow which in turn may substantially affect the absorption of

drugs possessing high hepatic extraction ratio.

Liquid chromatographic coupled with tandem mass spectrometer (LC-MS/MS)

have become the methods of choice for measuring drugs in biological fluids, yielding

concentration versus time data for drug compounds from in-vivo samples such as

plasma (Alessandro Musenga et al. 2008).

LC-MS/MS instrument consists of three major components

LC (to resolve a complex mixture of components)

An interface (to transport the analyte in to the ion source) of a mass

spectrometer

Mass spectrometer (to ionize and mass analyze the individually

resolved components)

The quadrapole mass spectrometer is the most common mass analyzer. Its

compact size, fast scan rate, high transmission efficiency and modest vacuum

requirements are ideal for small inexpensive instruments. Most quadrupole

instruments are limited to unit m/z resolution and have a mass range of m/z 1000.

Many bench top instruments have mass range of m/z 500 but research instruments

are available with mass range upto m/z 4000.

5

Bioavailability studies can be accessed via plasma or urine data using the

following parameters:

Area under the plasma time curve (AUC), or the cumulative amount of

drug excreted in urine,

Maximum concentration (Cmax), or rate of drug excretion in urine and

Time of maximum concentration (Tmax).

Several approaches can be employed for determining the in-vivo absorption.

Wagner-Nelson, Loo-Riegelman and numerical de-convolution are such methods.

Wagner Nelson andLoo-Riegelman are both model dependent methods in which the

former is used for a one compartment model and the latter is for a multi-

compartment system.

The Wagner Nelson method is less complicated than the LooRiegelman, as

there is no requirement for intravenous data. However, misinterpretation on the

terminal phase of the plasma profile is likely in the occurrence of a flip-flop

phenomenon in which the rate of absorption is slower than the rate of elimination.

De-convolution is a numerical method used to estimate the time course of drug

input using a mathematical model based on the convolution integral. For example,

the absorption rate time course (rabs) that resulted in plasma concentration (c(t)) may

be estimated by solving the convolution integral equation for absorption rate time

course. De-convolution is a model independent method which can be employed for

either one-or multiple-compartment models.

1.4 In-vitro dissolution

Drug absorption from a solid dosage form following oral administration

depends on the release of the drug substance from the drug product, the dissolution

or solubilization of the drug under physiological conditions, and the permeability

across the gastrointestinal tract (Jose David et al. 2013). Because of the critical

nature of the first two of these steps, in-vitro dissolution may be relevant to the

prediction of in- vivo performance.

6

The purpose of in-vitro dissolution studies in drug development process is to

assess the lot-to-lot quality of a drug product, guide development of new

formulations; and ensure continuing product quality and performance after certain

changes, such as changes in the formulation, the manufacturing process, the site of

manufacture, and the scale-up of the manufacturing process (Pui Shan Chana et al.

2014).

Modified release dosage forms typically require dissolution testing over

multiple time points, and IVIVC plays an important role in setting these

specifications. Specification time points are usually chosen in the early, middle and

late stages of the dissolution profiles. In the absence of an IVIVC, the range of the

dissolution specification rarely exceeds ± 10% of the dissolution of the pivotal

clinical batch. In the presence of IVIVC, however, wider specifications may be

applicable based on the predicted concentration-time profiles of test batches being

bioequivalent to the reference batch.

However, for the IVIVC perspective, dissolution is proposed to be a surrogate

of drug bioavailability. Thus, a more rigorous dissolution standard may be necessary

for the in-vivo waiver. Generally, a dissolution methodology, which is able to

discriminate between the study formulations and which best, reflects the in-vivo

behavior would be selected.

The utilization of in-vitro dissolution data for predicting in-vivo performance

requires a meaningful method of transformation of the data (Lake et al.1999). A

direct comparison between in-vitro and in-vivo data is not possible since the

measurement of in-vivo release/absorption profiles is not straightforward. There are

also arguments about appropriateness of using classical single (experimental) point

pharmacokinetic parameters like Cmax and Tmax to assess

bioavailability/bioequivalence of modified release preparations. Various

mathematical models and equations have been described in literature for conversion

of directly measurable pharmacokinetic data to release/absorption characteristic of

the drug from the dosage form for comparison with in-vitro dissolution data.

7

1.5 IVIVC Models

IVIVC models are developed to explore the relationships between in-vitro

dissolution/release and in-vivo absorption profiles. This model relationship facilitates

the rational development and evaluation of immediate/extended release dosage forms

as a tool for formulation screening, in setting dissolution specifications and as a

surrogate for bioequivalence testing.

IVIVC modeling involves three stages, which are,

model development,

model validation, and

model application to different scenarios.

Developing a predictable IVIVC depends upon the complexity of the delivery

system, its formulation composition, method of manufacture, physicochemical

properties of the drug and the dissolution method.

Five correlation levels have been defined in the IVIVC FDA guidance. The

concept of correlation level is based upon the ability of the correlation to reflect the

complete plasma drug level-time profile which will result from administration of the

given dosage form.

1.5.1 Level A Correlation

This level of correlation is the highest category of correlation and represents a

point-to-point relationship between in-vitro dissolution rate and in-vivo input rate of

the drug from the dosage form (Kortejarvi et al. 2002). Generally, percent of drug

absorbed may be calculated by means of model dependent techniques such as

Wagner-Nelson procedure or Loo-Riegelman method or by model-independent

numerical de-convolution. The purpose of Level A correlation is to define a direct

relationship between in-vivo data such that measurement of in-vitro dissolution rate

alone is sufficient to determine the biopharmaceutical rate of the dosage form. In the

case of a level A correlation, an in-vitro dissolution curve can serve as a surrogate for

in-vivo performance (Malte Selch Larsen et al. 2015). Therefore, a change in

8

manufacturing site, method of manufacture, raw material supplies, minor formulation

modification, and even product strength using the same formulation can be justified

without the need for additional human studies.

1.5.2 Level B Correlation

A level B IVIVC utilizes the principles of statistical moment analysis. In this

level of correlation, the mean in-vitro dissolution time (MDT vitro) of the product is

compared to either mean in-vivo residence time (MRT) or the mean in-vivo

dissolution time (MDT vivo). Although a level B correlation uses all of the in-vitro

and in-vivo data, it is not considered to be a point-to-point correlation, since there are

a number of different in-vivo curves that will produce similar mean residence time

values. A level B correlation does not uniquely reflect the actual in-vivo plasma level

curves. Therefore, one cannot rely upon a level B correlation alone to justify

formulation modification, manufacturing site change, excipient source change, etc.,

1.5.3 Level C Correlation

In this level of correlation, one dissolution time point (t50%, t90%, etc.) is

compared to one mean pharmacokinetic parameter such as AUC, tmax or Cmax.

Therefore, it represents a single point correlation and does not reflect the entire shape

of the plasma drug concentration curve, which is indeed a crucial factor that is a

good indicative of the performance of modified-release products. This is the weakest

level of correlation as partial relationship between absorption and dissolution is

established. Due to its obvious limitations, the usefulness of a Level C correlation is

limited in predicting in-vivo drug performance.

1.5.4 Multiple-level C correlation

A multiple level C correlation relates one or several pharmacokinetic

parameters of interest (Cmax, AUC, or any other suitable parameters) to the amount of

drug dissolved at several time points of the dissolution profile

(Gregor Bender et al. 2009). A multiple point level C correlation may be used to

justify a bio-waiver, provided that the correlation has been established over the entire

dissolution profile with one or more pharmacokinetic parameters of interest. A

9

relationship should be demonstrated at each time point at the same parameter such

that the effect on the in-vivo performance of any change in dissolution can be

assessed. If such a multiple level C correlation is achievable, then the development of

a level A correlation is also likely. A multiple Level C correlation should be based on

at least three dissolution time points covering the early, middle, and late stages of the

dissolution profile.

1.5.5 Level D correlation

Level D correlation is a rank order and qualitative analysis and is not

considered useful for regulatory purposes. It is not a formal correlation but serves as

an aid in the development of a formulation or processing procedure.

1.5.6 IVIVC Model Development

Development of an IVIVC consists of model development and model

validation (Rossi et al. 2007). A number of methods are available to probe the in-vivo

and in-vitro relationships. Among the earliest methods are the two stage de-

convolution methods that involve estimation of the in-vivo absorption profile from

the concentration-time data using the Wagner-Nelson or Loo-Riegelman methods

(Stage 1). Subsequent to the estimation of the in-vivo absorption profile, the

relationship with in-vitro dissolution is evaluated (Stage 2). More recently, one stage

convolution-based approaches for IVIVC have been investigated. The one stage

convolution methods compute the in-vivo absorption and simultaneously model the

in-vivo and in-vitro data. While the two stage method allows for systematic model

development, the one stage method obviates the need for the administration of an

intravenous, oral solution or immediate release bolus dose (Soto et al. 2010).

1.5.7 IVIVC Model Validation

The objective of any mathematical predictive tool is to successfully predict the

outcome (in-vivo profile) with a given model and test condition (in-vitro profile).

Integral to the model development exercise is model validation, which can be

accomplished using data from the formulations used to build the model (internal

validation) or using data obtained from a different (new) formulation (external

10

validation). While internal validation serves the purpose of providing the basis for

the acceptability of the model, external validation is superior and affords greater

“confidence” in the model.

Internal Validation

Using the IVIVC model, for each formulation, the relevant exposure

parameters (Cmax and AUC) are predicted and compared to the actual (observed)

values. The prediction errors are calculated (Jantratid et al. 2009).

The criteria set in the FDA guidance on IVIVC are as follows: For Cmax and

AUC, the mean absolute percent prediction error (% PE) should not exceed 10%, and

the prediction error for individual formulations should not exceed 15%.

External Validation

For establishing external predictability, the exposure parameters for a new

formulation are predicted using its in-vitro dissolution profile and the IVIVC model

and the predicted parameters are compared to the observed parameters (Gomez-

Mantilla et al. 2014). The prediction errors are computed as for the internal

validation. For Cmax and AUC, the prediction error for the external validation

formulation should not exceed 10%. A prediction error of 10% to 20% indicates

inconclusive predictability and illustrates the need for further study using additional

data sets. For drugs with narrow therapeutic index, external validation is required

despite acceptable internal validation, whereas internal validation is usually

sufficient with non-narrow therapeutic index drugs.

11

1.6 Drug Profile

For the present study, based on the solubility and permeability, Pregabalin and

Pramipexole were selected for developing IVIVC correlation.

1.6.1 Pregabalin

Chemical Name : (3S)-3-aminomethyl-5-methyl hexanoic acid.

Molecular Formula : C8H17NO2

Solubility : It is freely soluble in water and basic and acidic

aqueous solutions.

Molecular structure :

Mechanism of Action

An anticonvulsant activity of Pregabalin is mediated through an

alpha 2-delta site (an auxiliary subunit of voltage-gated calcium channels) in central

nervous system tissues (Charles et al. 2007). In-vitro Pregabalin reduces the calcium

dependent release of several neurotransmitters, possibly by modulation of calcium

channel function (Robert Lee et al. 2008).

Pharmacokinetics

Pregabalin is rapidly absorbed when administered on an empty stomach, peak

plasma concentrations occurring within one hour. Pregabalin oral bioavailability is

estimated to be greater than or equal to 90% and is independent of dose

(Daniel et al. 2007). The volu m e of dis t ribution of Pregabalin for an orally

administered dose is approximately 0.56 L/kg and is not bound to plasma proteins.

http://en.wikipedia.org/wiki/Volume_of_distribution

12

Pregabalin undergoes negligible metabolism in humans (Meihua Rose Feng et al.

2001). Approximately 98% of the Pregabalin recovered in the urine was unchanged.

The N-methyl Pregabalin is the major metabolite (Thrasivoulos et al. 2008).

Pregabalin is eliminated from the systemic circulation primarily by renal excretion as

unchanged drug. R e n a l c l ea r a n c e of Pregabalin is 73 mL/minute.

1.6.2 Pramipexole

Chemical Name : (S)-2-amino-4,5,6,7-tetrahydro-6 (propylamino)

benzothiazole dihydrochloride monohydrate.

Molecular Formula : C10H17N3S·2HCl·H2O

Solubility : It is freely soluble in water

Molecular Structure:

Mechanism of Action

Pramipexole is used for the treatment of Parkinson’s disease

(Salin et al.2009;Chwieduk and Curran 2010 and Trond Kvernmo et al. 2006). It is a

non-ergot dopamine agonist with high relative in-vitro specificity and full intrinsic

activity at the D2 subfamily of dopamine receptors, binding with higher affinity to

D3 than to D2 or D4 receptor subtypes (Schapira et al. 2009;Grosset et al. 2005 and

Wolfram Eisenreich et al. 2010). It stimulates dopamine receptors in the striatum

(Dziedzicka-Wasylewska et al. 2001 and Rascol et al. 2010).

http://en.wikipedia.org/wiki/Renal_clearance

13

Pharmacokinetics

Pramipexole is rapidly absorbed, reaching peak concentrations in

approximately two hours (Poewe et al. 2009 and Dansirikul et al. 2009). The

absolute bioavailability of Pramipexole is greater than 90%, indicating that it is well

absorbed and undergoes little pre-systemic metabolism (Abib et al. 2012 and Hauser

et al. 2009). Pramipexole distributes into red blood cells (Jenner et al. 2009). Urinary

excretion is the major route of Pramipexole elimination, with 90% of a Pramipexole

dose recovered in urine, almost all as unchanged drug (Peter Jenner et al. 2009)

1.7 Scope and Object of the Present Study

IVIVC can be used in the development of new pharmaceuticals to reduce the

number of human studies during the formulation development, as the main objective

of an IVIVC is to serve as a surrogate for in-vivo bioavailability and to support

biowaivers. Thus the need for a tool to reliably correlate in-vitro and in-vivo drug

release data has exceedingly increased. Such a tool shortens the drug development

period, economizes the resources and leads to improved product quality. With the

proliferation of modified-release products, it becomes necessary to examine the

concept of IVIVC in greater depth. Investigations of IVIVC are increasingly

becoming an integral part of extended release drug development. There must be

some in-vitro means of assuring that each batch of the same product will perform

identically in-vivo.

The aim of IVIVC is thus to enable the dissolution test to be used as a

surrogate for bioequivalence studies. Dissolution testing of modified release

formulations poses many challenges. These challenges include developing and

validating the test method, ensuring that the method is appropriately discriminatory

and addressing the potential for an IVIVC.

Bioavailability and bioequivalence studies involve mathematical analyses of

plasma level vs time curves which permits the estimations of half-life, absorption and

excretion rates, extent of absorption (area under the curve), and other constants that

are useful in describing the fate of a given drug in an organism. It should be noted,

however, that neither bioavailability nor bioequivalence data could be generated

14

without analytic methodology to accurately measure drugs in biological fluids

(Kasawar and Farooqui 2010 ; Pathare et al. 2006 ;Reza Ahmadkhaniha et al. 2014

and Yi Lau Yau et al. 1996).

For the estimation of the drugs present in the biological fluid, LC-MS/MS

method is considered to be more suitable since these are the powerful and rugged

method and also extremely specific, linear, precise, accurate, sensitive and rapid.

The present study, therefore, aims to develop and validate IVIVC of

Pramipexole and Pregabalin. An extensive literature survey carried out by the

writer revealed that there are however, no reports of IVIVC.

In detail, the aims of the study described here were as set out below:

1.7.1 Bioequivalence study design and data handling

It is proposed to conduct a randomized, two treatment, two period, two

sequence, single dose, crossover bioequivalence study for the immediate release

formulation and modified release formulation in twenty four healthy, adult, male,

human subjects under fasting conditions.

1.7.2 Development of LC-MS/MS methods for the estimation of selected drugs

in plasma samples.

The main objective of this work is to develop rapid, selective and sensitive

LC-MS/MS methods that have short and simple extraction procedures, consume

small amounts of solvent and biological fluid for extraction and a short turn-around

time.

For the present study propose to optimize the following chromatographic conditions,

Selection of Mass range

Selection of initial separation conditions

Nature of the stationary phase

Nature of the mobile phase (pH, peak modifier, solvent strength, ratio and

flow rate)

15

Sensitivity and

Selection of internal standard

The developed method is also proposed to be validated using the various

validation parameters such as,

Accuracy

Precision

Linearity and Range

Limit of detection (LOD)/Limit of Quantitation (LOQ)

Selectivity/specificity,

Robustness/ruggedness

1.7.3 Development of in-vitro dissolution studies

It is proposed to carryout in-vitro dissolution methods for selected formulations

using five different mediums with two different agitations and calculates the

cumulative percentage release of the drug in the formulations.

1.7.4 In-vitro and in-vivo data analysis

After estimating the selected drugs in biological fluids the following

pharmacokinetic parameters are proposed to be calculated;

Cmax

tmax

AUC (0-t)

AUC (0- ∞)

Maximum Plasma Concentration

Time of Maximum Plasma Concentration

Area under plasma concentrations time curve 0 to 24 hrs

Area under plasma concentrations time curve 0 to hrs

t 1/2

keli

Elimination half life

Elimination constant

The In –transformed pharmacokinetic parameters are proposed to be analysed

by an Analysis of Variance (ANOVA) and two sided ‘T’ tests for 95% confidence

intervals for the difference between treatments.

16

From the cumulative percentage release of the drug in the formulations, it is

proposed to calculate dissolution rate constants and similarity factor for selected

formulations.

1.7.5 Development of IVIVC correlations

After carrying out an in-vivo and in-vitro data analysis, it is proposed to

develop level A IVIVC for the selected drugs and validate the correlation internally

and externally.

17

CHAPTER 2

LITERATURE REVIEW

Abib et al. (2012) reported comparative bioavailability studies of two

Pramipexole formulations in healthy volunteers after a single dose administration

under fasting conditions. The study was conducted with randomized two period

crossover design and 8 days wash out period in 48 volunteers of both sexes. Plasma

samples were obtained over a 48 hour interval. Pramipexole was analyzed by LC-

MS/MS in the presence of Tansulosina as internal standard. The mean ratio of

parameters Cmax and AUC0-t and 90% confidence intervals of correspondents were

calculated to determine the bioequivalence. The means AUC0-t for test and reference

formulation were 8201.90 pg.h/ml and 7891.56 pg.h/ml, for AUC0-inf were 8574.71

pg.h/ml and 8288.01 pg.h/ml and, for Cmax were 642.09 pg/ml and 633.94 pg/ml,

respectively. Geometric mean ratio was 103.61 % for AUC0-t, 103.13% for AUC0-inf

and 100.81% for Cmax. The 90 % confidence intervals were 98.02 - 109.51%, 97.95-

108.59%, 93.06-109.21%, respectively. Since the 90 % confidence intervals for Cmax,

AUC0-t and AUC0-inf were within 80–125% interval proposed by Food and Drug

Administration, it was concluded that test formulation was bioequivalent to reference

formulation according to both the rate and extent of absorption.

Alessandro Musenga et al. (2008) reported an analysis of the anti-parkinson

drug Pramipexole in human urine by capillary electrophoresis with laser-induced

fluorescence detection. Separation was carried out in uncoated fused silica capillaries

(75 μm internal diameter, 75.0 and 60.0 cm total and effective length, respectively),

with a background electrolyte composed of borate buffer (50 mM, pH 10.3), tetra

butyl ammonium bromide (30 mM), and acetone (15%, v/v). Applying a 20 kV

voltage, the electrophoretic run is completed within 12 min. A sample pre-treatment

18

procedure based on liquid/liquid extraction with ethyl acetate, followed by

derivatisation of Pramipexole with fluoresce in iso thiocyanate at pH 9, allows the

complete removal of biological interferences, with extraction yields always higher

than 94.5%. Method validation gave good linearity (r2 = 0.9992) in the 25.0–1000

ng/ml range; limit of detection and limit of quantitation were 10.0 and 25.0 ng/ml,

respectively; precision was ≤ 6.8 R.S.D%, accuracy expressed as recovery

percentage was > 90.0. The method was applied to the analysis of urine samples

from patients undergoing therapy with Pramipexole.

Chakshu Bhatia et al. (2012) reported the formulation and evaluation of

transdermal patch of Pregabalin. Matrix type transdermal drug delivery system

(TDDS) of Pregabalin was prepared by the solvent evaporation technique. Several

batches were prepared by using combination of HPMC and PVP; PVA and PVP;

Eudragit RL-100 and Eudragit RS-100; HPMC and EC in different ratios. Propylene

glycol was used as plasticizer and DMSO was incorporated as a permeation enhancer.

Formulated transdermal patches were charachterised for their physicochemical

parameters like thickness, weight variation, flatness, tensile strength, folding

endurance, moisture content, moisture uptake and drug content uniformity. Patches

were evaluated for their in-vitro drug release profile and ex-vivo skin permeation

studies. Patches were also subjected to stability studies and skin irritation studies to

determine their compatibility with skin. Formulation P1 containing HPMC and PVP

in the ratio of 3:1 and propylene glycol, 5% w/v and DMSO, 6% w/v was found to be

the most optimum formulation. P1 was also found to exhibit maximum

in-vitro drug release of about 81.70%. Result of evaluation studies revealed that

Pregabalin can be administered as a controlled drug delivery system to reduce

frequency of drug administration. But this hypothesis requires further confirmation

via in-vivo pharmacodynamic and pharmacokinetic studies in animal and human

models.

Charles et al. (2007) reported the pharmacology and mechanism of action of

Pregabalin. Pregabalin is approved in US and Europe for adjunctive therapy of

partial seizures in adults, and also has been approved for the treatment of pain from

diabetic neuropathy or post-herpetic neuralgia in adults. Recently, it has been

approved for treatment of anxiety disorders in Europe. Pregabalin is structurally

19

related to the antiepileptic drug gabapentin and the site of action of both drugs is

similar, the alpha2–delta (α2–δ) protein, an auxiliary subunit of voltage-gated

calcium channels. Pregabalin subtly reduces the synaptic release of several

neurotransmitters, apparently by binding to α2–δ subunits, and possibly accounting

for its actions in-vivo to reduce neuronal excitability and seizures. Several studies

indicate that the pharmacology of Pregabalin requires binding to α2–δ subunits,

including structure-activity analyses of compounds binding to α2–δ subunits and

pharmacology in mice deficient in binding at the α2–δ Type 1 protein. The

preclinical findings to date are consistent with a mechanism that may entail reduction

of abnormal neuronal excitability through reduced neurotransmitter release. This

review addresses the preclinical pharmacology of Pregabalin, and also the biology of

the high affinity binding site, and presumed site of action.

Chwieduk and Curran (2010) investigated the use of once-daily Pramipexole

extended release formulation for the treatment of early and advanced idiopathic

Parkinson’s disease. Once-daily Pramipexole ER and three times-daily Pramipexole

immediate release (IR) have similar exposure over 24 hours. The ER formulation is

associated with fewer fluctuations in plasma Pramipexole concentrations over this

period. Pramipexole ER improved the symptoms of Parkinson's disease in three well

designed trials in adults with early or advanced disease, as measured by changes

from baseline in the sum of the Unified Parkinson's Disease Rating Scale (UPDRS)

parts II and III subtotal scores. In a nine week study, the majority of patients with

early Parkinson's disease who were receiving stable Pramipexole IR treatment were

successfully switched to Pramipexole ER. Relative to placebo at week 18,

Pramipexole ER 0.375-4.5 mg (of the salt) once daily significantly decreased the

sum of the UPDRS parts II and III subtotal scores from baseline in two trials in

patients with early or advanced Parkinson's disease, and also reduced the percentage

of off-time during waking hours in patients with advanced disease. The efficacy of

Pramipexole ER was maintained after 33 weeks of treatment in the trials in patients

with early or advanced Parkinson's disease. Pramipexole ER was generally well

tolerated in patients with Parkinson's disease, with the rate of adverse events being

generally similar to that with Pramipexole IR.

20

Daniel et al. (2007) investigated the pharmacology, pharmacokinetics, efficacy,

and tolerability of Pregabalin. In 4 clinical trials in a total of 1068 patients with

diabetic peripheral neuropathy, the patients receiving Pregabalin 300 to 600 mg/d

had significantly greater improvement in mean pain scores than placebo recipients (P

≤ 0.01). Patients with post herpetic neuralgia receiving Pregabalin 450 to 600 mg/d

had significantly greater improvement in relief of pain and pain-related sleep

interference than placebo recipients (P ≤ 0.002). Patients with refractory partial-onset

seizures who received Pregabalin 150 to 600 mg/d (divided into 2 or 3 doses)

concomitantly with antiepileptic drugs had significantly fewer seizures than placebo

recipients (P ≤ 0.001). In the 3 studies that evaluated the efficacy of Pregabalin in

patients with GAD or SAD, the patients receiving Pregabalin 200 to 600 mg/d

(divided into 2 or 3 daily doses) had a significantly greater reduction in mean pain

scores on the Hamilton Anxiety Scale than placebo recipients (P ≤ 0.01). Across all

the reviewed clinical trials, the most commonly reported adverse effects (AEs) were

those affecting the central nervous system, including somnolence (≤ 50%), dizziness

(≤ 49%), and headache (≤ 29%). AEs resulted in withdrawal from the study in ≤ 32%

of patients. Pregabalin appears to be an effective therapy in patients with diabetic

peripheral neuropathy, post therapeutic neuralgia, and adults with refractory partial-

onset seizures. The available data suggest that Pregabalin may be beneficial as an

adjunctive therapy in adult patients with GAD or SAD.

Dansirikul et al. (2009) reported the relative bioavailability comparing

extended release Pramipexole and immediate release Pramipexole in identical daily

doses, titration steps, and titration intervals. In a phase III study on patients with

early Parkinson’s disease, plasma concentrations were determined before taking the

morning dose, and 1, 2, and 4 hours later after a stable final dose of Pramipexole had

been established. Aided by population-centered pharmacokinetic procedures, this

enabled the simulation of mean consecutive time profiles of Pramipexole plasma

concentrations in Parkinson patients. It illustrates the desired 24 hours steady

exposure in patients after the application of the extended-release Pramipexole tablet.

Dickinson et al. (2008) have reported a Quality by Design (QbD) in

pharmaceutical product development in a regulatory context and the process of

implementing such concepts in the drug approval process. This has the potential to

21

allow for a more flexible regulatory approach based on understanding and

optimization of how design of a product and its manufacturing process may affect

product quality. Thus, adding restrictions to manufacturing beyond what can be

motivated by clinical quality brings no benefits but only additional costs. This leads

to a challenge for biopharmaceutical scientists to link clinical product performance to

critical manufacturing attributes. In vitro dissolution testing is clearly a key tool for

this purpose and the present bioequivalence guidelines and biopharmaceutical

classification system (BCS) provides a platform for regulatory applications of in-

vitro dissolution as a marker for consistency in clinical outcomes. However, the

application of these concepts might need to be further developed in the context of

QbD to take advantage of the higher level of understanding that is implied and

displayed in regulatory documentation utilizing QbD concepts. Aspects that should

be considered include identification of rate limiting steps in the absorption process

that can be linked to pharmacokinetic variables and used for prediction of

bioavailability variables, in-vivo relevance of in-vitro dissolution test conditions and

performance/interpretation of specific bioavailability studies on critical

formulation/process variables. This article will give some examples and suggestions

how clinical relevance of dissolution testing can be achieved in the context of QbD

derived from a specific case study for a BCS II compound.

Dziedzicka et al. (2001) reported the indication of Pramipexole as selective

dopamine D2 receptor agonist for the symptomatic treatment of Parkinson’s disease,

either alone (without levodopa) or in combination with levodopa, that is, during the

entire progress of disease up to the advanced stage. Pramipexole is a full non

ergoline dopamine agonist with selective affinity for dopamine receptors of the D2

subfamily. This substance shows a 7 to 10 fold higher affinity to D3 than to D2

receptors. Pramipexole acts on presynaptic as well as on postsynaptic receptors. In

intact dopaminergic systems, though, the effects of Pramipexole are primarily stirred

via presynaptic auto receptors of the D3 and D2 type, thereby reducing the synthesis

and synaptic release of dopamine. Effects on postsynaptic receptors are only

observed at higher doses, and they are marked by prolonged latency periods. With

reduced dopamine release due to loss or damage of the presynaptic termini, however,

the postsynaptic D2 and D3 receptors are additionally and immediately stimulated.

22

Elena Soto et al. (2010) reported an in-vitro and in-vivo correlation model for

Pramipexole slow-release oral formulations. The IVIVC was developed based on

data from an immediate-release (IR) and three slow-release (SR) formulations of

Pramipexole, a fourth SR formulation was used for validation purposes. In vitro

dissolution profiles were obtained from all SR formulations. Fifteen volunteers

received all Pramipexole formulations in a randomized cross-over trial. Data were

analyzed using the population modeling approach. Dissolution profiles of the SR

formulations were described by the Weibull model. The pharmacokinetics of the IR

formulation was described by a two-compartment disposition model with first-order

absorption. Difference between the in-vivo and in-vitro estimates of the release rate

constants (k(d)) from the Weibull function suggests the release process occurs faster

in-vivo. Pharmacokinetic profiles for SR formulations were described based on the

in-vitro release model with k (d) increased in 0.058/h and the population

pharmacokinetic model developed from the IR formulation. A level A IVIVC was

established and evaluated for the Pramipexole SR formulations, which can be used in

the future as a surrogate to avoid certain bioequivalence studies.

Gomez-Mantilla et al. (2014) reported a statistical comparison of dissolution

profiles to predict the bioequivalence of extended release formulations. Appropriate

setting of dissolution specification of extended release (ER) formulations should

include precise definition of a multidimensional space of complex definition and

interpretation, including limits in dissolution parameters, lag time (t-lag), variability,

and goodness of fit. This study aimed to set dissolution specifications of ER by

developing drug-specific dissolution profile comparison tests (DPC tests) that are

able to detect differences in release profiles between ER formulations that represent a

lack of bioequivalence (BE). Dissolution profiles of test formulations were simulated

using the Weibull and Hill models. Differential equations based in-vivo and in-vitro

correlation (IVIVC) models were used to simulate plasma concentrations. BE trial

simulations were employed to find the formulations likely to be declared

bioequivalent and non-bioequivalent (BE space). Customization of DPC tests was

made by adjusting the delta of a recently described tolerated difference test (TDT) or

the limits of rejection of f2. Drug ka (especially if ka is small), formulation lag time

(t-lag), the number of subjects included in the BE studies, and the number of sampled

23

time points in the DPC test were the factors that affected the most these setups of

dissolution specifications. Another recently described DPC test, permutation test

(PT), showed excellent statistical power. All the formulations declared as similar

with PT were also bioequivalent. Similar case-specific studies may support the bio-

waiving of ER drug formulations based on customized DPC tests

Gregor Bender et al. (2009) reported the population pharmacokinetic model of

the Pregabalin-sildenafil interaction in rats, application of simulation to preclinical

PK- PD study design. Preliminary evidence has suggested a synergistic interaction

between Pregabalin and sildenafil for the treatment of neuropathic pain. The focus of

this study was to determine the influence of sildenafil on the pharmacokinetics (PK)

of Pregabalin with the objective of informing the design of a quantitative

pharmacodynamic (PD) study. The pharmacokinetics were determined in rats

following 2-hr intravenous infusions of Pregabalin at doses of 4 mg/kg/hr and

10 mg/kg/hr with and without a sildenafil bolus (2.2 mg) and steady state infusion

(12 mg/kg/hr for 6 h). This PK model was utilized in a preclinical trial simulation

with the aim of selecting the optimal sampling strategy to characterize the PK-PD

profile in a future study. Eight logistically feasible PK sampling strategies were

simulated in NONMEM and examined through trial simulation techniques. A two-

compartment population PK model best described Pregabalin pharmacokinetics.

Significant model covariates included either a binary effect of sildenafil

administration (30.2% decreases in clearance) or a concentration-dependent effect

due to sildenafil’s active metabolite. Analysis of simulations indicated that three

post-PD samples had the best cost/benefit ratio by providing a significant increase in

the precision (and minor improvement in bias) of both PK and PD parameters

compared with no PK sampling.

Grosset et al. (2005) reported a simple therapeutic regimen for Parkinson’s

disease. Patients will comply much more readily to with fewer applications than to

treatments with more frequent drug administration. A prolonged-action drug permits

the steady release of the active ingredient over 24 hours preventing the active

concentration from continuously surging on and surging off as commonly

encountered with multiple applications of the substance. An unvarying, efficient

level by continuous release over 24 hours will help avoid losses during the course of

24

the day. Pramipexole, the dopamine agonist that had been a non-depot formula so far,

which patients had to take t.i.d (3x) daily, could be turned into a controlled-release

drug to be administered once daily. This paper gives an overview regarding the

development and pharmacology of the extended-release form of Pramipexole, and it

summarizes the available clinical data on depot Pramipexole in the treatment of early

and advanced Parkinson’s disease.

Hauser et al. (2009) reported the clinical study on extended-release

Pramipexole in the early stage of PD using 259 patients who had been ill for about a

year. The study was carried on for 18 weeks with an initial titration period of 7

weeks). This controlled double-blind trial (extended-release Pramipexole:

immediate-release Pramipexole: placebo in the ratio of 2 : 2 : 1) also focused on the

effect by employing UPDRS II and III plus CGI-I and PGI-I. An improvement by 7.5

points was found in the group treated with immediate-release Pramipexole: the group

taking extended-release Pramipexole scored 7.4 points and the placebo group 2.7

points. Response rates were determined by GCI-I and PGI-I and were indicative of

improvements in week 18 and 33 for extended-release Pramipexole in 37/35.6%. The

result was 48/23.8% under immediate-release Pramipexole and 18/12% under

placebo. The authors concluded that both Pramipexole formulas were safe and

superior to placebo, aside from being well tolerated. The efficacy of extended-release

Pramipexole was said to be similar to immediate-release Pramipexole with

comparable adverse effects.

Hauser et al. (2010) reported the randomized, double-blind, multicenter

evaluation of Pramipexole extended release once daily in early Parkinson's disease.

The objective of this study was to evaluate the efficacy and safety of Pramipexole

extended release (ER) administered once daily in early Parkinson's disease (PD).

Pramipexole immediate release (IR) administered three times daily (t.i.d) is an

efficacious and generally well-tolerated treatment for PD. A Pramipexole ER

formulation is now available. We performed a randomized, double-blind, placebo

and active comparator-controlled trial in subjects with early PD. The primary

efficacy and safety evaluation of Pramipexole ER compared with placebo took place

at week 18. Two hundred fifty-nine subjects were randomized 2:2:1 to treatment with

Pramipexole ER once daily, Pramipexole IR t.i.d, or placebo. Levodopa rescue was

25

required by 7 subjects in the placebo group (14%), 3 subjects in the Pramipexole ER

group (2.9%, P = 0.0160), and 1 subject in the Pramipexole IR group (1.0%,

P = 0.0017). Adjusted mean [standard error (SE)] change in Unified Parkinson

Disease Rating Scale (UPDRS) II [activities of daily living (ADL)] + III (motor)

scores from baseline to week 18, including post-levodopa rescue evaluations, was -

5.1 (1.3) in the placebo group, -8.1 (1.1) in the Pramipexole ER group (P = 0.0282),

and -8.4 (1.1) in the Pramipexole IR group (P = 0.0153). Adjusted mean (SE) change

in UPDRS ADL + motor scores, censoring post-levodopa rescue data, was -2.7 (1.3)

in the placebo group, -7.4 (1.1) in the Pramipexole ER group (P = 0.0010), and -7.5

(1.1) in the Pramipexole IR group (P = 0.0006). Adverse events more common with

Pramipexole ER than placebo included somnolence, nausea, constipation, and fatigue.

Pramipexole ER administered once daily was demonstrated to be efficacious

compared with placebo and provided similar efficacy and tolerability as Pramipexole

IR administered t.i.d.

Jantratid et al. (2009) reported an application of bio-relevant dissolution tests

to the prediction of in-vivo performance of an oral modified-release (MR) dosage

form. In vitro dissolution of MR diclofenac sodium pellets containing 100 mg active

ingredient was evaluated under simulated pre- and postprandial conditions using

USP Apparatus 3 (reciprocating cylinder, Bio-Dis) and 4 (flow-through cell) and

results compared with compendial methods using USP Apparatus 1 (basket) and 2

(paddle). In-vivo, the effects of food on the absorption of diclofenac sodium from the

pellet dosage form was investigated by administering the product to 16 healthy

volunteers pre- and postprandial in a crossover-design study. The in-vitro results

were compared with the in-vivo data by means of Level A in-vitro and in-vivo

correlation (IVIVC) and Weibull distribution analysis. The compendial dissolution

tests were not able to predict food effects. The bio relevant dissolution tests predicted

correctly that the release (and hence absorption) of diclofenac sodium would be

slower in the fed state than in the fasted state. No significant differences in extent of

absorption due to changes in extent of release were predicted or observed. The

results demonstrate good correlations between in-vitro drug release and in-vivo drug

absorption in both pre and post-prandial states using the bio relevant dissolution test

methods.

26

Jenner et al. (2009) reported a clinical phase I study for Pramipexole matrix

tablets. In a crossover study with in healthy male subjects, the pharmacokinetic

properties were investigated in the steady state. An optimal formula for further

clinical development was supposed to be identified based on the a maximum plasma

concentration, in the steady state (day 4 of each extended-release Pramipexole

therapy), that does not exceed the one obtained after immediate-release Pramipexole

t.i.d., and a minimum plasma concentration not less than the one observed after the

immediate-release formula applied t.i.d., a peak/trough fluctuation (PTF) over

24 hours that is smaller than or comparable to the one following immediate-release

Pramipexole,a bioavailability not less than ≥75% in the steady state that compares

with the immediate-release formula, no incidence of irregular release (“dose-

dumping” defined as a not more than 80% dose absorption within 4 hours after

application). One matrix tablet met all of the above criteria and was chosen for

further clinical development. It consists of an innovative hydrogel formula. With this

kind of tablet, the drug substance is homogeneously embedded in a polymeric matrix.

The slow down (= extended release) of the agent is accomplished by combining three

polymers hypromellose, corn starch, and carbomer. The interaction of these three

polymers warrants the uniform and long-lasting release of the agent over 24 hours.

Upon contact with digestive juices, the drug substance is first dissolved at the surface.

The matrix then starts swelling, forming a viscous jelly that releases Pramipexole

consistently over 24 hours. Because of Pramipexole’s good solubility independent

from pH-value, the drug substance is dissolved from the matrix also in deeper

intestinal segments and is ready for absorption. In patients with Parkinson's disease,

once-daily use of an ER formulation may improve the convenience of treatment

relative to the IR formulation taken 3 times daily and thus increase compliance.

Jose david et al. (2013) reported the permutation test (PT) and tolerated

difference test (TDT for statistical comparison of dissolution profiles. The most

popular way of comparing oral solid forms of drug formulations from different

batches or manufacturers is through dissolution profile comparison. Usually, a

similarity factor known as (f2) is employed; however, the level of confidence

associated with this method is uncertain and its statistical power is low. In addition,

f2 lacks the flexibility needed to perform in special scenarios. In this study two new

27

statistical tests based on non-parametrical Permutation Test theory are described, the

Permutation Test (PT), which is very restrictive to confer similarity, and the

Tolerated Difference Test (TDT), which has flexible restrictedness to confer

similarity, are described and compared to f2. The statistical power and robustness of

the tests were analyzed by simulation using the Higuchi, Korsmayer, Peppas and

Weibull dissolution models. Several batches of oral solid forms were simulated while

varying the velocity of dissolution (from 30 min to 300 min to dissolve 85% of the

total content) and the variability within each batch (CV 2–30%). For levels of

variability below 10% the new tests exhibited better statistical power than f2 and

equal or better robustness than f2. TDT can also be modified to distinguish different

levels of similarity and can be employed to obtain customized comparisons for

specific drugs. In conclusion, two new methods, more versatile and with a stronger

statistical basis than f2, are described and proposed as viable alternatives to that

method. Additionally, an optimized time sampling strategy and an experimental

design-driven strategy for performing dissolution profile comparisons are described.

Jost (2010) reported the clinical studies of Pramipexole Immediate-release and

extended-release tablets. The substance itself is unchanged, meaning there is an

identical receptor profile, identical efficacy, and identical receptor binding. The half-

life of the agent is also the same, but the continuous release from the depot tablet

results in an overall prolonged plasma half-life. Any of the accepted statements

linked to immediate-release Pramipexole also apply to extended-release

Pramipexole-except for the daily doses required. Extended-release Pramipexole can

be used in both early and late Parkinson’s disease. A switch can take place overnight,

the ratio being 1:1, for example, immediate-release Pramipexole mg (base) are

consistent with 2.1 mg extended-release Pramipexole. In most cases, the patient is

not going to be affected by this switch. More efficaciousness, increased dyskinesias

or undesired effects are not to be expected. In a few cases, the effect may be less,

which would require a dose adjustment. Some patients appreciate the stimulating

effect of immediate-release Pramipexole with a rapid afflux and higher peak and for

this reason, they prefer fast-release Pramipexole. So far, there have been no insights

regarding any increased individual side effect owing to the use of extended-release

Pramipexole. Reduction of plasma peaks might even result in decreased side effects.

28

Since the introduction of extended-release Pramipexole, and in consideration of

pharmacologic and clinical aspects, it has been recommended putting the patient on

extended-release Pramipexole in a new approach. All patients who have been under

immediate-release Pramipexole may furthermore be switched to extended-release

Pramipexole overnight. The inauguration of extended release Pramipexole is to be

regarded as another important option in the drug treatment of Parkinson’s disease.

Kasawar and Farooqui (2010) reported a simple, precise, specific, and accurate

reverse phase HPLC method for the determination of Pregabalin in capsule dosage

form. The chromatography was set on Hypersil BDS, C8, 150 × 4.6 mm, 5 μm

column using photodiode array detector. The mobile phase consisting of phosphate

buffer pH 6.9 and acetonitrile in the ratio of 95:05 with flow rate of1 ml/min. The

method was validated according to ICH guidelines with respect to specificity,

linearity, accuracy, precision and robustness. Lower limit of quantification is 0.6

mg/l. The Pregabalin sample solution was found to be stable at room temperature for

about 26 hour. The influence of fluctuating temperature and humidity conditions that

might occur during transportation of drug products can be estimated using stability

analysis of a drug. The assay is calibrated over the range of 500 μg/ml to 1500 μg/ml

and without derivatisation of analyte also the proposed method can quantify (LOQ)

at least0.61 μg/ml and can detect (LOD) at least 0.23 μg/ml. The developed method

has been validated showing the method accuracy, linearity and reproducibility.

Validation procedure was mainly based on the ICH guideline.

Koenen-Bergmann et al. (2008) reported a level A in-vitro and in-vivo

correlation (IVIVC) with the chosen formula was established in the course that was

able to predict a complete plasma concentration profile in humans by in-vitro

solubility charts with adequate precision. This IVIVC also showed that Pramipexole

of the extended-release formula was steadily absorbed all through the entire intestine

including the colon. The variability among other individuals in this process was

rather low and not influenced by other factors food for instance.

Kortejarvi et al. (2002) reported the different levels of correlation between in-

vitro release and in-vivo absorption rate for four modified-release levosimendan

capsule formulations. Differences and similarities in the in-vitro dissolution curves

29

were compared with pharmacokinetic parameters describing absorption rate.

Formulations F, G, H and I differed in the amounts of the delaying excipients alginic

acid and HPMC. In vitro release rate was studied by the USP basket method using

the following conditions: pH 5.8 or 7.4 and a rotation speed of 50 or 100 rpm. In-vivo

bioavailability was tested in nine healthy male volunteers and the fractions absorbed

were calculated by the Wagner–Nelson method. Dissolution conditions pH 5.8 and a

rotation speed of 100 rpm predicted best the similarities and differences in absorption

rates among different formulations, and levels C and B correlation coefficients were

0.85 and 0.97, respectively. For formulation Hlevel A correlation (r=0.997) was

found when in-vitro lag time was 0.2 h and time scale factor 1.9. This study indicated

that dissolution tests developed can be used as a surrogate for human bioequivalence

studies, for development processes of final commercial products, to ensure batch to

batch bioequivalence and in the future possible scale-up and post approval change

cases for modified release levosimendan formulation H.

Lake et al. (1999) have reported a dissolution test method for carbamazepine

immediate release tablets, giving the best in-vitro-in-vivo correlations and to

determine the potential of this method as an estimate for bioequivalence testing. Four

200 mg carbamazepine products which are sold on the Dutch market, covering the

innovator and three generic products were selected. They had been tested in a

randomised, four way cross-over bioavailability study in healthy volunteers. Their

dissolution rate behavior in-vitro was investigated using 1% sodium lauryl sulphate

in water and 0.1 M/l Hydrochloric acid in water. In the bioavailability study these

products had shown no large differences in the extent of absorption but large

differences in absorption rate. The products now also showed large differences in

dissolution rate in-vitro in both dissolution media, the rank order being the same as

for the absorption rate. It was concluded that the absorption rate in-vivo depends on

the dissolution rate in-vivo. Level C' IVIVC according to the USP were optimized by

plotting percentages dissolved on selected time points (D values) or their reciprocals

(1/D values), against several pharmacokinetic parameters primarily related to the

absorption phase and against AUC. In this way for each IVIVC the optimum D or

1/D value, was calculated. For both media no meaningful IVIVC were obtained with

AUC, but favorable IVIVC were obtained with the parameters primarily related to

30

the absorption phase. In the bioavailability study, among the pharmacokinetic

characteristics primarily related to the absorption phase, Cmax was the most promising

in expressing rate of absorption in bioequivalence testing in single dose studies with

carbamazepine immediate release tablets.

Malte Selch Larsen et al. (2015) reported an in-vivo and in-vitro Evaluations of

Intestinal Gabapentin. Gabapentin exhibits saturable absorption kinetics, however, it

remains unclear which transporters that are involved in the intestinal transport of

gabapentin. Thus, the aim of the current study was to explore the mechanistic

influence of transporters on the intestinal absorption of Gabapentin by both in-vivo

and in-vitro investigations. Gabapentin showed dose-dependent oral absorption

kinetics and dose-independent disposition kinetics. Co-application of BCH inhibited

intestinal absorption in-vivo and apical uptake in-vitro, whereas no effect was

observed following co-application of L-lysine. The present study shows for the first

time that BCH was capable of inhibiting intestinal absorption of gabapentin in-vivo.

Furthermore, in Caco-2 cell experiments BCH inhibited apical uptake of gabapentin.

These findings may imply that a BCH-sensitive transport-system was involved in the

apical and possibly the basolateral transport of gabapentin across the intestinal wall.

Meihua Rose Feng et al. (2001) reported a brain microdialysis and PK/PD

correlation of Pregabalin in rats. In this report, blood-brain barrier (BBB) influx and

efflux of PGB were investigated with microdialysis at efficacious doses in rats. BBB

influx (CLin) and efflux (CLout) permeability for Pregabalin were 4.8 and

37.2 μL/min/g brain, respectively, following an intravenous infusion to rats. The

results indicate that PGB is brain pentrable, supporting its anti-epilepsy and other

CNS pharmacology. Significant anticonvulsant action of PGB was detected between

2 and 8 hr post oral dose, which is lag behind ECF drug concentrations lees.

A PK/PD link model was used to describe the counter-clockwise hysteresis

relationship between Pregabalin brain ECF concentration and the anticonvulsant

effect in rats. The resulting Ce (concentration in effect compartment) versus effect

profile exhibits a sigmoidal curve and the calculated ECe50 and Keo values were

95.3 ng/mL and 0.0092/min, respectively. The small Keo value suggests that the

effect is not directly proportional to the amount of Pregabalin in the ECF

compartment possibly due to inherent delay.

31

Pathare et al. (2006) reported a validated chiral liquid chromatographic method

for the enantiomeric separation of Pramipexole dihydrochloride monohydrate. A

chiral liquid chromatographic method was developed for the enantiomeric resolution

of Pramipexole dihydrochloride monohydrate. The enantiomers of Pramipexole

dihydrochloride monohydrate were resolved on a Chiralpak AD (250 mm × 4.6 mm,

10 μm) column using a mobile phase system containing

n-hexane:ethanol:diethylamine (70:30:0.1, v/v/v). The resolution between the

enantiomers was found not less than eight. The presence of diethylamine in the

mobile phase has played an important role in enhancing chromatographic efficiency

and resolution between the enantiomers. The developed method was extensively

validated and proved to be robust. The limit of detection and limit of quantification

of (R)-enantiomer were found to be 300 and 900 ng/ml, respectively for 20 μl

injection volume. The percentage recovery of (R)-enantiomer was ranged from 97.3

to 102.0 in bulk drug samples of Pramipexole dihydrochloride monohydrate.

Pramipexole dihydrochloride monohydrate sample solution and mobile phase were

found to be stable for at least 48 h. The proposed method was found to be suitable

and accurate for the quantitative determination of (R)-enantiomer in bulk drugs.

Peter Jenner et al. (2009) investigated the pharmacokinetic properties of a

variety of prototypes for a once daily extended release (ER) formulation of

Pramipexole and to further characterize the prototype whose pharmacokinetics best

matched those of the IR formulation. Three Phase I studies were conducted, all in

healthy adult men aged ≤ 50 years with a body mass index of 18.5 to 29.9 kg/m2. In

the first study, 7 prototypes of a once-daily ER formulation with various release

properties, including rate and pH dependence, were compared with the IR

formulation taken 3 times daily to identify the optimal pharmacokinetic resemblance

based on predefined criteria derived from plasma AUC0−24h, Cmax, and Cmin. In the

second study, a level A in-vitro/in-vivo correlation (IVIVC) suitable for predicting an

entire in-vivo bioavailability time course based on in-vitro dissolution was

established and validated, and the single-dose pharmacokinetics of the optimal ER

formulation identified in the first study were analyzed for food effect. In the third

study, steady-state pharmacokinetics of the optimal ER formulation were assessed

across a range of Pramipexole doses (0.375–4.5 mg/d), including investigation of the

32

food effect at steady state for the highest dose. Tolerability was assessed throughout

all studies based on physical examinations, laboratory measurements, and adverse

events (AEs). In these studies in healthy male volunteers, an ER Pramipexole

formulation was identified that resembled the IR formulation in terms of both

pharmacokinetics and tolerability. In patients with Parkinson's disease, once-daily

use of an ER formulation may improve the convenience of treatment relative to the

IR formulation taken 3 times daily and thus increase compliance.

Poewe et al. (2009) reported the effectiveness of extended-release Pramipexole

in the early stage of disease. this work group scrutinized 539 patients who had had

symptoms for averagely 12 months and treated them with immediate-release

Pramipexole by 3-arm design: depot Pramipexole: placebo in a ratio of 2 : 2 : 1 for 26

weeks. The effectiveness was checked upon after 18 weeks, the (non-inferiority)

after 33 weeks. UPDRS II and III besides CGI-I (Clinical Global Impression

Improvement) and PGI-I (Patient Global Impression Improvement) served as

parameters. The two goals of the study were attained, that is, proof of the superiority

versus placebo in week 18 and proof of the non-inferiority of extended-release

Pramipexole in week 33 (−8.6 versus −8.8 scores). Relevant differences in respect of

CGI-I and PGI-I were not seen (46.1/33.3 versus 43.3/34.4%), the incidence and

severity of side effects did not differ either.

Pui Shan Chana et al. (2014) reported an in-vitro transport assay of rufinamide,

Pregabalin, and zonisamide by human P-glycoprotein. P-glycoprotein (Pgp) export

may contribute to antiepileptic drug (AED) resistance. Concentration equilibrium

transport assays (CETA) measure permeable-drug transport. Zonisamide, Pregabalin,

and rufinamide are not Pgp substrates in CETA. Epilepsy is resistant to treatment

with antiepileptic drugs (AEDs) in about one third of epilepsy patients. AED export

by P-glycoprotein (Pgp) overexpressed in the blood–brain barrier may contribute to

AED resistance. The Pgp transport status of many of the recently approved AEDs

remains unknown. We investigated whether several new AEDs - zonisamide (ZNS),

Pregabalin (PGB), and rufinamide (RFM) - are human Pgp substrates. MDCKII and

LLC-PK1 cells transfected with the human MDR1 gene, which encodes the Pgp

protein, were used in concentration equilibrium transport assays (CETA) to

determine the substrate status of ZNS, PGB, and RFM. For each drug, an equal

33

concentration was added to apical and basal chambers, and the concentration in both

chambers was measured up to 4 hours. RFM, ZNS, and PGB were not transported by

MDR1-transfected cells from basolateral to apical sides in CETA. ZNS, RFM, and

PGB are not substrates of human Pgp. These data suggest that resistance to these

drugs may not be attributed to increased Pgp activity in resistant patients.

Quinones et al. (2010) reported a comparative bioavailability study of two

formulations of Pregabalin in healthy Chilean volunteers. The aim of this study was

to compare the pharmacokinetic parameters between two brands of Pregabalin in

healthy Chilean volunteers. A randomized, single-dose, two-period, two-sequence,

crossover study design with a 2-week washout period was conducted in healthy

Chilean males. Plasma samples were collected over a 12-hour period after

administration of 150 mg Pregabalin in each period. A validated ultra-performance

liquid chromatography with positive ionization mass spectrometric detection method

was used to analyze Pregabalin concentration in plasma. Pharmacokinetic parameters

were determined using a non-compartmental method. Bioequivalence between the

test and reference products was determined when the ratio for the 90% confidence

intervals (CIs) of the difference in the means of the log-transformed area under the

curve (AUC0-t, AUC0-∞, and maximum concentration Cmax) of the two products were

within 0.80 and 1.25. These results suggest that both products are bioequivalent and

can be used as interchangeable options in the clinical setting.

Rascol et al. (2009) investigated the extent of switching a patient from

immediate-release Pramipexole to extended-release Pramipexole. This was a

double-blind study,156 patients were switched who had received invariably more

than 1.05 mg (b ase) Pramipexole for at least 4 weeks (on the average 1.9 mg (base)

immediate-release Pramipexole). Changes up to 15% in the UPDRS (Unified

Parkinson Disease Rating Scale) II and III were rated noninferior. 84.5% were

successfully changed overnight (87 out of 103 patients). The proof on noninferiority

failed although extended-release Pramipexole turned out even better per UPDRS and

CGI-I (Clinical Global Impression Improvement), responder rate (87. 4 versus

78.8%). There was no difference in side effects.

34

Rascol et al. (2010) reported the efficacy, safety, and tolerability of overnight

switching from immediate to once daily extended release Pramipexole in early

Parkinson's disease. Non-fluctuating patients on Pramipexole IR three times daily,

alone or with levodopa, for early PD were randomly switched overnight to double

blind IR three times daily (N = 52) or ER once-daily (N = 104) at initially unchanged

daily dosage. Successful switching (defined as no worsening >15% of baseline

UPDRS II+III score and no drug-related adverse event withdrawal) was assessed at 9

weeks, after optional dosage adjustments (primary endpoint), and at 4 weeks, before

adjustment. Other secondary endpoints included adjusted mean changes from

baseline in UPDRS scores and proportion of responders based on Clinical or Patient

Global Impression (CGI/PGI). Absolute difference between percentage of successful

switch to ER versus IR was tested for ER noninferiority, defined as a 95%

confidence-interval lower bound not exceeding -15%. At 9 weeks, 84.5% of the ER

group had been successfully switched, versus 94.2% for IR. Noninferiority was not

demonstrated, with a difference of -9.76% (95% CI: [-18.81%, +1.66%]). At 4 weeks,

81.6 % of the ER group had been successfully switched, versus 92.3% for IR, a

difference of -10.75 % (95% CI: [-20.51%, +1.48%]). UPDRS changes and CGI/PGI

analyses showed no differences between the groups. Both formulations were safe and

well tolerated. Pramipexole ER was not equivalent to IR, but the difference was

marginal. The fact that >80% of the patients successfully switched overnight at

unchanged dosage shows that this practice was feasible in most patients.

Reza Ahmadkhaniha et al. (2014) reported a validated HPLC method for

quantification of Pregabalin in human plasma using 1-fluoro-2,4-dinitrobenzene as

derivatization agent. In this study, a sensitive, simple, and reliable HPLC method for

quantification of Pregabalin in human plasma was developed and validated. 1-

Fluoro-2,4-dinitrobenzene was used as pre-column derivatization agent. For

chromatography, an analytical reversed phase (C18) column and a mixture of

Na2HPO4 10 mM (pH 8.0)—methanol (35 : 65 v/v) were used as stationary and

mobile phase, respectively. Detection was performed using a UV detector tuned at

360 nm. The linearity of the method was tested over the concentration range

1–4500 n g/mL in 500 μL of human plasma and satisfactory results were obtained

(r2 >0.999). The method showed good precision and accuracy in terms of within

35

between days relative standard deviations and percent deviation from nominated

values (in the range of 4.3–12.7% and 2.6–8.0%, resp.). The limit of quantification of

the method was found to be 1 ng/mL which is better than previously reported method

and indicates its potential application for sensitive bio-analysis.

Robert Lee et al. (2008) reported the possible heart failure exacerbation

associated with Pregabalin. Regabalin is an analog of the neurotransmitter γ-

aminobutyric acid that exhibits analgesic, anticonvulsant, and anxiolytic properties.

Owing to its pharmacologic properties, the drug has been used worldwide in the

management of diabetic peripheral neuropathy, post therapeutic neuralgia,

generalized anxiety disorder, and social anxiety disorder. Although central nervous

system disturbances account for the majority of Pregabalin's side effects, dose-

dependent peripheral edema and weight gain have also been reported. Recently, three

case reports have been published documenting a possible association between

Pregabalin administration and chronic heart failure decompensation. They presented

three additional cases of possible heart failure exacerbation in patients with clinically

stable heart failure who received Pregabalin for neuropathic pain. Additionally,

literature was reviewed addressing the nature and possible etiology for this adverse

effect.

Rossi et al. (2007) have reported a dissolution procedure for Ritonavir soft

gelatin capsules (Norvir) based on in-vivo data. Several conditions such as medium

composition, pH, surfactant concentration and rotation speed were evaluated. The

method was carried out using the same batch of Norvir used in a bioequivalence

study and the in-vivo data were used to select the best dissolution test conditions

based on in-vitro-in-vivo correlation (IVIVC). The dissolution test was validated

using a high-performance liquid chromatographic method (HPLC). For this

formulation, the best dissolution conditions were achieved using paddle, 900 ml of

medium containing water with 0.7% (w/v) of sodium lauryl sulfate at a rotation

speed of 25 rpm. Under these conditions a significant linear relationship between

fraction of ritonavir absorbed and dissolved was obtained (R(2)=0.993) and a level A

IVIVC was established. In the HPLC method a relative standard deviation for intra-

day precision was <1.6% and for inter-day precision was <1.4%. Accuracy was from

98.5% to 101.6% over the concentration range required for the dissolution test

36

(4.0-124.0 μg/ml). Both the HPLC method and the dissolution test are validated and

could be used to evaluate the dissolution profile of ritonavir soft gelatin capsules.

Salin et al. (2009) reported the 3 arm study using 101 patients for 33 weeks.

84 patients were evaluated at the end of the study, 35 of them being on extended-

release Pramipexole, 31 under immediate-release Pramipexole and 18 under placebo.

Changes of UPDRS II and III were compared with week 18 to 33. The group taking

extended-release Pramipexole scored higher by a change of 0.3 (−11.8 versus −11.5

points). The group treated with immediate-release Pramipexole presented with a

change of −11.9 points. The change in the placebo group amounted to −4.2 points up

to week 18 and −2.7 points to week 33. This means that in both drug groups the

effect was maintained between week 18 and 33 whereas a decline of 1.5 points in

was recorded in the placebo group. Parallel data on response were also collected.

PGI interestingly enough revealed a slight superiority of the extended-release

formula compared to immediate-release Pramipexole in week 18 and 33 (45.7/42.9

versus 35.5/41.9%), evaluation of CGI disclosed a superiority of the immediate-

release formula in week 18 and 33 (64.5/51.6 versus 46.9/40.6%).

Schapira et al. (2009) reported the Effectiveness of Extended-Release

Pramipexole in Advanced Parkinson’s Disease. This examination included 517

patients, who had been diseased for about 6 years, treated already by approximately

600 mg levodopa. Used in a 3-arm design were immediate-release Pramipexole:

extended-release pramipexol: placebo in a ratio of 1 : 1 : 1. The superiority of

Pramipexole was studied after 18 weeks by UPDRS part II and III (Figure 6) and by

off periods. The effectiveness was rechecked then 33 weeks later. Extended-release

Pramipexole proved superior after 18 weeks, reflected by 4.9 points (−11.0 versus

6.1) in UPDRS and 0.7 (−2.1 versus 1.4) hours off time as opposed to placebo. There

were no relevant differences between immediate-release Pramipexole and extended-

release Pramipexole. The great effect of placebo was astonishing. Giddiness and

vomiting occurred less under extended-relapse Pramipexole than under immediate-

release Pramipexole.

Soto et al. (2010) reported the population in-vitro and in-vivo correlation model

for Pramipexole slow-release oral formulations. The IVIVC was developed based on

37

data from an immediate-release (IR) and three slow-release (SR) formulations of

Pramipexole; a fourth SR formulation was used for validation purposes. In vitro

dissolution profiles were obtained from all SR formulations. Fifteen volunteers

received all Pramipexole formulations in a randomized cross-over trial. Data were

analyzed using the population modelling approach as implemented in NONMEM VI.

Dissolution profiles of the SR formulations were described by the Weibull model.

The pharmacokinetics of the IR formulation were described by a two-compartment

disposition model with first-order absorption. Difference between the in-vivo and in-

vitro estimates of the release rate constants (k(d)) from the Weibull function suggests

the release process occurs faster in-vivo. Pharmacokinetic profiles for SR

formulations were described based on the in-vitro release model with k(d) increased

in0.058/h and the population pharmacokinetic model developed from the IR

formulation. A level A IVIVC was established and evaluated for the Pramipexole SR

formulations, which can be used in the future as a surrogate to avoid certain

bioequivalence studies.

Thrasivoulos et al. (2008) reported the efficacy of Pregabalin and gabapentin

for neuropathic pain in spinal-cord injury. Spinal-cord injury (SCI) is a leading cause

of neuropathic pain (NP). Current pharmaceutical treatments for NP in SCI patients

are not effective. Two promising options are gabapentin (GP) and Pregabalin (PB).

Their predominant mechanism of action is believed to be the inhibition of calcium

currents, leading in turn to reduced neurotransmitter release and attenuation of

postsynaptic excitability. This could explain much of their efficacy in the treatment

of both seizure disorders and pain syndromes. However, evidence for their efficacy

in attenuating NP of SCI is still controversial. There is a lack of studies comparing

GP and PB in treating NP in SCI. This systematic review indicates the possible

efficacy of PB and GP in NP of SCI. Recommendations for future research to inform

clinical practice should include cost-effectiveness studies and dose-response analysis

in order to determine the schema employed and the duration of treatment.

Trond Kvernmo et al. (2006) reported a dopamine agonists (DAs), which can

be categorized as ergot derived and non-ergot derived, are used in the treatment of

Parkinson's disease. Relevant articles were identified through a search of MEDLINE

using the terms dopamine agonists (or each individual drug name) and

38

pharmacokinetics, metabolism, drug-drug interaction, interactions, CYP450, fibrosis,

valvular heart disease, tremor, clinical trials, reviews, and meta-analyses. Abstracts

from recent sessions of the International Congress of Parkinson's Disease and

Movement Disorders were also examined. Clinical studies with <20 patients overall

or <10 patients per treatment group in the final analysis were excluded. All DAs that

were graded at least possibly useful with respect to at least 3 of 4 items connected to

the treatment/prevention of motor symptoms/complications in the most recent

evidence-based medical review update were included. This resulted in a focus on the

ergot-derived DAs Bromocriptine, Cabergoline, and Pergolide, and the non-ergot-

derived DAs Pramipexole and Ropinirole. As reflected in the results of the clinical

trials included in this review, dyskinesia associated with DA therapy may be linked

to stimulation of the D1 receptor. Fibrosis (including VHD) seemed to be a class

effect of the ergot-derived DAs. Each of the DAs except Pramipexole has the

potential to interact with other drugs via the CYP enzyme system.

Wolfram Eisenreich et al. (2010) reported a novel treatment option in

Parkinson's disease using Pramipexole extended release formulations. Based on

numerous clinical data and vast experiences, efficacy and safety profiles of this non-

ergoline dopamine agonist are well characterized. Since October 2009, an extended-

release formulation of Pramipexole has been available for symptomatic treatment of

Parkinson's disease. Pramipexole administration can be cut down from three times to

once a day due to the newly developed extended-release formulation. This is

considerable progress in regard to minimizing pill burden and enhancing compliance.

Moreover, the 24 h continuous drug release of the once-daily extended-release

formulation results in fewer fluctuations in plasma concentrations over time

compared to immediate-release Pramipexole, given three times daily. The present

study summarizes pharmacokinetics and all essential pharmacological and clinical

characteristics of the extended-release formulation. In addition, it provides all study

data, available so far, with regard to transition and de-novo administration of

extended-release formulation for patients with Parkinson's disease. It further

compares efficacy and safety data of immediate-release Pramipexole with the

extended-release formulation of Pramipexole.

39

Yi Lau Yau et al. (1996) reported a sensitive and selective high-performance

liquid chromatographic (HPLC) method was developed for the determination of

Pramipexole in human plasma and urine. Plasma/urine is made alkaline before

Pramipexole and BHT-920 (internal standard) are extracted by ethyl ether and back-

extracted with a solution that contains heptanes sulfonic acid. Separation is achieved

by ion-pair chromatography on a Zorbax Rx C8 column with electrochemical

detection at 0.6 V for plasma and ultraviolet detection at 286 nm for urine. The

retention times of Pramipexole and internal standard are approximately 14.4 and 10.7

min, respectively. The assay is linear in concentration ranges of 50 to 15 000 pg/ml

(plasma) and 10 to 10 000 ng/ml (urine). The correlation coefficients are greater than

0.9992 for all curves. For the plasma method, the analysis of pooled quality controls

(300, 3000, and 10 000 pg/ml) demonstrates excellent precision with relative

standard deviations (R.S.D.) (n=18) of 1.1%, 2.3%, and 6.8%, respectively. For the

urine method, quality control pools prepared at 30, 300, and 3000 ng/ml had R.S.D.

values (n=18) of 2.9%, 1.7%, and 3.0%, respectively. The plasma and urine controls

were stable for more than nine and three months, respectively. The mean recoveries

for Pramipexole and internal standard from plasma were 97.7% and 98.2%,

respectively. The mean recoveries for Pramipexole and internal standard from urine

were 89.8% and 95.1%, respectively. The method is accurate with all intra-day (n=6)

and overall (n=18) mean values for the quality control samples being less than 6.4

and 5.8% from theoretical for plasma and urine, respectively.

40

CHAPTER 3

MATERIALS AND METHODS

3.1 Reagents, Chemicals and Instruments

3.1.1 Reagents and Chemicals used

Methanol, Acetonitrile and Water of HPLC grade from Merck, Ammonium

Formate, Trichloro acetic acid, Dichloromethane, n-Hexane, Diethyl ether and

Formic Acid were AR Grade, Pregabalin, and Tramadol obtained from Aarti Drugs

Limited, Pramipexole dihydrochloride monohydrate from Orchid Chemicals and

Pharmaceuticals Ltd, India. Quetiapine Fumarate obtained from Lupin Laboratories

Limited, Maharashtra, India.

3.1.2 Instruments used

i.

ii.

Agilent 6460 Triple Quad LC-MS/MS

AB Sciex API 5500 Triple Quad LC-MS/MS

iii. Sartorius single pan digital balance (R200D & 1702)

iv. Systronics pH meter, pH system 361.

v. Shimadzu LC 2010A HT HPLC system with

configurations;

following

vi.

vii.

Electrolab USP Type I and II dissolution testing apparatus

Shimadzu 160A UV-VIS spectrophotometer

viii.

ix.

Perkin-Elmer FT IR 1600 series

Ultra Sonicator

x. Solid phase Extractor

41

3.2 Bioequivalence study

This section describes the study design, products of evaluation, subject

selection, inclusion and exclusion criteria, safely and ethics review procedure, drugs

administration, meals and food restrictions, blood collection and extraction,

evaluation of pharmacokinetic parameters and statistical analysis involved in the

bioequivalence studies.

3.2.1 Study Design

A single dose, randomized, two treatment, two period, two sequence, single dose,

crossover bioequivalence study for the immediate release formulation and modified

release formulation in twenty four healthy, adult, male, human subjects under fasting

conditions.

3.2.2 Product for Evaluation

In each dosing session, volunteers received either immediate release

formulation or modified release formulation. A wash out period of seven days was

allowed between dose administrations.

3.2.3 Subjects

The subjects for the bioavailability study were selected from the panel of

volunteers enrolled with the Centre of Bioequivalence, Roxaane Research Private

Limited, Chennai. Seven days prior to the commencement of the study, volunteers

were screened for the following for inclusion in the study;

Healthy males, 20 - 35 years of age

Not more than ±15% from ideal weight for subjects height and elbow

breadth

General good health as determined by medical history and physical

examination within 30 days prior to the start of the study (without a history

of clinically significant organ system disorders, or ongoing infectious

diseases, history of benign prostatic hypertrophy, prostate infections, or

urinary retention, history of asthma and drug allergy history of peripheral

42

neuropathy, history of alcohol abuse or drug addiction requiring treatment

within the last 12 months)

No prescription drugs within 14 days, or OTC preparations, herbal remedies,

or nutritional supplements (excluding vitamins) within 7 days prior to drug

administration and

Subjects with systolic blood pressure 90-140 mmHg, diastolic pressure

50-90 mmHg and pulse rate within 50- 100 bpm

On the basis of this preliminary screening, 24 volunteers were selected and

their liver and renal functions and hematological parameters such as hemoglobin

content, RBC and WBC counts, blood sugar, cholesterol, bilirubin and ECG were

examined by standard clinical and biochemical investigations. No grapefruit juice

or grapefruit containing products for at least 72 h and caffeine or xanthine

consumption for at least 12 h prior to drug administration was allowed in each

period. No concomitant medication (other than the study drug) was allowed during

the study phase. Volunteers were also instructed to refrain from consuming alcohol,

smoking or other stimulant drinks during this period.

3.2.4 Ethics Review Procedure

The protocol of the study was then submitted to the Institutional Human

Ethical Committee and the approval for conducting the same was obtained. Prior to

the commencement of the study, each subject was provided with an information

sheet giving details of the investigational drugs, procedure and potential risk

involved and a written consent was obtained. They were instructed that they are free

to withdraw their consent and to discontinue their participation in the study at any

time without prejudice.

3.2.5 Drug Administration

All the volunteers were made to assemble in the Bioequivalence Centre, 12

hours prior to the initiation of the study. After overnight fasting, the volunteers were

given code numbers and allocated to the treatment in accordance with the

randomized code. Their pulse rates and blood pressures were recorded and a sterile

intravenous cannula introduced with strict aseptic precautions for blood collection.

43

Volunteers received either immediate release formulation or modified release

formulation according to their code numbers with 240 ml of water. The order of

treatment administration was randomized in two sequences (AB and BA) in blocks

of two.

Blood samples (4 ml) were collected using disposable syringes in

pre-heparinised centrifugal tubes at 0 (before drug administration), 0.5, 1.0, 1.5, 2.0,

3.0, 4.0, 6.0, 8.0, 12.0, 18.0 and 24.0 hours post dosing. The samples were

centrifuged at 3500 rpm for 10 minutes to separate plasma. They were transferred

into airtight containers and stored at deep freeze condition until starting of analysis.

A similar procedure adopting cross-over design in drug treatment was repeated after

7 days of wash out period.

3.2.6 Subject Monitoring

The study was monitored by a physician and a clinical pharmacologist. In

addition, a staff nurse and a technician were present throughout the study for blood

collection and plasma separation. The blood pressure and pulse rate were measured

at 0.5, 1, 3, 6, 12 and 24 hours post dosing. The volunteers were monitored for

abnormal symptoms during the study period and for one week after the study period

and if noticed, the details were entered in the case report sheets and tabulated at the

end of the study.

3.2.7 Meals and Food Restrictions

Standard breakfast was provided after 3 h post dosing. Subjects were

instructed to eat their entire breakfast in 30 minutes. Lunch and dinner, consisting

of caffeine-free, xanthine-free, and grapefruit-free foods and beverages, were served

after 7 and 12 hours post dosing during the in house portion of the study.

3.2.8 Extraction of drugs from plasma

All the plasma samples were extracted and their drug levels were quantified

using LC-MS/MS technique. Detailed procedures involved in extraction and

quantification are discussed under section 3.3.8.

44

3.2.9 Estimation of Pharmacokinetic Parameters

Pharmacokinetic parameters namely, the peak height concentration (Cmax),

the time of peak concentration (Tmax), and elimination rate constant (Keli) were

determined for individual drug treatments from the observed plasma concentration-

time data. The area under the plasma concentration-time curves (AUC) were

calculated by trapezoidal rule from time zero to the last observed concentration.

3.3 Analytical Method Development

Method development involves evaluation and optimization of the various

stages of sample preparation, chromatographic separation, detection and

quantification. Optimization of various parameters were tried in order to develop a

selective and sensitive method for the analysis of Pregabalin and Pramipexole in

plasma samples.

3.3.1 Selection of Molecular Ions

LC-MS/MS instrument was calibrated with Reserpine standard in positive

and negative ionization mode. LC-MS/MS detector at unit resolution in the multiple

reaction monitoring (MRM) mode was preferred. 100 ng/ml of Pregabalin,

Pramipexole, Quetiapine Fumarate and Tramadol solutions were infused and mass

spectrums were recorded. Using the mass spectra of the infused solutions, parent and

product ions were selected for analyte and internal standards.

The transition of the protonated molecular parent ions were m/z 160.2, m/z

264.2, m/z 212.30, m/z 384.80 and the product ions m/z 55.1, m/z 58.0, m/z 153.30,

m/z 220.30 for the Pregabalin, Tramadol, Pramipexole and Quetiapine Fumarate,

respectively.

3.3.2 Selection of Source Parameters

The source parameters namely Gas temperature, Gas flow, Nebulizer, Sheath

gas temperatures, Sheath gas flow, Capillary voltage, Charging voltage were

optimized for Pregabalin and Tramadol. The optimized source parameters for

Pregabalin and Tramadol is presented in Table 3.2.

45

Table 3.1 Source Parameters for Pregabalin

Source parameters Value

Gas temperature (oC) 300

Gas flow (lml/min) 10

Nebulizer (psi) 45

Sheath gas temperature (oC) 400

Sheath gas flow (lml/min) 11

Capillary voltage (V) 3500

Charging voltage (V) 500

The optimized source parameters for Pramipexole and Quetiapine is presented in

Table 3.2.

Table 3.2 Source Parameters for Pramipexole

Source parameters Value

Gas temperature (oC) 500

Gas flow (l/min) 10

Nebulizer (psi) 45

Sheath gas temperature (oC) 400

Sheath gas flow (l/min) 11

Capillary voltage (V) 5500

Charging voltage (V) 500

46

3.3.3 Column Selection

Reversed phase Hypersil, Symmetry and Phenomenox columns of different

sizes and different particle sizes (C8 (100 x 4.6 mm, 5 µm), C18 (100 x 4.6 mm, 5 µm),

C18 (50 x 4.6 mm, 5 µm), C18 (50 x 4.6, 10 µm) and C18 (3 x 30 mm, 3.5 µm)) were

tried. Based on better resolution and reproducibility, Kromasil C18 (3x 30 mm,

3.5µm) was selected for the present study.

3.3.4 Selection of Mobile Phase

Different mobile phases, such as acetonitrile and 2 mM ammonium formate

in different ratios ie. 80:20 (v/v), 70:30 (v/v), 65:35 (v/v) and 60:40 (v/v), 0.5 %

formic acid and acetonitrile in different ratios ie. 90:10 (v/v), 85:15 (v/v), 80:20 (v/v)

and 70:30 (v/v) were tried.

Based on the peak shape and separation, acetonitrile: 0.5% formic acid

(80:20) was selected as mobile phase for Pregabalin and Acetonitrile: 5mM

Ammonium Formate (65:35) was selected as mobile phase for Pramipexole analysis.

3.3.5 Effect of Injection Volume

The process of quantification at very low concentrations is a competition

between signal and noise. In order to keep the instrument clean the amount of sample

reaching into the mass spectrometer should be kept as low as possible. A comparison

was made between injecting 5 µl and 2 µl of reconstituted extracts of Pramipexole

and Pregabalinfrom 50 ng/ml of plasma samples. At 5 µl injection volume, signal to

noise ratio of Pramipexole peak was 15, whereas at 2 µl injection volume, signal to

noise ratio of Pregabalin was 15, hence, 5 µl of injection volume for Pregabalin and

2 µl of injection volume for Pramipexole was selected for the present analysis.

3.3.6 Effect of Flow Rate

Effect of flow rate on chromatogram was studied at a flow rate of 0.5, 0.75

and 1.0 ml/min of mobile phase. Pregabalin and internal standard was eluted at 1.6

and 1.4 minutes respectively at 1ml/min flow rate. Pramipexole and internal standard

47

was eluted at 1.9 and 1.81 minutes respectively at 0.5 ml/min flow rate. Flow rate of

1.0 ml/min for Pregabalin and 0.5 ml/min for Pramipexole was selected for the

present study.

3.3.7 Selection of Internal standard

Different compounds such as Tramadol, Verapamil, Paracetamol,

Itraconazole, Quetiapine, Atorvastatin etc. were tried for internal standards. Based on

the peak response with good elution and recovery Tramadol was selected as internal

standard for Pregabalin and Quetiapine was selected as internal standard for

Pramipixole.

3.3.8 Selection of Extraction Procedure

Extraction was tried with Liquid-Liquid Extraction (LLE). Aliquots of 500 µl

of spiked plasma in a glass tube was added with 50 µl of 500 ng/ml Pregabalin and

tried with different extraction solvents. The ratio of the solvents and percentage

recovery obtained is shown in Table 3.3.

Table 3.3 Liquid –Liquid Extraction of Pregabalin

Solvents (%) Volume% Recovery

Analyte IS

Methyl Tertiary butyl

Ether(MTBE)3ml 25 48

MTBE:

Dichloromethane(DCM)3ml 45 16

n-Hexane 3ml 20 18

Diethyl ether :

DCM(80:20)3ml 38 28

48

The recovery of LLE method was very low, hence Solid Phase Extraction

procedure was attempted with various cartridges. Strata-X 33 µm cartridge was

selected for the present study.

The Solid phase extraction procedure for the extraction of Pregabalin from

plasma samples as follows,

The solid phase cartridges were conditioned using 1 ml of 100%

methanol.

It was equilibrated and acidified with 1 ml of 1% Formic acid.

550 µl plasma sample and 200 µl of internal standard was added.

Washed twice with 1 ml of 1% Formic Acid.

Pregabalin was eluted with 500 µl of mobile phase (Acetonitrile: 0.5%

Formic Acid). Eluted samples were dried under Nitrogen

Reconstituted the samples with 300 µl of Mobile phase, vortexed for 1

minute and 2 µL of the sample was injected.

The Solid phase extraction procedure for the extraction of Pramipexole from

plasma samples as follows,

The solid phase cartridges were conditioned using 1ml of 100% methanol.

It was equilibrated and acidified with 1 ml of 1% Formic acid.

550 µl plasma sample and 200 µl of internal standard were added.

Washed twice with 1 ml of 20% methanol in water.

Pramipixole was eluted with 500 µl of methanol.

Eluted samples were dried under Nitrogen

Reconstituted the samples with 300 µl of Mobile phase, vortexed for 1

minute and 2 µL of the sample was injected.

49

3.4 Method Validation

3.4.1 System Suitability

Un-extracted standard was prepared equivalent to upper level of calibration

curve concentration and internal standard. It was injected for six times and the

chromatograms were recorded as per developed bioanalytical method. If the system

suitability did not pass with six injections, six more injections were performed until

the system suitability test passes. The retention times and responses of the analyte

and internal standard were recorded. The system suitability was evaluated by

manually calculating the mean, standard deviation and coefficient of variation for the

retention time and area.

The %CV of area ratio of drug and internal standard is ≤3% for single analyte

and for ≤5% for multiple analyte. The %CV of retention time of drug and internal

standard is 2%. If the results did not comply with the acceptance criteria, then the

system was checked for its malfunction and suitable remedial actions were taken and

the system suitability should be performed again.

Following parameters were assessed during validation

Selectivity

Specificity

Ruggedness

Recovery

Linearity

Precision

Accuracy

Dilution integrity

Matrix effect and

Stability

50

3.4.2 Linearity

The linearity of the selected range was determined by preparing calibration curve

consists of a blank sample (matrix sample processed without internal standard),

blank with internal standard and 8 non-zero standards covering the expected range

(coded as CS1 to CS8) were analysed.

3.4.3 Accuracy and Precision

Accuracy and precision of the method were determined by analyzing six

replicates of Lower limit of quantification (LLOQ), Lower quality control (LQC),

Middle quality control (MQC) and Higher Quality control ( HQC) in different

occasions.

Within Run accuracy and precision

Within run accuracy and precision evaluations were performed by analyzing

replicate concentration of Pregabalin in Human plasma. The run consisted of a

calibration curve standard plus a total of 24 spiked samples, 6 replicates of each of

lower limit of quantitation (LLOQ), low (LQC), medium (MQC) and high (HQC)

quality control samples.

Between run accuracy and precision

The between run accuracy and precision evaluations were assessed by the

repeated analysis of human plasma samples containing different concentrations of

Pregabalin by changing analyst to analyst and by changing the column. A single run

consisted of a calibration curve standards plus 6 replicates of LLOQ, LQC, MQC and

HQC samples.

3.4.4 Recovery

Recovery of the developed method can be evaluated by analyzing six

replicates of analyte along with internal standard by comparing the analytical results

for extracted samples at three concentrations equivalent to LQC, MQC and HQC

51

with unextracted samples that represent 100% recovery. The percentage recovery of

analyte and internal standard were calculated using appropriate chromatographic

conditions. For the internal standard, mean internal standard responses of eighteen

processed samples were compared to the mean internal standard responses of

eighteen appropriately diluted pure internal standard solutions.

3.4.5 Selectivity

Selectivity was assessed by analyzing blank plasma samples obtained from

six different sources with six samples at LLOQ concentrations spiked using the

biological matrix of any one source. Randomly selected blank human plasma sources

were taken to determine the extent to which endogenous human plasma interfere

with the analyte or the internal standard.

3.4.6 Sensitivity

Sensitivity was determined by limit of quantification by analyzing six

replicates of lower limit of quantification (LLOQ) that can be measured with

acceptable accuracy and precision.

3.4.7 Matrix Effect

It had been noted that co eluting, undetected endogenous matrix components

might reduce the ion intensity of the analyte and adversely affect the reproducibility

and accuracy of the LCMS/MS assay. In order to determine whether this effect

(matrix effect) was present or not, 6 different plasma pools were extracted and then

spiked with standard solution concentration equal to LQC (post extracted spiked

sample). Samples were prepared at low quality control level (LQC) in different

human plasma sources analysed with 3 replicates of comparison samples in a single

run. Percentage nominal concentrations were calculated for each matrix.

3.4.8 Carry over Test

Carry over is calculated as the percentage peak area observed in a processed

plasma blank injected immediately after a processed Upper limit of quantification

52

(ULOQ) calibration standard. No significant carry over was observed for analyte and

internal Standard.

3.4.9 Stability

The stabilities were assessed under varying storage and handling conditions

and determined by calculating the percentage nominal of LQC and HQC samples

against freshly prepared calibration curve standards and compared with bulk spiked

comparison samples (CS). As a part of method validation bench-top, in-injector,

stock solution, freeze thaw, dry extract, wet extract, short and long term stabilities

were also evaluated. Samples were considered to be stable if the assay values were

within the acceptable limits of accuracy (± 15% SD) and precision (± 15% RSD)

Freeze and Thaw Stability

Samples were prepared at low (LQC) and higher (HQC) quality control levels,

aliquoted and frozen at (-700C), some of the aliquots of quality control samples were

subjected to three freeze-thaw cycles (stability samples). Six replicates of each LQC,

MQC and HQC stored at (-70oC) were thawed completely unassisted at room

temperature and refrozen immediately to (-700C). This cycle was repeated for three

times with 12 hour intervals and the samples were extracted and analysed with

freshly prepared calibration curve standards and comparison samples. A calibration

curve and quality control samples were freshly prepared and processed with 6

replicates of stability samples and analyzed in a single run. At the time of analysis,

the samples were removed from deep freezer and kept in the room temperature and

allowed to thaw.

Bench Top stability

The stability of samples on the bench i.e., when kept outside the freezer were

studied to know the stability of samples at room temperature. Six replicates of LQC

& HQC were kept at room temperature for 6 hours, these samples were processed

and analysed with a freshly prepared calibration curve standards and comparison

samples.

53

3.5 Estimation of Pregabalin in Plasma Samples

3.5.1 Preparation of standard Stock Solution

10 mg of Pregabalin was transferred into a 10 mL volumetric flask. Add 5 ml

of methanol and water mixture (1:1) was added and made up the volume with same

to produce a solution of 1mg/mL strength.

3.5.2 Preparation of Calibration Curve Samples Stock Dilutions

Standard stock solution prepared ranging from 1.0 ng/mL to 200.0 ng mL

using 50:50 methanol and water mixture (1:1) and is presented in Table 3.5 and 3.6.

3.5.3 Internal standard stock solution

10 mg of internal standard was transferred to a 10 ml volumetric flask to

which 5 ml of methanol was added to dissolve. The volume was then made up to 10

ml using methanol (stock solution A).

100 µl of stock solution A was taken in a volumetric flask and the volume

was made upto 10 ml using mobile phase (stock solution B).

500 µl of stock solution B was taken in a volumetric flask and the volume

was made upto 10 ml using mobile phase (stock solution C).

Table 3.4 Preparation of PregabalinStandards for Calibration Curve (Dilution I)

Stock

Solution

concentration

(ng/mL)

Volume

of

diluent

(mL)

Stock

Solution

ID

Spiking

solution

ID

Volume

taken(mL)

Final

volume(mL)

Final conc.

(ng/mL)

C 10160.755 2.460 7.540 10.000 2500.000 CS1

C 10160.755 4.921 5.079 10.000 5000.000 CS2

B 101607.551 1.845 8.155 10.000 18750.000 CS3

B 101607.551 3.691 6.309 10.000 37500.000 CS4

A 1016075.50 1.015 8.985 10.000 103200.000 CS5

A 1016075.50 2.031 7.969 10.000 206400.000 CS6

A 1016075.50 2.986 7.014 10.000 303500.000 CS7

A 1016075.50 4.207 5.793 10.000 427500.000 CS8

A 1016075.50 4.920 5.080 10.000 500000.000 CS9

54

55

Table 3.5 Preparation of Pregabalin Standards for Calibration Curve (Dilution II)

Spiking

Solution

Concentration

(ng/ml)

Spiking

Solution

ID

Final

conc.

(ng/mL)

Volume

taken(mL)

Volume of

diluent(mL)

Final

volume(mL)

CC

ID

CS1 2500.000 0.200 9.800 10.000 50.000 CS1

CS2 5000.000 0.200 9.800 10.000 100.000 CS2

CS3 18750.000 0.200 9.800 10.000 375.000 CS3

CS4 37500.000 0.200 9.800 10.000 750.000 CS4

CS5 103200.000 0.200 9.800 10.000 2064.000 CS5

CS6 206400.000 0.200 9.800 10.000 4128.000 CS6

CS7 303500.000 0.200 9.800 10.000 6070.000 CS7

CS8 427500.000 0.200 9.800 10.000 8550.000 CS8

CS9 500000.000 0.200 9.800 10.000 10000.000 CS9

3.5.4 Preparation of QC Samples

In this the spiked samples were taken and they were used to monitor the performanceof the method. For this the samples were taken from the stock solution and they wereprepared according to the procedures given in Table 3.7 and 3.8.

56

Table 3.6 Preparation of Pregabalin QC Samples (Dilution-I)

Final

concentra

tion.

(ng/mL)

Solution

concentratio

n (ng/ml)

Volume

taken

(mL)

Volume of

diluent

(mL)

Final

volume

(mL)

Solution

ID

Spiking solution

ID

C 10160.75 2.460 7.540 10.000 2500.00 SS01-LLOQ

C 10160.75 6.292 3.708 10.000 6400.00 SS01-LQC

A 1016075.50 1.575 8.425 10.000 160000.00 SS01-MQC

A 1016075.50 3.937 6.063 10.000 400000.00 SS01-HQC

Table 3.7 Preparation of Pregabalin QC Samples (Dilution-II)

Spiking

Solution

ID

Solution

concentration

(ng/mL)

Volume of

diluent

(mL)

Final

conc.

(ng/mL)

Spiking

solution

ID

Volume

taken(mL)

Final

volume(mL)

SS01-

LLOQ2500.000 0.200 9.800 10.000 50.000 LLOQ

SS01-

LQC6400.000 0.200 9.800 10.000 128.000 LQC

SS01-

MQC160000.000 0.200 9.800 10.000 3200.000 MQC

SS01-

HQC400000.000 0.200 9.800 10.000 8000.000 HQC

57




injected with the optimised chromatographic conditions and the chromatograms

were recorded. The quantification of the chromatogram was performed using peak

area ratios (response factor) of the drug to internal standard. The calibration curves

are constructed routinely for spiked plasma containing drug and internal standard

during the process of pre-study validation and in-study validation.

3.6 Estimation of Pramipexole in Plasma Samples

3.6.1 Preparation of Pramipexole Calibration Curve Samples Stock Dilutions

Pramipexole standard calibration stock solutions ranging from 1.0 ng/mL

to 200.0 ng/mL was prepared using methanol and water mixture (1:1) as diluent as

shown in Table 3.9.

Table 3.8 Stock Dilution for Pramipexole Calibration Standard

Volumeof

Diluent(mL)

Volumeof finalsolution

(mL)

Initialsolution

ID

Initial stockconc.

(ng/mL)

Volume ofstock

taken(mL)

Final stockconc.(ng/m

L)

Final solutionS.No.

1 Std I 19662.2 0.05 4.95 5.000 196.622 SS1

2 SS 1 196.622 3.75 1.25 5.000 147.466 SS2

3 SS 2 147.466 2.50 2.50 5.000 73.733 SS3

4 SS 3 73.733 2.50 2.50 5.000 36.867 SS4

5 SS 4 36.866 1.88 3.12 5.000 13.825 SS5

6 SS 5 13.825 1.52 3.48 5.000 4.2166 SS6

7 SS 6 4.2166 2.40 2.60 5.000 2.024 SS7

8 SS 7 2.024 2.50 2.50 5.000 1.012 SS8

58

3.6.2 Stock Dilution for Pramipexole Quality Control Sample

Pramipexole quality control stock solution ranging from 100.0 to 20000.0

ng/mL using methanol and water mixture (1:1) was prepared as shown in the

Table.3.10.

Table 3.9 Stock Dilution for Pramipexole Quality Control Samples

Volume

of

Diluent

added

(mL)

Total

volume

of final

solution

mL

Initial

solution

ID

Volume of

stock

taken(mL)

Final

solution

ID

Initial stock

conc.(ng/mL)

Final stock

conc.(ng/mLS.No

1 QCStd 1 9799.54 0.2 9.8 10 195.09 QC1

2 QC1 195.99 3.75 6.26 10 73.49 QC2

3 QC2 73.49 5 5 10 36.74 QC3

4 QC3 36.74 0.75 9.25 10 2.75 QC4

5 QC4 2.75 3.7 6.3 10 1.01 QC5

3.6.3 Preparation of Quetiapine Stock Solution

9.831 mg of Quetiapine was transferred into a 10mL volumetric flask. 5 ml of

Methanol was added, mixed the contents until Quetiapine was dissolved. The volume

was made up with methanol to produce a solution of 0.983.13 mg/mL concentration

of Quetiapine.

3.6.4 Preparation of Quetiapine Stock Dilutions

0.1ml of Quetiapine stock solution was transferred into 5 ml volumetric flask

and the final volume was made using methanol:water mixture (1:1) to produce

working concentration of 19622.72 ng/mL Quetiapine.

59

3.6.5 Pramipexole Calibration Standards in Human plasma

Pramipexole stock dilutions ranging from 20.0 to 4000.0 pg/mL was prepared

as per Table 3.10.

Table 3.10 Pramipexole Calibration standards in Human plasma

Total

Volume

of Final

Solution

(mL)

Initial

solution

ID

Volume of

stock

taken(mL)

Initial stock

conc.(ng/mL)

Final Stock

Conc.(pg/ml)

Final

Solution IDS.No

1 SS 1 196.62 0.020 1 3932.44 STD- 8

2 SS 2 147.46 0.020 1 2949.33 STD- 7

3 SS 3 73.73 0.020 1 1474.66 STD- 6

4 SS 4 36.86 0.020 1 737.33 STD- 5

5 SS 5 13.82 0.020 1 276.50 STD- 4

6 SS 6 4.21 0.020 1 84.33 STD- 3

7 SS 7 2.02 0.020 1 40.48 STD- 2

8 SS 8 1.01 0.020 1 20.24 STD- 1

60

3.6.6 Preparation of Quality Control Samples of Pramipexole

Quality control samples in Human K3EDTA plasma ranging from 20.0

to 1500.0 pg/ml was prepared as per Table 3.11.

Table 3.11 Pramipexole Quality Control samples in Human Plasma

Volumeof

Diluentadded(mL)

Totalvolumeof finalsolution

(mL)

Initialsolution

ID

Volume ofstock

taken(mL)

Finalsolution

ID

S. No

Initial stock conc.(ng/mL)

Final stock conc(pg/mL)

1 QC 1 7349.66 0.200 0.800 1 1469.9320 HQC

2 QC 2 3674.83 0.200 0.800 1 734.9660 MQC

3 QC 3 275.61 0.200 0.800 1 55.1220 LQC

4 QC 4 101.98 0.200 0.800 1 20.3960 LOQQC




injected with the optimised chromatographic conditions and the chromatograms

were recorded. The quantification of the chromatogram was performed using peak

area ratios (response factor) of the drug to internal standard. The calibration curves

are constructed routinely for spiked plasma containing drug and internal standard

during the process of pre-study validation and in-study validation.

3.7 Determination of Pharmacokinetic Parameters

The following Pharmacokinetic parameters were determined for individual

drug treatments from the observed plasma concentration-time data. The area under

the plasma concentration-time curves (AUC) were calculated by trapezoidal rule

from time zero to the last observed concentration.

61

Cmax

tmax

AUC (0-t)

AUC (0- ∞)

Maximum plasma concentration

Time of maximum plasma concentration

Area under plasma concentrations time curve 0 to 24 hrs

Area under plasma concentrations time curve 0 to hrs

t 1/2

keli

Elimination half-life

Elimination constant

The statistical analysis was carried out for Cmax, AUC(0-t) and AUC (0- ∞)

3.8 Development of in-vitro dissolution studies

The release characteristics of selected drugs in their formulations is carried out

using USP XXIII dissolution apparatus (type I, basket; type II, paddle), at different

rpm, with the media of pH 1.2, 4.5, 6.8, distilled water and 7.4 buffers maintained at

37±0.5˚C. Dissolution tests was performed on twelve tablets. Percentage drug release

at various time intervals was calculated and compared.

5 ml of the samples were withdrawn at 0.0, 0.5, 1.0, 1.5, 2.0, 3.0, 4.0, 6.0, 8.0,

12.0, 18.0 and 24.0 hr time intervals for a period of 24 hours. Equal quantity of the

dissolution medium was replaced to the dissolution jar after each sampling.

The amount of the drug released was estimated. Percentage drug release at

various time intervals were calculated and compared.

3.9 In-vitro and in-vivo correlation

Difference factor (f1) and a similarity factor (f2) were calculated. The

difference factor calculates the percent difference between the two curves at each

time point and is a measurement of the relative error between the two curves. The

similarity factor is a logarithmic reciprocal square root transformation of the sum

squared error and is a measurement of the similarity in the percent dissolution

between the two curves. Generally, f1 values up to 15 (0-15) and f2 values greater

than 50 (50-100) ensure sameness or equivalence of the two curves.

62

The measured plasma concentrations were used to calculate the area under

the plasma concentration-time profile from time zero to the last concentration time

point (AUC(0-t)). The AUC(0-t) was determined by the trapezoidal method. AUC(0-ω)

was determined by the following equation:

AUC(0-ω) = AUC(0-t) + C(t)/ ke

kewas estimated by fitting the logarithm of the concentrations versus time to a

straight line over the observed exponential decline. The Wagner-Nelson method42

was used to calculate the percentage of the selected drugs dose absorbed

F(t) = C(t) + ke AUC(0-t)

Where F(t) is the amount absorbed.

The percent absorbed is determined by dividing the amount absorbed at any

time by the plateau value, keAUC(0-ω) and multiplying this ratio by 100:

C(t) + ke AUC(0-t)

% dose absorbed = x 100

ke AUC(0-ω)

The percentage of drug dissolved was determined using the aforementioned

dissolution testing method and the fraction of drug absorbed was determined using

the method of Wagner-Nelson. Linear regression analysis was used to examine the

relationship between percentage of drug dissolved and the percentage of drug

absorbed. The percentage of drug un-absorbed was calculated from the percentage

absorbed. The slope of the best-fit line for the semi-log treatment of this data was

taken as the first order rate constant for absorption. The dissolution rate constants

were determined from percentage released vs the square root of time. Linear

regression analysis was applied to the in-vitro and in-vivo correlation plots and

coefficient of determination (r2), slope and intercept values were calculated.

63

3.9.1 Validation of IVIVC


dissolution data and mean in-vivo pharmacokinetics of the selected modified release

formulations. Briefly, the correlation of the mean in-vitro dissolution rate constants

was correlated to the mean absorption rate constants for the modified release

formulations. These two data points, along with the zero-zero intercept were used to

calculate the expected absorption rate constants.

The prediction of plasma concentration was accomplished using thefollowing curve fitting equation:

kay = Const. X (Dose) X ------------ (e-ket – e-kat)

ka - ke

Where, y is predicted plasma concentration (mcg/ml);

Const. is the constant representing F / Vd (where F is the fraction

absorbed, and Vd is the volume of distribution);

ka is absorption rate constant;

keisoverall elimination rate constant.

The de-convolution was accomplished on a spread-sheet in Excel.

To further assess the predictability and the validity of the correlations, IVIVC

model-predicted Cmax and AUC values were determined for each formulation. The

percent prediction errors for Cmax and AUC were calculated as follows:

Cmax (obs) - Cmax (pred)% PECmax = ------------------------------- X 100

Cmax (obs)

AUC (obs) - AUC (pred)% PEAUC = ------------------------------- X 100

AUC (obs)

64

Where Cmax (obs) and Cmax (pred) are the observed and IVIVC model-

predicted maximum plasma concentrations, respectively;

AUC (obs) and AUC (pred) are the observed and IVIVC model-predicted

AUC for the plasma concentration profiles, respectively.

65

CHAPTER 4

RESULTS AND DISCUSSION

This chapter describes the experimental results obtained in the present

investigation in the form of Tables and Figures along with a detailed discussion on

results of bioequivalence study design and data handling, development of LC-

MS/MS methods for the estimation of Pregabalin and Pramipexole in plasma

samples, validation of the developed methods, estimation of the selected drugs in

plasma samples, determination of pharmacokinetic parameters, development of

in-vitro dissolution studies, in-vivo and in-vitro data analysis and in-vitro and in-vivo

correlation model development and validation.

The developed in-vitro and in-vivo correlation, may serve as surrogate for

additional bioequivalence studies as part of the formulation development, scale up

and pre and post approval changes.

4.1 Bioequivalence study design and data handling

Comparative bioavailability studies between immediate release formulation

(IR formulation) and modified release formulations (MR formulation) of selected

drugs were carried out in 24 healthy human subjects adopting a single dose,

randomized, complete, two ways, two periods cross over design.

After overnight fasting, the volunteers were given code numbers and were

allocated to the treatment in accordance with the randomisation code. The order of

treatment administration was randomised in two sequences (AB and BA) in blocks of

two. In each dosing session, volunteers received either immediate release

66

formulation or modified release formulation. A washout period of seven days was

allowed between dose administrations.

A total of 13 blood samples were collected at 0 hour (before drug

administration) 0.5, 1.0, 1.5, 2.0, 3.0, 4.0, 6.0, 8.0, 10.0, 12.0, 18.0 and 24.0 hours

post dosing. Blood Samples were collected through an indwelling cannula placed in

a forearm vein. The pre-dose blood sample was collected within a period of one hour

before dosing and post-dose samples were collected within 2-minutes of the schedule

time. The blood samples were collected in 6-ml vacutainers containing EDTA as the

anticoagulant. The Plasma was separated, divided into two portions while

transferring to labeled storage vials and promptly frozen at -70 C until analysis.

All subjects were on fast overnight for a period of 10 hours before

commencement of dosing. Drinking water was not allowed from one hour pre-dosing

to two hours post dosing except while administering the dose. Uniform and low fat

meals were provided to all the subjects. A standard breakfast and lunch were

provided at 4, 8, and 12 hours after the drug administration.

The samples were centrifuged and plasma was separated. There were no

serious adverse effects observed during the entire study. The total number of blood

samples drawn during the study was 28 and the total volume of blood drawn

including 15ml for screening was about 200 ml.

4.2 Development of LC-MS/MS Methods for the Estimation of Pregabalin and

Pramipexole in Plasma Samples

The LC MS/MS instrument was calibrated with polypropylene glycol

standard in positive and negative ion mode. Infusion was done using 500 ng/ml of

Pregabalin, Pramipexole and internal standards in mobile phase. Using the mass

spectra of this solution, mass spectrometer parameters were optimized.

The various LC-MS/MS conditions namely, source parameters, column

selection, volatile mobile phase, selective extraction procedure and sensitive

acquisition methods, pH of the mobile phase, solvent strength, solvent ratio, flow

rate, addition of peak modifiers in mobile phase, nature of the stationary phase,

67

injection volume, molecular ion and internal standard were optimized in order to

develop a selective and sensitive method for the analysis of Pregabalin and

Pramipexole in plasma samples.

The optimized method for the estimation of Pregabalin in plasma samples is,

Mass Spectrometer : Agilent 6460 QQQ

Ion source : ESI + Agilent Jet Stream

Polarity : Positive

Pregabalin Ion : 160.2 (parent), 55.1 (product)

Tramadol Ion : 264.2 (parent), 58.0 (product)

Column : Kromasil C18 (3.5µm, 3, 30 mm)

Column oven temperature : 35.00C

Auto sampler temperature : 150C

Mobile phase : Acetonitrile: 0.5% Formic Acid (80:20)

Flow rate : 1 ml/min

Volume of injection : 2µl

Pregabalin Retention Time : 1.042

Tramadol Retention Time : 1.120

Run time : 2 minutes

Dwell time : 200 ms

68

The optimized method for the estimation of Pramipexole in plasma samples is,

Mass Spectrometer : API 5500, AB Sciex

Ion source : ESI + Agilent Jet Stream

Polarity : Positive

Pramipexole Ion : 212.30 (parent), 153.30 (product)

Quetiapine Fumarate Ion : 384.80 (parent), 220.300 (product)

Column : Hypersil gold column (5 µm,50 x 4.6 mm)

Column oven temperature : 35.00C

Auto sampler temperature : 150C

Mobile phase : Acetonitrile :5mM Ammonium Formate

Mobile Phase Ratio : (65:35) Flow

rate : 0.5 mL/min

Volume of injection : 5µl

Pramipexole RT : 1.81 minutes

Quetiapine Fumarate RT : 1.30 minutes

Run time : 3 minutes

Dwell time : 200 ms

69

4.3 Method Validation for Pregabalin

The developed method was validated according to currently accepted FDA

guidelines of bio-analytical method validation.

4.3.1 Linearity

Calibration curves are found to be consistently accurate and precise, linear over

the range of 50 to 10000 ng/ml. The correlation coefficient (r) is equal to 0.9949.

Back calculations were made from the calibration curves to determine Pregabalin

concentrations of each calibration standard. Datas are presented in Table 4.1 and a

typical calibration curve is presented in Figure 4.1



replicates of lower limit of quantitation (LLOQ), low (LQC), medium (MQC) and

high (HQC) quality control samples in different occasions.

Intra-batch accuracy and precision evaluations were performed by analyzing

replicate concentration of Pregabalin in Human plasma. The run consisted of a



quality control samples. The percentage of nominal value should be within 15% of

the actual except at LLOQ, where it should not deviate by more than 20%. Each

concentration level should not exceed 15% of the coefficient of variation (CV)

except for the LLOQ, where it should not exceed 20% of the coefficient of variation

(CV).

Intra-batch coefficients of variation for limit of quantification of quality

control (LOQQC), low (LQC), medium (MQC), high (HQC) quality control for

Pregabalin samples were 8.48, 1.14, 3.67 and 4.57 %, respectively. Intra-batch

percentages of nominal concentrations for LOQQC, LQC, MQC and HQC were

105.07, 90.73, 108.81 and 106.20 %, respectively, and it is within the limit. The

results are shown in Table 4.2.

70

Inter-batchaccuracy and precision evaluations were assessed by the repeated

analysis of human plasma samples containing different concentrations of Pregabalin

by changing analyst to analyst and by changing the column. A single run consisted of

a calibration curve standards plus 6 replicates of lower limit of quantitation (LLOQ),

low (LQC), medium (MQC) and high (HQC) quality control samples. The

percentage of nominal value should be within 15% of the actual value except at

LLOQ, where it should not deviate by more than 20%. Each concentration level

should not exceed 15% of the coefficient of variation (CV) except for the LLOQ,

where it should not exceed 20% of the coefficient of variation (CV).

Inter-batch coefficients of variation for LOQQC, LQC, MQC, HQC samples

of Pregabalin were 4.88, 2.39, 3.35 and 4.75 % respectively. The between run

percentages of nominal concentrations for LOQQC, LQC, MQC and HQC were

103.06, 97.97, 102.42 and 103.08 % respectively and it is within the limit. The

results are shown in Table 4.3.

Recovery of the developed method can be evaluated by analyzing six

replicates of analyte along with internal standard by comparing the analytical results

for extracted samples at three concentrations (equivalent to LQC, MQC and HQC)

with un-extracted samples that represent 100 % recovery. The percentage recovery of

analyte and internal standard (IS) were calculated. For the internal standard, mean

internal standard responses of eighteen processed samples were compared to the

mean internal standard responses of eighteen appropriately diluted pure internal

standard solutions. Recovery of the analyte need not be 100%, but the extent of

recovery of an analyte and of the internal standard should be consistent, precise and

reproducible.

Mean recovery values are 88.92, 88.25 and 84.81 % at low, medium and high

quality control levels respectively. Mean recovery value for the internal standard

was 89.43% and it is within the limit. Results are presented in Table 4.4 and 4.5.

71

4.3.3 Matrix Selectivity

Selectivity was assessed by analyzing blank plasma samples obtained from six

different sources with six samples at LLOQ concentrations spiked using the



with the analyte or the internal standard. The Results are presented in Table 4.5.

No significant interference was observed in six different sources of human

plasma samples.

4.3.4 Sensitivity



acceptable accuracy and precision. A calibration curve standards and lower limit of

quantification samples (LLOQ) were processed and analysed in a single run. At the

time of analysis, the samples were removed from the deep freezer and kept in the

room temperature and allowed to thaw. Analyte peak (response) should be

identifiable, discrete and reproducible with a precision of 20% and accuracy of 80 to

120%. Results are presented in Table 4.6.

Lower limit of quantitation for Pregabalin coefficient of variation was 6.766

and a percentage of nominal concentration was 109.07 % which is within the limit.

4.3.5 Matrix effect

Undetected endogenous matrix components might reduce the ion intensity of

the analyte and adversely affect the reproducibility and accuracy of the LC-MS/MS

assay. In order to determine the matrix effect, 6 different plasma pools were

extracted and then spiked with standard solution concentration equal to LQC (post

extracted spiked sample). Samples were prepared at low quality control level (LQC)

in different human plasma sources analysed with 3 replicates of comparison samples

in a single run. Percentage nominal concentrations were calculated for each matrix.

72

The Results are presented in Table 4.7. The Matrix effect was found to be 104.84%

for Pregabalin.


Carry over test was calculated as the percentage peak area observed in a

processed plasma blank injected immediately after a processed ULOQ calibration

standard. No significant carry over was observed for Analyte and Internal Standard.

The Results are presented in Table 4.8.

4.3.7 Stability


Six replicates of each LQC, MQC and HQC stored at (-70oC) were thawed

completely unassisted at room temperature and refrozen immediately to (-700C). This

cycle was repeated for three times with 12 hour intervals and the samples were

extracted and analysed with freshly prepared calibration curve standards and

comparison samples.

Samples were prepared at low (LQC) and higher (HQC) quality control and

frozen at (-700C), some of the aliquots of quality control samples were subjected to

three freeze thaw cycles (stability samples). A calibration curve and quality control

samples were freshly prepared and processed with 6 replicates of stability samples

and analyzed in a single run. At the time of analysis, the samples were removed from

deep freezer and kept in the room temperature and allowed to thaw. The Results are

presented in Table 4.9.

The mean accuracy of Quality Control samples at each level was within ±15%

of the actual value.

Bench Top stability

Six replicates of LQC and HQC were kept at room temperature for 6 hours,

these samples were processed and analysed with a freshly prepared calibration curve

standards and comparison samples. The Results are presented in Table 4.10.

73

Table 4.1 Intercept, Slope and Correlation Coefficient Values for Pregabalin

Calibration Curve

Curve No. Intercept SlopeCorrelation

coefficient(r2)

1 0.275 0.0007 0.9974

2 0.981 0.0006 0.9958

3 1.024 0.0001 0.9941

4 0.289 0.0005 0.9953

5 0.265 0.0004 0.9962

Fig. 4.1: Calibration Curve of Pregabalin

Table 4.2 Intra-batch Accuracy and Precision of Pregabalin

QC ID LLOQ LQC MQC HQC

Actualconcentration

ng/mL50.00 128.06 3201.42 8003.55

PA-01

47.13 118.60 3436.57 7908.46

55.52 116.11 3459.41 8310.70

57.08 115.87 3428.68 8658.44

55.15 115.34 3523.49 9141.63

55.91 116.87 3526.73 9039.95

56.42 114.31 3605.57 8973.44

Mean 54.53 116.18 3496.76 8672.11

SD 3.69 1.46 67.98 481.77

%CV 6.77 1.26 1.94 5.56

%Nominal 109.06 90.73 109.23 108.35

PA-02

48.16 124.62 3126.52 7906.43

54.42 129.11 3359.42 7830.63

52.06 126.86 3228.43 8258.43

49.14 120.12 3423.46 8141.64

53.98 125.89 3326.62 8890.95

51.41 126.11 3208.53 8473.24

Mean 51.53 125.45 3278.83 8250.22

SD 2.52 3.00 109.88 391.50

%CV 4.88 2.39 3.35 4.75

%Nominal 103.06 97.97 102.42 103.08

PA-03

48.12 118.60 3436.54 7808.43

45.53 116.11 3359.41 8410.69

55.06 115.87 3628.48 8258.43

52.14 115.34 3543.48 8941.62

57.92 116.87 3326.72 8803.93

56.43 114.31 3606.57 8773.43

Mean 52.53 116.18 3483.53 8499.42

SD 4.46 1.33 128.02 388.80

%CV 8.48 1.14 3.67 4.57

%Nominal 105.07 90.73 108.81 106.20

74

Table 4.3 Inter-batch Accuracy and Precision of Pregabalin

QC ID LLOQ LQC MQC HQC

Actualconcentration

ng/mL50.00 128.05 3201.41 8003.54

PA-01

54.53 116.18 3496.76 8672.1155.52 116.10 3459.40 8410.6957.08 115.86 3428.67 8658.4356.02 118.12 3302.63 8868.2052.08 128.12 3102.61 8168.2052.52 126.10 3159.40 8080.63

Mean 54.62 120.08 3324.91 8476.38

SD 1.98 5.54 164.73 310.12

%CV 3.62 4.61 4.95 3.65

% Nominal 109.25 93.77 103.85 105.90

PA-02

48.12 118.60 3436.54 7808.4245.52 116.10 3359.40 8410.6853.23 126.16 3486.76 8682.1254.62 116.14 3259.42 8310.6855.28 118.86 3628.67 8638.4252.03 124.87 3428.62 8820.24

Mean 51.468 120.12 3433.24 8445.09SD 3.857 4.36 123.89 363.01% CV 7.49 3.63 3.61 4.29% Nominal 102.94 96.19 107.24 105.52

PA-03

48.16 124.62 3126.52 7906.4254.42 129.11 3359.41 7830.6252.06 126.86 3228.42 8258.4249.14 120.12 3423.46 8141.6453.98 125.88 3326.62 8890.9451.41 126.11 3208.52 8473.23

Mean 51.53 125.45 3278.82 8250.21

SD 2.519 3.003 109.88 391.50

% CV 4.88 2.39 3.35 4.75

% Nominal 103.06 97.97 102.42 103.08

75

Table 4.4 Recovery of Pregabalin

Sample NameExtracted sample

ResponseUn extracted

sample Response % Recovery

LQC

6912 7680

88.92 %

7765 85337903 88158181 90377508 8763

7949 9149Mean 7703 8663SD 446.44 527.81%CV 0.602 6.092

MQC

250914 285486

88.25 %

283355 314839234636 272928280869 323712264981 287898265775 305946

Mean 263421 298468SD 18410.72 19461.52%CV 6.989 6.520

HQC

611211 712699

84.81 %

657090 782436645259 799875647679 731593569744 702434605876 676956

Mean 622809 734332SD 33271.13 47738.47%CV 5.342 6.500

76

Table 4.5 Recovery of Tramadol (lnternal Standard)

Extracted sample

Response

Un extracted

sample ResponseS. No % Recovery

1 1128024 1261348

89.43 %

2 1015235 1135228

3 1088757 1217440

4 1151089 1287139

5 1152370 1289004

6 1061858 1187362

7 1523122 1703144

8 1177545 1316722

9 1073840 1200760

10 1083053 1211062

11 1020475 1141088

12 1109863 1241041

13 1140817 1275653

14 1126721 1259891

15 1188609 1329094

16 1055095 1179799

17 1147110 1282690

18 1019673 1140191

Mean 1125736 1258814

SD 112809.1 126148.4

%CV 10.020 10.021

77

78

Table 4.6 Matrix Selectivity of Pregabalin

Matrix IdentificationInterference with

AnalyteInterference with IS

MT-144/09 0.00 0.00

MT-146/09 0.00 0.00

MT-157/09 0.00 0.00

MT-159/09 0.00 0.00

Heamolysed plasma 0.00 0.00

Lipemic plasma 0.00 0.00

Table 4.7 Lower Limit of Quantitation (LLOQ)

S. No

Cal. concentration

(2.001 ng/mL)

Accuracy

1 47.13 94.25

2 55.52 111.03

3 57.08 114.15

4 55.15 110.29

5 55.91 111.81

6 56.41 112.82

Mean 54.53

SD 3.68

%CV 6.76

% Nominal 109.07

79

Table 4.8 Matrix Effect of Pregabalin

LQCMatrix ID

Response ofstandard solution

Response of PostExtracted sample

Matrix factor

MT-110/09

9158 8733 104.87

9346 8875 105.31

9417 9037 104.20

MT-114/09

9170 8733 105.00

9157 8875 103.18

9977 9037 110.40

MT-115/09

8870 8733 101.57

9284 8875 104.61

9551 9037 105.69

MT-124/09

9293 8733 106.41

9351 8875 105.36

10111 9037 111.88

MT-123/09

9334 8733 106.88

9600 8875 108.17

9922 9037 109.79

MT-125/09

8863 8733 101.49

9473 8875 106.74

9478 9037 104.88

Table 4.9 Carry over test of Pregabalin

Sample ID Analyte peak area IS peak area

Extracted blank 0 0

Extracted LLOQ+IS 1061858 1187362

Extracted ULOQ+IS 1188609 1329094

Extracted blank 0 0

% Carry over 0.00 0.00

(µg/mL) (µg/mL)

1 134.16 104.77 135.27 105.64

2 139.83 109.2 137.50 107.38

3 132.48 103.46 132.92 103.8

4 136.17 106.34 142.43 111.23

5 135.42 105.75 139.51 108.95

6 133.52 104.27 140.32 109.58

Mean 135.26 137.99

SD 2.59 3.48

%CV 1.91 2.52

% Stability 102.01

1 7014.30 87.64 8218.84 102.69

2 7328.84 91.57 8671.04 108.34

3 7105.55 88.78 8253.25 103.12

4 7456.10 93.16 7580.96 94.72

5 7874.69 98.39 8215.64 102.65

6 8528.58 106.56 8020.35 100.21

Mean 7551.34 8160.01

SD 566.61 355.30

%CV 7.50 4.35

% Stability 108.06

80

Table 4.10 Freeze and Thaw Stability of Pregabalin

SampleFresh samples After 3 cycle

Name S. NoCal. Con.

AccuracyCal. Con.

Accuracy

LQC

HQC

Table 4.11 Bench Top stability of Pregabalin

Sample

Name

Fresh samples After 6 hours

S. NoCal. Con.

(µg/mL)Accuracy

Cal. Con.

(µg/mL)Accuracy

LQC

1 137.32 107.24 127.89 99.87

2 143.33 111.93 141.61 110.59

3 140.76 109.92 121.87 95.17

4 127.89 99.87 133.89 104.56

5 134.75 105.23 115.00 89.81

6 145.05 113.27 136.47 106.57

Mean 138.18 129.45

SD 6.30 9.85

%CV 4.56 7.61

% Stability 93.68

HQC

1 7856.28 98.16 7010.30 87.59

2 7327.24 91.55 7143.16 89.25

3 7441.69 92.98 7752.23 96.86

4 6953.48 86.88 7666.59 95.79

5 7183.98 89.76 8027.55 100.30

6 6826.22 85.29 8378.11 104.68

Mean 7264.82 7662.99

SD 369.00 519.32

%CV 5.07 6.77

% Stability 105.48

81

82

4.4 Validation of Pramipexole

4.4.1 Linearity

Calibration curves are found to be consistently accurate and precise, linear

over the range of 200 to 4000 pg/mL. The correlation coefficient (r) is equal to

0.9928. Back calculations were made from the calibration curves to determine

Pramipexole concentrations of each calibration standard. Correlation coefficient

values are presented in Table 4.12 and a typical calibration curve is presented in

Figure 4.2.



replicates of LLOQ, LQC, MQC and HQC in different occasions.

Intra-batch accuracy and precision evaluations were performed by analyzing

replicate concentration of Pramipexole in Human plasma. The run consisted of a



quality control samples. Intra-batch coefficients of variation for limit of

quantification of quality control (LOQQC), low (LQC), medium (MQC), high

(HQC) quality control for Pramipexole samples were 11.37, 6.38, 3.01 and 5.92 %

respectively. Intra-batch percentages of nominal concentrations for LOQQC, LQC,

MQC and HQC were 116.80, 103.90, 103.07 and 97.59 % respectively and it is

within the limit. The results are shown in Table 4.13.

Inter-batchaccuracy and precision evaluations were assessed by the repeated

analysis of human plasma samples containing different concentrations of

Pramipexole by changing analyst to analyst and by changing the column. A single

run consisted of a calibration curve standards plus 6 replicates of lower limit of

quantitation (LLOQ), low (LQC), medium (MQC) and high (HQC) quality control

samples. Inter-batch coefficients of variation for LOQQC, LQC, MQC, HQC

samples of Pramipexole were 14.70, 8.56, 4.18 and 1.53% respectively. The

between run percentages of nominal concentrations for LOQQC, LQC, MQC and

83

HQC were 116.77, 96.85, 106.96 and 109.79% respectively and it is within the limit.

The results are shown in Table 4.14.

Recovery of the developed method can be evaluated by analyzing six replicates

of analyte along with internal standard by comparing the analytical results for

extracted samples at three concentrations (equivalent to LQC, MQC and HQC) with

un-extracted samples that represent 100% recovery. The percentage recovery of

analyte and internal standard were calculated using appropriate chromatographic

conditions. For the internal standard, mean internal standard responses of eighteen

processed samples were compared to the mean internal standard responses of

eighteen appropriately diluted pure internal standard solutions. Mean recovery

values were 74.03, 82.52 and 80.12% at low, medium and high quality control levels

respectively. Mean recovery value for the internal standard was 80.43 % and it is

within the limit. Results are presented in Table 4.15 and 4.16.

4.4.3 Matrix Selectivity

Selectivity was assessed by analyzing blank plasma samples obtained from six

different sources with six samples at LLOQ concentrations spiked using the



with the analyte or the internal standard. The Results are presented in Table 4.17.

4.4.4 Sensitivity



acceptable accuracy and precision. Results are presented in Table 4.17. Lower limit

of quantitation for Pramipexole coefficient of variation was 3.64 and a percentage of

nominal concentration was 98.07 % which is within the limit.

84

4.4.5 Matrix effect

It had been noted that co eluting, undetected endogenous matrix components

might reduce the ion intensity of the analyte and adversely affect the reproducibility

and accuracy of the LC-MS/MS method. In order to determine whether this effect

(matrix effect) was present or not, 6 different plasma pools were extracted and then

spiked with standard solution concentration equal to LQC (post extracted spiked

sample). Samples were prepared at low quality control level (LQC) in different

human plasma sources analysed with 3 replicates of comparison samples in a single

run. Percentage nominal concentrations were calculated for each matrix. The Results

are presented in Table 4.18. The Matrix effect was found to be 101.84 % for

Pramipexole.


Carry over is calculated as the percentage peak area observed in a processed

plasma blank injected immediately after a processed ULOQ calibration standard. No

significant carry over was observed for Analyte and Internal Standard. The Results

are presented in Table 4.19.

4.4.7 Stability


Six replicates of each LQC, MQC and HQC stored at (-70oC) were thawed

completely unassisted at room temperature and refrozen immediately to (-700C). This

cycle was repeated for three times with 12 hour intervals and the samples were

extracted and analysed with freshly prepared calibration curve standards and

comparison samples. Samples were prepared at low (LQC) and high (HQC) quality

control levels and frozen at (-700C), some of the aliquots of quality control samples

were subjected to three freeze-thaw cycles (stability samples). A calibration curve

and quality control samples were freshly prepared and processed with 6 replicates of

stability samples and analyzed in a single run. At the time of analysis, the samples

were removed from deep freezer and kept in the room temperature and allowed to

85

thaw. The Results are presented in Table 4.20. The mean accuracy of Quality Control

samples at each level was within ±15% of the actual value.

Bench Top stability

The stability of samples on the bench i.e., when kept outside the freezer were

studied to know the stability of samples at room temperature. Six replicates of LQC

& HQC were kept at room temperature for 6 hours these samples were processed and

analysed with a freshly prepared calibration curve standards and comparison

samples. The Results are presented in Table 4.21.

86

Table 4.12 Intercept, Slope and Correlation coefficient values for

Pramipexole Calibration Curve

Curve

No.Intercept Slope

Correlation

coefficient(r2)

1 0.265 0.0004 0.9962

2 0.971 0.0005 0.9948

3 0.289 0.0005 0.9953

4 1.024 0.0001 0.9941

5 0.275 0.0007 0.9974

Fig. 4.2: Calibration Curve of Pramipexole

Table 4.13 Intra-batch Accuracy and Precision of Pramipexole

QC ID LOQQC LQC MQC HQC

ActualConcentration

pg/mL20.40 55.12 1469.93 2939.86

PA-01

20.13 47.49 1648.28 3284.71

22.42 51.90 1530.35 3282.22

24.09 57.63 1562.10 3162.53

22.43 50.63 1510.47 3187.47

19.65 52.84 1659.87 3222.18

24.18 59.83 1522.64 3227.41

Mean 23.82 53.39 1572.28 3227.76

SD 3.50 4.57 65.72 49.23

%CV 14.70 8.56 4.18 1.53

%Nominal 116.77 96.85 106.96 109.79

PA-02

24.16 50.12 1538.16 3315.38

23.02 57.41 1484.66 3100.34

21.80 48.30 1515.32 2934.57

24.06 49.62 1537.21 2989.89

25.01 54.12 1554.41 2876.49

24.47 52.14 1560.85 3075.70

Mean 25.42 51.95 1531.77 3048.73

SD 4.43 3.37 28.00 155.34

%CV 17.44 6.38 1.83 5.10

%Nominal 124.63 94.25 104.21 103.70

PA-03

28.48 45.47 1598.67 2886.47

23.25 49.67 1504.33 2983.14

23.73 99.58 1477.95 2958.73

23.17 49.35 1534.46 2960.82

24.22 51.78 1485.63 2893.64

20.08 47.77 1489.11 2531.37

Mean 23.82 57.27 1515.03 2869.03

SD 2.71 20.84 45.60 169.95

% CV 11.37 6.38 3.01 5.92

% Nominal 116.80 103.90 103.07 97.59

87

Table 4.14 Inter-batch Accuracy and Precision of Pramipexole

QC ID LOQQC LQC MQC HQC

ActualConcentration

pg/mL20.40 55.12 1469.93 2939.86

PA-01

24.16 50.12 1538.16 3315.38

23.02 57.41 1484.66 3100.34

21.80 48.30 1515.32 2934.57

24.06 49.62 1537.21 2989.89

25.01 54.12 1554.41 2876.49

24.47 52.14 1560.85 3075.70

Mean 25.42 51.95 1531.77 3048.73

SD 4.43 3.37 28.00 155.34

% CV 17.44 6.48 1.83 5.10

% Nominal 124.63 94.25 104.21 103.70

PA-02

28.48 45.47 1598.67 2886.47

23.25 49.67 1504.33 2983.14

23.73 54..5839 1477.95 2958.73

23.17 49.35 1534.46 2960.82

24.22 51.78 1485.63 2893.64

20.08 47.77 1489.11 2531.37

Mean 23.82 57.27 1515.03 2869.03

SD 2.71 20.84 45.60 169.95

% CV 11.37 6.38 3.01 5.92

% Nominal 116.80 103.90 103.07 97.59

PA-03

20.13 47.49 1648.28 3284.71

22.42 51.90 1530.35 3282.22

24.09 57.63 1562.10 3162.53

22.43 50.63 1510.47 3187.47

19.65 52.84 1659.87 3222.18

24.18 59.83 1522.64 3227.41

Mean 23.82 53.39 1572.28 3227.76

SD 3.50 4.57 65.72 49.23

% CV 14.70 8.56 4.18 1.53

% Nominal 116.77 96.85 106.96 109.79

88

Table 4.15 Recovery of Pramipexole

Quality control sample

ID

Aqueous analyte

area

Extracted Analyte

Area

LQC

5827 2861

3560 3196

3641 2729

3489 2831

3396 3017

3757 2889

Mean 3945 2921

%Recovery 74.03

MQC

108254 91159

112579 9390

113729 92370

116525 95627

115943 95699

118523 97800

Mean 114259 94291

%Recovery 82.52

HQC

237576 200475

234150 190470

233862 180647

229446 178929

223307 175996

227618 183945

Mean 230993 185077

% Recovery 80.12

89

Table 4.16 Recovery of Quetiapine (Internal Standard)

Quality control

sample IDAqueous analyte area

Extracted Analyte

Area

LQC

286951 274785

182502 264753

248380 273006

304910 274887

311395 266484

319042 265670

MQC

362114 266398

365558 270301

359083 268334

363605 273828

365346 270992

367941 275798

HQC

366101 265758

367659 270033

366802 270595

366252 263057

361254 268961

361082 262875

Mean 334777 269251

% Recovery 80.43

90

91

91

Table 4.17 Matrix Selectivity of Pramipexole

Plasma

lot

Selectivity (spiked

LLOQ)

%inter-ference in

BlankSpecificity (Blank) Area Ratio SN Ratio

Analyte IS peak Analyte IS peak

Analyte

(≤20%)

IS peak

(≤5%)

Analyte/ IS

Analyte

MAT 916 0 0 1892 128972 0.000 0.000 0.0147 44.862

MAT 917 0 0 1876 125755 0.000 0.000 0.0149 45.794

MAT 918 0 0 1928 124231 0.000 0.000 0.0155 49.631

MAT 919 0 0 1863 122650 0.000 0.000 0.0152 51.504

MAT 920 0 0 1850 122876 0.000 0.000 0.0151 44.596

MAT 921 0 0 1720 122123 0.000 0.000 0.0141 37.892

MAT

136(H*)

0 0 1851 123922 0.000 0.000 0.0149 52.306

Mean 0.01491

SD 0.000441

%CV 2.96

(H)*- Haemolyzed Lot % of lots passed = 100.00%

92

92

Table 4.18 Lower Limit of Quantitation (LLOQ) of Pramipexole

Parameters LLOQ

Calculated concentration (pg mL)

20.240

20.993

19.407

20.082

19.600

19.161

Mean 19.848

SD 0.723

%CV 3.640

%Nominal 98.073

93

93

Table 4.19 Matrix Effect of Pramipexole

Aqueous sample Spiked sample Area ratio Matrix Factor

Analyte

Area

Analyte

Area

Aqueous

sample

Spiked

sample

Matrix

FactorLot No IS Area IS Area

MAT 916 4489 121787 4429 119724 0.0369 0.037 1.02

MAT 917 4586 122720 4116 120522 0.0374 0.0342 0.94

MAT 918 4542 124656 4401 119279 0.0364 0.0369 1.02

MAT 919 4339 122989 4858 120102 0.0353 0.0404 1.11

MAT 920 4402 122223 4405 120335 0.036 0.0366 1.01

MAT 921 4465 124470 4519 119748 0.0359 0.0377 1.04

MAT

136(H*)

4386 121450 0.0361 0.99

Mean 0.036 0.036 1.018

SD 0.051

%CV 5.04

(H)*- Haemolyzed Lot Matrix Effect = 101.84

Table 4.20 Carry over test of Pramipexole

Sample ID Analyte peak area IS peak area

Extracted blank 0 0

Extracted LLOQ+IS 4489 121787

Extracted ULOQ+IS 4586 122720

Extracted blank 0 0

%Carry over 0.00 0.00

Table 4.21 Freeze and Thaw stability of Pramipexole

LQC CS HQC CS LQC FT4 HQC FT4

55.122 2939.864 55.122 2939.864

Actual

concentration

(pg/mL)

Calculated

concentration

(pg/mL)

58.822 2979.755 63.466 2982.360

61.391 2924.904 55.401 2572.076

60.429 2928.377 53.287 2898.413

62.534 3014.649 54.065 2797.862

63.728 2852.733 51.702 2775.815

62.828 2942.260 55.189 2883.421

Mean 61.622 2940.446 55.519 2818.324

SD 1.790 55.0183 4.1217 141.720

%CV 2.91 1.87 7.42 5.03

%Nominal 111.79 100.02 100.72 95.87

% Nominal against

CS

90.10 95.85

94

Table 4.22 Bench Top stability of Pramipexole

0.hr 8hrs

LQC CS HQC CSLQC

stability

HQC

stability

Actual concentration

(pg/mL)

55.122 2939.864 55.122 2939.864

Calculated

concentration(pg/mL)

55.921 2991.807 53.741 3002.031

54.392 3021.0761 52.296 3064.895

62.302 2968.565 48.587 3033.745

54.816 2989.871 50.670 2921.980

52.401 2963.158 52.930 3000.352

52.469 2875.439 62.163 3005.113

Mean 55.384 2968.316 53.398 3004.686

SD 3.656 49.905 4.668 47.614

%CV 6.60 1.68 8.74 1.58

%Nominal 100.48 100.97 96.87 102.20

% Nominal against CS 96.41 101.23

95

96

4.5 Estimation of Pregabalin and Pramipexole in plasma samples

Estimation of Pregabalin and Pramipexole in plasma samples from the

volunteers was carried out using optimized chromatographic conditions.

The mass spectrum of Pregabalin parent ion and product ions were given in

Fig. 4.3 and 4.4 and for Tramadol parent ion and product ions were given in Fig. 4.5

and 4.6. A typical chromatogram obtained from a processed blank human plasma

sample is presented in Figure 4.7 and representative chromatograms of the lower

limit of quantitation, lower quality control, middle quality control, higher quality

control and upper limit of quantitation samples were given in Fig.4.8, 4.9, 4.10, 4.11

and 4.12.

The mass spectrum of Pramipexole parent ion and product ions were given in

Figure 4.13 and 4.14 and for Quetiapine parent ion and product ions were given in

Figure 4.15 and 4.16. A typical chromatogram obtained from a processed blank

human plasma sample is presented in Figure 4.17 and representative chromatograms

of the lower limit of quantitation, lower quality control, middle quality control, high

quality control and upper limit of quantitation samples were given in Figures 4.18,

4.19, 4.20, 4.21 and 4.22. The calibration samples (CC samples), quality control

samples (QC samples) and plasma sample solutions were injected with the optimised

and validated chromatographic conditions and chromatograms were recorded. The

retention time of Pragabalin and internal standard were 1.0 and 1.1, respectively. The

retention time Pramipexole and internal standard were 1.3 and 1.8, respectively. The

quantification of the chromatogram was performed using peak area ratios (response

factor) of the drug to internal standard. The calibration curves were constructed

routinely during the process of pre-study validation and in-study validation. The

mobile phase used for the assay provided a well-defined separation between the drug,

internal standard and endogenous components. The zero h (pre-dose) samples of all

subjects showed no interference at retention time of both selected drugs and internal

standards. The concentration of the selected drugs present in the plasma samples

were calculated.

5

5

5

97

Fig. 4.3: Mass Spectrum of Pregabalin (Parent Ion)

x102 +ESI MRM :52 (0.0 20 -0.340 m in, 5 sc ans) Frag=8 0.0V (1 60.1 - > …**)

2. Pregabalin_PREGABALIN_26155.1

2

1.

1

0.

052.5 53 53.5 54 54.5 55 55.5 56 56.5 57 57.5

Counts vs. Mass- t o - Charge ( m /z)

Fig. 4.4: Mass Spectrum of Pregabalin (Product Ion)

98

Fig. 4.5: Mass Spectrum of Tramadol (Parent Ion)

Fig. 4.6: Mass Spectrum of Tramadol (Product Ion)

99

Fig. 4.7: Representative chromatogram of processed blank plasma

Fig. 4.8: Typical chromatogram obtained from LLOQ

100

Fig. 4.9: Typical chromatogram obtained from LQC

Fig. 4.10: Typical chromatogram obtained from MQC

101

Fig. 4.11: Typical chromatogram obtained from HQC

Fig. 4.12: Typical chromatogram obtained from ULOQ

102

Fig. 4.13: Mass Spectrum of Pramipexole (Parent Ion)

Fig. 4.14: Mass Spectrum of Pramipexole (Product Ion)

103

Fig. 4.15: Mass Spectrum of Quetiapine (Parent Ion)

Fig. 4.16: Mass Spectrum of Quetiapine (Product Ion)

104

Fig. 4.17: Representative chromatogram of processed blank plasma

Fig. 4.18: Typical chromatogram obtained from LLOQ

105

Fig. 4.19: Typical chromatogram obtained from LQC

Fig. 4.20: Typical chromatogram obtained from MQC

106

Fig. 4.21: Typical chromatogram obtained from HQC

Fig. 4.22: Typical chromatogram obtained from ULOQ

107

4.6 In-vitro and in-vivo correlations for Pregabalin

4.6.1 In-vivo data analysis

Comparative bioavailability studies for immediate and modified release

formulations of Pregabalin were carried out in healthy human subjects. The drug-

plasma levels were measured over 24 hours by validated LCMSMS method. The

plasma concentration of the individual subjects and Pharmacokinetic parameters such

as, Peak plasma concentration (Cmax), Time to peak Concentration (tmax), Area under

the plasma concentration time curve (AUC0-24 and AUC0-∞), elimination rate

constant (keli) and Elimination half-life (t1/2) were calculated and are presented in

Table 4.23 to 4.24. The mean plasma concentration of the immediate and modified

release formulation of Pregabalin is presented in Table 4.25 and the mean

concentration time curve is presented in Fig. 4.23. The mean pharmacokinetic

profiles of immediate and modified release formulation of Pregabalin are presented

in Table 4.26.

The In-transformed values of Cmax, AUC0-t and AUC0-∞, along with the factors

included in this statistical analysis were period, sequence, treatments and subjects.

The factor subject was random and others were fixed. A difference between the

treatments was including 95% confidence interval. The design statement indicates

that the subjects were nested within the sequences.

The statistical parameters for In-transformed values of Cmax, that is the sum of

square, degree of freedom, mean square, F, significance values for immediate and

modified release formulations of Pregabalin, between subjects effects are presented

in Table 4.27. From these values, it is seen that the period, sequence and treatment

effects are non-significant when immediate release formulation was compared with

modified release formulation. However, the significant differences were observed

when immediate release formulation was compared with modified release

formulation. The 95% confidence interval of the difference between the two In-

transformed Cmax values for individual subjects and mean percentage ratio are

presented in Table 4.30. The 95% confidence interval for immediate and modified

release formulations ranges from -0.1306 to -0.0292, while the mean differences for

108

immediate and modified release formulations of Pregabalin was -0.0791. Back-

transformed to regular units, this means that the mean Cmax-0.0791=1.008, while

95% confidence interval for immediate and modified release formulations ranges

from -0.1306= 1.139 to -0.0292=1.089. The mean percentage ratio between

immediate and modified release formulation of Pregabalin was 194.65. The

percentage confidence interval for immediate vs modified release formulations

ranges from 88.50 to 108.04.

The statistical parameters for In-transformed values of AUC0-24, that is the

sum of square, degree of freedom, mean square, F, significance values for immediate

and modified release formulations of Pregabalin, between subjects effects are

presented in Table 4.28. From these values, it is seen that the period, sequence and

treatment effects are non-significant when immediate release formulation was

compared with modified release formulations. However, the significant differences

were observed when immediate release formulation was compared with modified

release formulation. The 95% confidence interval of the difference between the two

In-transformed AUC0-24 values for individual subjects and mean percentage ratio are



immediate and modified release formulations of Pregabalin was -0.0967. Back-

transformed to regular units, this means that the mean AUC0-24 -0.0967= 1.101, while

the 95 % confidence interval for immediate Vs modified release formulations ranges

from -0.1277 = 1.136 to -0.0721 = 1.075. The mean percentage ratio between

immediate and modified release formulation was 151.42. The percentage confidence

interval for immediate vs modified release formulations ranges from 96.32 to 97.64

The statistical parameters for In-transformed values of AUC0-∞, that is the


and modified release formulations of Pregabalin, between subjects effects are





release formulation. The 95 % confidence interval of the difference between the two

109

In-transformed AUC0-∞ values for individual subjects and mean percentage ratio are

presented in Table 4.30. The 95 % confidence interval for immediate and modified


immediate and modified release formulations of Pregabalinwas -0.0951. Back-

transformed to regular units, this means that the mean

AUC0-∞ -0.0951= 1.0998, while the 95 % confidence interval for immediate Vs

modified release formulations ranges from -0.1232 = 1.132 to -0.0665= 1.068. The

mean percentage ratio between immediate and modified release formulation was of

Pregabalin was 146.79. The percentage confidence interval for immediate Vs

modified release formulations ranges from 97.16 to 97.11.


The in-vitro release characteristics of the immediate and modifies release

formulations of Pregabalin was determined. Cumulative percentage drug release at

various time intervals were calculated and are presented in Table 4.31 and 4.32 and

in Fig. 4.24 and 4.25. The similarity factor (f2) was calculated and presented in

Table 4.33.

4.6.3 In-vitro and in-vivo correlations

This section describes in-vivo and in-vitro data analysis, in-vitro and in-vivo

model ‘A’ correlation development and validation for immediate and modified

release formulations.

When dissolution tests were performed at pH 1.2 buffer, pH 4.5 buffer, water

and pH 7.4 buffer at 50 and 75 rpm, the release of the Pregabalin was found to be

almost indistinguishable between the immediate and modified release formulations.

The higher similarity factor (f2) values (more than 50) confirms that these dissolution

mediums are indistinguishable and ensures sameness or equivalence between the two

dissolution profiles and hence not considered for the present study.

The best discrimination was achieved at pH 6.8 buffer at 50 rpm as well as 75

rpm. The (f2) value for pH 6.8 buffer at 50 rpm and 75 rpm were 45.98 and 42.68,

respectively. The associated f2 metric, and f2 value below 50 suggests that the two

110

dissolution profiles are dissimilar and reveals pH 6.8 buffer at 50 and 75 rpm were

more discriminating dissolution mediums and hence selected for IVIVC model

development.

A Level A correlation was developed by a two-stage procedure,

deconvolution followed by comparison of the percent dissolved vs the percent

absorbed data for both immediate and modified release formulations. The in-vitro

and in-vivo correlation plot was constructed using percentage of drug dissolved at

pH 6.8 buffer dissolution media at both 50 and 75 rpm vs the percentage of drug

absorbed. The slope of the best-fit line was examined using linear regression

analysis and coefficient of correlation (r2). The slope and intercept values were

calculated and are presented in Table 4.34 and in Fig. 4.26 and 4.27. The correlation

coefficient (r2) of pH 6.8 buffer and at 50 and 75 rpm was 0.8098 and 0.8130,

respectively for modified release formulation, while 0.8960 and 0.9084, respectively

for immediate release formulation. A good linear regression relationship was thus

observed when the dissolution studies were carried out in pH 6.8 buffer at 75 rpm

and hence this was selected for further analysis.

The dissolution rate constants were determined from percentage drug release

versus the square root of time. The slope of the best-fit line for the semi-log

treatment of this data was taken as the first order rate constant for absorption. Linear

regression analysis was applied to the in-vitro and in- vivo correlation plots and

coefficient of correlation (r2), slope and intercept values were calculated and are

presented in Fig. 4.28 to 4.29. The correlation coefficient (r2) for pH 6.8 buffer at

75 rpm for modified release and immediate release formulation were 0.9251 and

0.9483, respectively. A good linear regression relationship was thus observed using

pH 6.8 buffer as dissolution medium at 75 rpm and hence this was selected at the

dissolution media of choice.

4.6.4 Internal validation


dissolution data and mean in-vivo pharmacokinetics of the immediate and modified

release formulations. The mean in-vitro dissolution rate constants were correlated to

111

the mean absorption rate constants for the modified release formulations. These two

data points, along with the zero–zero intercept were used to calculate the expected

absorption rate constants.

The prediction of plasma concentration was calculated. From this, percentage

prediction errors for Cmax and AUC were calculated and are presented in Table 4.35

and 4.36 and in Fig.4 30 and 4.31. The Cmax prediction errors for both the immediate

and modified release formulations were found to be 2.190 and -12.60, respectively.

The AUC prediction errors for both the immediate and modified release formulations

were found to be 9.39 and -2.76, respectively. These values were very close to the

observed mean values.

4.6.5 External validation

The in-vitro release characteristics of the immediate and modified release

formulations of Pregabalin were determined. Cumulative percentage drug release at

various time intervals and similarity factor (f2) were calculated. When dissolution

test was performed at pH 6.8 buffer at 75 rpm, best discrimination was achieved

between the immediate and modified release formulations of Pregabalin. The

associated f2 metric, and f2 value below 50 suggests that the two dissolution profiles

are dissimilar and reveals pH 6.8 buffer at 75 rpm was discriminating dissolution

medium.

An in-vitro and in-vivo correlation plot was constructed using percentage of

the drug dissolved at pH 6.8 buffer dissolution media at 75 rpm vs the percentage of

drug absorbed. The slope of the best fit line was examined using Linear regression

analysis and the coefficient of determination (r2), slope and intercept values

calculated are presented. The correlation coefficient (r2) value for immediate and

modified release formulations was 0.9084 and 0.813, respectively. A good linear

regression relationship was observed.


Vs the square root of time. The slope of the best fit line for the semi-log treatment of

this data was taken as the first order rate constant for absorption. Linear regression

analysis was applied to the in-vitro and in-vivo correlation plots and the coefficient of

112

correlation (r2), slope and intercept values calculated are presented in Table 4.37. The

correlation coefficients (r2) value for immediate and modified release formulations

was 0.9251 and 0.9483, respectively.

The prediction of plasma concentration for immediate and modified release

formulations of Pregabalin was calculated. From this, percentage prediction errors

for Cmax and AUC were calculated. The Cmax prediction errors for both the immediate

and modified release formulations were found to be 2.190 and -12.60, respectively.

The AUCprediction errors for both the immediate and modified release formulations

were found to be 9.39 and -2.76, respectively. The Cmax and AUC prediction error

was within the specified limit and hence, the IVIVC is considered as validated both

in terms of internal and external validation.

113

113

Table 4.23 Individual plasma concentrations (mcg/ml) and pharmacokinetic parameters for Pregabalin Immediate Release

Formulation

Time A B C D E F G H I J K L

0 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

0.5 693.88 1233.89 1009.43 912.05 1079.76 1167.68 926.91 769.08 998.55 741.19 1247.71 1034.66

1 890.98 1223.04 982.75 1228.39 1169.44 1130.67 880.00 1027.01 962.66 1084.40 1221.97 1056.43

1.5 844.23 1140.27 924.60 1217.09 1102.79 1087.28 864.50 968.67 926.07 1021.00 1105.73 964.13

2 796.75 1068.28 875.72 1102.39 1008.13 1038.79 818.74 922.20 900.59 967.07 1025.43 972.38

3 686.76 958.20 768.81 1039.51 824.13 968.26 757.22 809.55 832.27 848.09 893.08 897.50

4 592.69 816.33 657.19 972.17 722.65 849.06 631.61 678.56 691.43 723.21 721.23 751.43

6 487.84 652.04 515.32 815.22 576.14 687.19 539.41 546.04 543.36 564.57 588.36 638.52

8 365.36 478.97 376.27 684.43 404.46 543.50 401.86 402.49 357.09 411.99 418.13 404.12

12 259.27 304.36 261.99 522.06 333.32 292.18 254.86 263.50 235.35 286.17 236.16 271.07

18 109.93 143.88 140.29 319.82 232.41 161.80 142.59 136.44 141.06 150.65 106.83 140.91

24 0.00 0.00 0.00 71.49 62.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Cmax 890.98 1233.89 1009.43 1228.39 1169.44 1167.68 926.91 1027.01 998.55 1084.40 1247.71 1056.43

Tmax 1.00 0.50 0.50 1.00 1.00 0.50 0.50 1.00 0.50 1.00 0.50 1.00

AUC 0-t 7643.85 9065.68 7338.02 12587.92 9110.02 9307.44 7225.74 7498.71 7326.70 7938.46 7941.69 8156.38

Keli 0.18 0.23 0.21 0.19 0.25 0.22 0.29 0.22 0.22 0.25 0.26 0.22

T-half 4.62 4.76 5.03 6.27 5.92 5.14 5.28 4.83 4.89 5.02 4.00 4.91

AUC0-∞ 7983.32 9652.60 8324.32 13188.42 9593.87 10075.77 7871.93 8043.61 7911.38 8609.06 8216.11 8742.40

114

114

Table 4.23 (continued). Individual plasma concentrations (mcg/ml) and pharmacokinetic parameters for Pregabalin Immediate

Release Formulation

Time M N O P Q R S T U V W X

0 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

0.5 996.73 934.18 1054.32 1101.33 803.33 920.32 1056.98 981.88 618.44 987.43 870.56 714.31

1 1216.98 1097.34 1186.45 1259.43 874.59 926.47 1231.08 967.73 877.82 1041.59 998.78 1040.97

1.5 1324.57 1161.28 1133.55 1227.55 864.16 903.32 1014.38 922.72 848.47 965.44 971.43 1005.37

2 172.30 1086.90 1075.23 1103.03 797.07 888.29 983.37 859.45 811.10 857.05 915.38 956.77

3 1035.28 973.10 953.11 1030.98 712.50 777.12 874.11 751.10 734.47 731.07 837.22 861.49

4 847.05 731.57 829.19 964.90 591.36 665.05 707.54 698.09 635.31 588.00 732.48 766.77

6 668.94 605.85 650.54 759.19 400.86 476.29 438.81 490.01 4395.84 383.22 520.21 618.99

8 522.65 395.34 497.43 593.16 260.74 353.46 275.10 388.36 318.60 241.07 364.74 462.90

12 315.64 292.68 277.53 324.00 123.57 214.90 131.61 240.28 154.30 165.40 215.46 284.25

18 120.33 143.68 144.21 155.98 104.04 104.79 105.61 152.13 89.35 110.25 122.65 158.20

24 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Cmax 1324.57 1161.28 1186.45 1259.43 874.59 926.47 1231.08 981.88 877.82 1041.59 998.78 1040.97

Tmax 1.50 1.50 1.00 1.00 1.00 0.50 1.00 0.50 1.00 1.00 1.00 1.00

AUC 0-t 9772.32 8927.36 9315.37 10455.0 6532.90 7033.67 6720.94 7141.27 6144.71 6063.23 7560.25 8608.18

Keli 0.27 0.19 0.21 0.19 0.26 0.20 0.26 0.24 0.22 0.21 0.22 0.18

T-half 4.69 5.17 5.30 5.40 4.53 4.89 4.30 5.44 4.37 4.61 5.07 5.83

AUC0-∞ 10268.6 10453.5 10050.0 11290.8 7175.97 7450.12 7089.49 7617.33 6425.08 6488.09 8114.36 9531.01

115

115

Table 4.24 Individual Plasma Concentrations (Mcg/Ml) and Pharmacokinetic Parameters for Pregabalin Modified Release

Formulation


0 0 0 0 0 0 0 0 0 0 0 0 0

0.5 88.43 78.1 78.98 0 0 0 0 0 0 0 0 0

1 259.77 174.08 173.79 263.77 217.43 207.33 252.08 240.66 284.556 187.35 184.88 119.55

1.5 357.83 296 251.51 268.43 314.87 296.33 329.07 417.54 384.85 366 216.56 169.98

2 478.79 376.84 362.26 353.47 402.32 360.11 510.23 554.67 476.98 456 383.97 359.74

3 623.97 463.29 438.55 549.11 673.05 583.77 549.97 486.36 673.07 585.06 615.67 583.07

4 547.41 518.11 363.98 463.09 555.95 514.74 524.98 452.39 614.07 487.46 535.93 514.09

6 489.59 449.89 333.77 435.07 526.79 485.66 459.92 355.01 485.05 376.38 475.09 447.23

8 450.07 364.83 258.1 387.54 392.05 389.89 365.71 295.6 391.9 309.17 389.98 378.91

12 231.69 216.78 226.8 238.95 226.44 225.96 247.43 245.67 233.99 245.97 233.58 241.28

18 156.15 152.57 163.88 156.7 153.94 144.96 157.95 137.71 160.86 135.27 153.24 156.38

24 84.97 88.58 86.89 85.86 81.99 83.38 91.97 70.43 83.52 68.09 85.99 86.57

Cmax 623.97 518.11 438.55 549.11 673.05 583.77 549.97 554.67 673.07 585.06 615.67 583.07

Tmax 3 4 3 3 3 3 3 2 3 3 3 3

AUC 0-t 5999.59 5219.26 4493.9 5373.99 5772.16 5442.23 5734.17 5212.13 5991.84 5449.93 5547.44 5378.11

Keli 0.14 0.11 0.06 0.2 0.11 0.18 0.11 0.17 0.12 0.13 0.11 0.11

T-half 6.12 6.62 7.42 6.5 5.76 6.54 6.73 7.15 6.21 6.5 6.03 6.44

AUC0-∞ 6530.8 5807.79 5216.36 5956.31 6317.07 5961.82 6361.18 5873.7 6500.2 6034.98 6097.42 5952.02

116

116

Table 4.24 (continued) Individual Plasma Concentrations (Mcg/Ml) and Pharmacokinetic Parameters for Pregabalin Modified

Release Product


0 0 0 0 0 0 0 0 0 0 0 0 0

0.5 0 145.09 90 90.44 0 0 0 0 0 99.06 0 98.1

1 162.89 273.67 185.88 167.88 196.98 174.77 117.07 231.44 175 173.9 206.96 174.87

1.5 392.59 344.41 364.48 389.36 389.25 261.23 250.91 327.11 298.91 348.53 287.99 376.27

2 426.38 378.97 410.03 565.74 423.05 395 522.53 394.99 415.94 475.49 400.43 414.79

3 583.68 441.77 540.77 519.7 477.67 440.32 626.95 531.7 500.04 531.14 508.23 468.75

4 545.97 500.23 491.07 481.23 394.05 505.89 554.07 448.05 444.08 464.07 453.42 509.08

6 424.96 498.38 351.64 371.78 413.53 445.05 494.99 374.37 381.97 354.51 380.55 407.37

8 311.39 377.65 279.68 349.65 252.98 387.79 414.56 299.26 334.48 339.65 314.2 334.7

12 245.81 247.81 235.97 226.89 206.58 248.56 220.97 246.96 247.44 231.78 240.81 224.99

18 147.28 143.32 142.71 133.04 137.99 162.24 155.28 146.11 135.51 140.38 132.65 126.86

24 69.11 64.56 67.22 71.11 67.43 86.99 90.14 67.76 67.67 70.48 67.85 59.71

Cmax 583.68 500.23 540.77 565.74 477.67 505.89 626.95 531.7 500.04 531.14 508.23 509.08

Tmax 3 4 3 2 3 4 3 3 3 3 3 4

AUC 0-t 5543.51 5645.58 5107.37 5350.42 4767.48 5418.24 5748.3 5176.75 5174.92 5257.47 5088.56 5174.36

Keli 0.15 0.12 0.13 0.1 0.14 0.21 0.11 0.13 0.1 0.14 0.1 0.15

T-half 6.03 6.53 6.89 6.21 7.21 7.21 6.11 7.83 6.91 7.11 7.21 7.03

AUC0-∞ 6142.33 6147.07 5715.09 5992.51 5402.92 5995.77 6337.85 5786.52 5788.68 5905.79 5699.04 5649.71

Table 4.25 Mean plasma concentrations (mcg/ml) for Pregabalin

Time

(h)

Immediate Release

Formulation

Modified Release

formulation

Mean S.D Mean S.D

0.000.00 0.00 0.00 0.00

0.50952.28 166.10 32.01 47.70

1.001065.71 129.36 200.27 44.85

1.501021.19 132.18 320.83 62.63

2.00916.77 187.23 429.11 62.23

3.00856.46 107.22 541.49 70.51

4.00731.87 104.87 495.14 54.72

6.00731.78 787.42 425.77 56.35

8.00413.43 102.95 348.74 50.70

12.00260.83 80.18 234.96 11.40

18.00143.24 47.49 147.21 10.64

24.005.56 18.90 77.01 10.02

117

118

118

Fig.4.23: Mean Concentration Time Curve for Pregabalin

119

119

Table 4.26 Pharmacokinetic Profile of Pregabalin

Parameters Immediate release product Modified Release product

Mean S.D Mean S.D

Cmax 1081.07 135.50 555.38 58.96

Tmax 0.88 0.30 3.08 0.50

AUC 0-t 8142.33 1496.59 5377.82 350.39

K eli 0.26 0.03 0.13 0.03

Tmax 5.01 0.52 6.68 0.52

AUC 0-t 8756.98 1603.36 5965.54 317.87

120

120

Table 4.27 Statistical data for Pregabalin Immediate Release Vs Modified Release Formulation

Dependent variable: Cmax Tests of Between-Subjects Effect

Source Type III

sum of

squares

df Mean

square

F Sig. Partial Eta

squared

Noncent.

parameter

Observed

power a

Intercept Hypothesis

Error

90.564

.332

1

29.675

90.564

9.567E-03b

12343.706 .000 .996 12343.706 1.000

SEQ Hypothesis

Error

3.453E-05

.180

1

22

2.667E-05

8.421E-3C

.004 .956 .000 .004 .121

PERIOD Hypothesis

Error

.000

.

0

.

.

.d

. . . . .

TREATMENT Hypothesis

Error

.000

.

0

.

.

.d

. . . . .

SUBJECT Hypothesis

Error

.743

.231

23

22

1.754E-02

8.421E-03c

2.167 .043 .743 51.656 .977

a. Computed using alpha = .1

b. 5.266E-02 MS(SUBJECT) +.947 MS (Error)

c. MS (Error)

d. Cannot compute the appropriate error term using Satterthwaite’s method

121

121


Dependent variable: AUC 0-t Tests of Between-Subjects Effect

Source Type III

sum of

squares

df Mean

square

F Sig. Partial Eta

squared

Noncent.

parameter

Observed

power a


Error

191.665

9.545E-02

1

27.067

191.665

3.543E-03b

56434.443 .000 .966 56434.443 1.000

SEQ Hypothesis

Error

7.833E-04

7.993E-02

1

22

7.833E-04

3.665-03C

.334 .832 .12 .334 .144

PERIOD Hypothesis

Error

.000

.

0

.

.

.d

. . . . .


Error

.000

.

0

.

.

.d

. . . . .

SUBJECT Hypothesis

Error

.232

7.993E-02

23

22

7.332E-03

3.872E-03c

2.776 .054 .675 56.332 .997



c. MS (Error)


122

122


Dependent variable: AUC 0-inf Tests of Between-Subjects Effect

Source Type III

sum of

squares

df Mean

square

F Sig. Partial Eta

squared

Noncent.

parameter

Observed

power a


Error

186.443

7.554E-02

1

27.998

186.443

2.554E-03b

69656.098 .000 1.000 69656.098 1.000

SEQ Hypothesis

Error

3.867E-04

5.976E-02

1

22

3.867E-04

2.997E-03C

.106 .775 .006 .106 .132

PERIOD Hypothesis

Error

.000

.

0

.

.

.d

. . . . .


Error

.000

.

0

.

.

.d

. . . . .

SUBJECT Hypothesis

Error

.143

5.987E-02

23

22

5.661E-03

2.997E-03C

2.558 .048 .776 59.332 .988



c. MS (Error)


123

123

Table 4.30 Paired Sample Test for Pregabalin

Paired Differences

t df Sig. (2-

tailed)

Mean

Std.

Deviation

Std.

Error

Mean

95% Confidence

Interval of the

Difference

Lower Upper

Pair 1 C max -0.0791 .12434 .02667 -.1306 -.0292 -3.553 23 0.005

Pair 2 AUC 0-t -.0967 0.0734 .01765 -.1277 -.0721 -4.556 23 .000

Pair 3 AUC 0-inf -.0951 .07098 .01332 -.1232 -.0665 -6.556 23 .000

124

124

Table 4.31 Cumulative percentage dissolved at 50 rpm for Pregabalin formulations

Time

(h)

Square

root of

time

(h)

pH 1.2 buffer pH 4.5 buffer pH 6.8 buffer Water pH 7.4 buffer

Formulation Formulation Formulation Formulation Formulation

Immediate Modified Immediate Modified Immediate Modified Immediate Modified Immediate Modified

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

0.50 0.71 25.32 0.00 26.57 0.00 16.32 7.56 27.94 11.86 16.93 10.98

1.00 1.00 38.48 36.87 38.82 32.35 35.56 15.99 32.37 30.22 40.21 19.09

1.50 1.22 40.45 42.83 49.21 43.92 58.96 32.97 40.67 38.94 52.06 32.19

2.00 1.41 48.30 46.06 52.13 44.67 84.18 41.90 48.03 42.38 58.01 36.90

3.00 1.73 55.87 50.06 58.77 55.55 97.44 62.08 56.85 51.27 62.09 42.32

4.00 2.00 65.16 54.96 64.69 64.43 100.02 75.03 69.00 58.88 74.32 49.76

6.00 2.45 88.32 64.76 70.44 66.75 100.87 84.02 100.12 87.32 82.19 63.99

8.00 2.83 90.21 74.52 85.94 74.62 101.01 95.21 100.44 100.09 100.67 73.07

12.00 3.46 100.01 96.75 99.53 90.22 101.86 99.02 100.59 100.15 101.98 101.09

18.00 4.24 100.37 99.53 100.61 100.01 102.18 99.87 100.98 101.67 102.44 102.98

24.00 4.90 100.57 99.83 100.11 102.34 102.39 99.99 101.43 101.43 102.98 103.00

125

125

CU

MU

LATIV

E

RE

LEA

SE (

%)

100

80

60

40

20

00 5 10 TIME

(HOURS)

15 20 25

Fig. 4.24: Cumulative Pregabalin Release Vs Time Profile for Immediate and

Modified Release Formulations at 50 RPM

126

126

Table 4.32 Cumulative percentage dissolved at 75 rpm for Pregabalin formulations

Time

(h)

Square

root of

time

(h)



Immediate Modified Immediate Modified Immediate Modified Immediate Modified Immediate Modified

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

0.50 0.71 29.11 0.00 32.54 0.00 17.99 10.32 28.63 20.32 17.21 15.43

1.00 1.00 39.64 40.32 42.83 34.99 36.78 22.64 35.92 36.21 43.28 25.32

1.50 1.22 43.01 47.9 50.84 45.89 64.89 40.21 40.67 40.21 54.90 45.22

2.00 1.41 53.72 50.44 61.66 55.55 75.66 45.89 48.03 47.29 62.67 53.20

3.00 1.73 64.67 67.93 67.93 64.90 97.32 61.21 56.85 52.64 67.00 59.12

4.00 2.00 75.64 83.54 70.52 74.90 100.02 71.64 78.21 74.32 79.32 62.00

6.00 2.45 99.56 99.32 84.83 92.67 100.97 86.83 99.21 88.32 96.33 70.53

8.00 2.83 100.42 99.54 99.11 100.03 101.01 99.43 99.29 98.32 99.32 99.43

12.00 3.46 100.72 100.43 100.61 100.43 100.86 99.67 99.45 98.64 99.78 100.05

18.00 4.24 100.81 101.23 100.11 101.95 100.18 100.01 99.59 99.43 100.32 100.56

24.00 4.90 100.99 101.89 100.50 102.64 102.09 100.23 100.19 100.02 101.21 100.94

127

127

CU

MU

LATIV

E

RELE

AS

E (

%)

C H A R TT I T L E

100

80

60

40

20

00 5 10 15 20 25

TIME(HOURS)



128

128

Table 4.33 Similarity factors for Pregabalin modified release dosage forms in

Various dissolution condition

S.No pH Condition Formulation Similarity factor (f2)

1 pH 1.2 buffer 50 rpm IR Vs MR 83.01






7 Distilled water 50 rpm IR Vs MR 73.64

8 Distilled water 75 rpm IR Vs MR 77.45



129

129

Table 4.34 IVIVC model regression of % absorbed vs. % dissolved for Pregabalin

Formulation using pH 6.8 at 50 and 75 rpm

Time

(Hours)

Percentage dissolved

50 RPM


75 RPM

Percentage absorbed

Immediate Modified Immediate Modified Immediate Modified

0.00 0.00 0.00 0.00 0.00 0 0

0.50 16.32 7.56 17.99 10.32 32.65 3.75

1.00 35.56 15.99 36.78 22.64 62.38 25.43

1.50 58.96 32.97 64.89 40.21 78.10 48.54

2.00 84.18 41.90 75.66 45.89 95.32 70.54

3.00 97.44 62.08 97.32 61.21 97.43 93.45

4.00 100.02 75.03 100.02 71.64 98.54 96.44

6.00 100.87 84.02 100.97 86.83 99.54 99.43

8.00 101.01 95.21 101.01 99.43 100.21 99.54

12.00 101.86 99.00 100.86 99.67 100.45 99.96

18.00 102.18 99.87 100.18 100.01 101.43 100.49

24.00 102.39 99.99 102.09 100.23 101.45 100.54

130

100

90

80

70

60

50

40

30

20

10

0

0 20 40 60 80 100

Fig. 4.26: IVIVC model Linear Regression Plot of % Absorbed Vs % Dissolved

for Immediate and Modified Release Pregabalin Formulations using pH 6.8

Buffer at 50 RPM

Fig.4.27: IVIVC model Linear Regression Plot of % Absorbed Vs % Dissolved

for Immediate and Modified Release Pregabalin Formulations using pH 6.8

Buffer at 75 RPM

100

80

60

4020

0 y = 19.708x + 32.195

R² = 0.619

y = 23.123x +11.504R² =

0.8364

Fig. 4.28: Cumulative Pregabalin Release Vs Square Root of Time Profile for

Immediate and Modified Release Pregabalin Formulations using pH 6.8 Buffer

at 50 RPM

100

80

60

4020

y = 19.708x + 32.195

0 R² = 0.619

y = 23.123x +11.504R² =

0.8364

Fig. 4.29: Cumulative Pregabalin Release Vs Square Root of Time Profile for

Immediate and Modified Release Pregabalin Formulations using pH 6.8 Buffer

at 75 RPM

Table 4.35 Observed and IVIVC model predicted Cmax and AUC values for

Pregabalin

Time

(Hours)

Immediate Modified

Fraction

observed

Fraction

predicted

Fraction

observed

Fraction

predicted

0.00 0.00 0.00 0.00 0

0.50 952.28 768.45 32.01 16.89

1.00 1065.71 999.87 200.27 83.54

1.50 1021.19 1089.56 320.83 220.67

2.00 916.77 1000.22 429.11 326.84

3.00 856.46 934.39 541.49 480.89

4.00 731.87 890.43 495.14 463.94

6.00 731.78 700.59 425.77 375.47

8.00 413.43 563.32 348.74 269.05

12.00 260.83 308.90 234.96 132.98

18.00 143.24 178.32 147.21 26.97

24.00 5.56 32.01 77.01 13.98

Cmax 1065.71 1089.56 541.49 480.89

AUC 9453.99 10433.32 5995.34 5834.06

Table 4.36 Prediction errors (%) associated with Cmax and AUC for Pregabalin

Formulation Cmax AUC

Immediate 2.19 9.39

Modified -12.60 -2.76

Average -5.21 3.31

3.5

3

2.5

2

1.5

1

0.5

00 5 10 15 20 25

Fraction observed Fraction predicted

Fig. 4.30 Observed and Predicted Pregabalin Plasma Concentration for the

Immediate Release Pregabalin Formulations using IVIVC Model

3.5

3

2.5

2

1.5

1

0.5

00 5 10 15 20 25


Fig. 4.31 Observed and Predicted Pregabalin Plasma Concentration for the

Modified Release Pregabalin Formulations using IVIVC Model

Table 4.37 IVIVC model linear regression plots of % absorbed vs % dissolved

for Pregabalin tablets using pH 6.8, at 75 rpm

Time

(Hours)

Percentage dissolved (pH 6.8) Percentage absorbed

Immediate Modified Immediate Modified

0.00 0.00 0.00 0 0

0.50 17.99 10.32 32.65 3.75

1.00 36.78 22.64 62.38 25.43

1.50 64.89 40.21 78.10 48.54

2.00 75.66 45.89 95.32 70.54

3.00 97.32 61.21 97.43 93.45

4.00 100.02 71.64 98.54 96.44

6.00 100.97 86.83 99.54 99.43

8.00 101.01 99.43 100.21 99.54

12.00 100.86 99.67 100.45 99.96

18.00 100.18 100.01 101.43 100.49

24.00 102.09 100.23 101.45 100.54

4.7 In-vitro and in-vivo correlations for Pramipexole


Comparative bioavailability studies for immediate and modified release

formulations of Pramipexole were carried out in healthy human subjects. The drug-

plasma levels were measured over 24 hours by validated LCMSMS method. The

plasma concentration of the individual subjects and Pharmacokinetic parameters such

as, Peak plasma concentration (Cmax), Time to peak Concentration (tmax), Area under

the plasma concentration time curve (AUC0-24 and AUC0-∞), elimination rate

constant (keli) and Elimination half-life (t1/2) were calculated and are presented in

Table 4.38 to 4.39. The mean plasma concentration of the immediate and modified

release formulation of Pramipexole is presented in Table 4.40. The mean

concentration time curve is presented in Fig.4.32. The mean pharmacokinetic profiles

of immediate and modified release formulation of Pramipexole are presented in

Table 4.41.

The In-transformed values of Cmax, AUC0-t and AUC0-∞ ,along with the factors

included in this statistical analysis were period, sequence, treatments and subjects.

The factor subject was random and others were fixed. A difference between the

treatments was including 95% confidence interval. The design statement indicates

that the subjects were nested within the sequences.

The statistical parameters for In-transformed values of Cmax, that is the sum of

square, degree of freedom, mean square, F, significance values for immediate and

modified release formulations of Pramipexole, between subject effects are presented

in Table 4.42. From these values, it is seen that the period, sequence and treatment

effects are non-significant when immediate release formulation was compared with

modified release formulation. However, the significant differences were observed

when immediate release formulation was compared with modified release

formulation. The 95% confidence interval of the difference between the two In-

transformed Cmax values for individual subjects and mean percentage ratio are


release formulations ranges from -0.097 to 0.085, while the mean differences for

immediate and modified release formulations of Pramipexole was -0.005. Back-

transformed to regular units, this means that the mean Cmax 0.005= 1.0051, while

95% confidence interval for immediate and modified release formulations ranges

from 0.097= 1.102 to 0.085=1.089. The mean percentage ratio between immediate

and modified release formulation of Pramipexole was 73.94. The percentage

confidence interval for immediate vs modified release formulations ranges from

108.64 to 109.64.

The statistical parameters for In-transformed values of AUC0-24, that is the


and modified release formulations of Pramipexole, between subject effects are






In-transformed AUC0-24 values for individual subjects and mean percentage ratio are




transformed to regular units, this means that the mean AUC0-24 -0.092 = 1.097, while

the 95 % confidence interval for immediate vs modified release formulations ranges

from -0.160=1.174 to -0.024= 1.025. The mean percentage ratio between immediate

and modified release formulation was 57.84. The percentage confidence interval for

immediate vs modified release formulations ranges from 93.43 to 107.01.

The statistical parameters for In-transformed values of AUC0-∞, that is the


and modified release formulations of Pramipexole, between subject effects are






137

In-transformed AUC0-∞ values for individual subjects and mean percentage ratio are




transformed to regular units, this means that the mean AUC0-∞ -0.086= 1.090, while

the 95 % confidence interval for immediate vs modified release formulations ranges

from -0.153= 1.166 to -0.028= 1.029. The mean percentage ratio between immediate

and modified release formulation was of Pramipexole was 56.63. The percentage

confidence interval for immediate vs modified release formulations ranges from

94.40 to 106.97.

4.7.2 In-vitro data analysis

The in-vitro release characteristics of the immediate and modifies release

formulations of Pramipexole was determined. Cumulative percentage drug release at

various time intervals were calculated and are presented in Table 4.46 and 4.47 and

in Fig. 4.33 and4.34. The similarity factor (f2) was calculated and presented in Table

4.48.

4.7.3 In-vitro and in-vivo correlations

This section describes in-vivo and in-vitro data analysis, in-vitro and in-vivo

model ‘A’ correlation development and validation for immediate and modified

release formulations. When dissolution tests were performed at pH 6.8 buffer, pH 7.4

buffer and water at 50 and 75 rpm, the release of the Pramipexole was found to be

almost indistinguishable between the immediate and modified release formulations.

The higher similarity factor (f2) values (more than 50) confirms that these dissolution

mediums are indistinguishable and ensures sameness or equivalence between the two

dissolution profiles and hence not considered for the present study.

The best discrimination was achieved at pH 1.2 buffer and pH 4.5 buffer at

50 rpm as well as 75 rpm. The (f2) value for pH 1.2 buffer and pH 4.5 buffer 50 rpm

was 45.87 and 43.76, respectively, whereas at 75 rpm the (f2) value 47.34 and 42.91,

respectively. The associated f2 metric, and f2 value below 50 suggests that the two

dissolution profiles are dissimilar and reveals pH 1.2 buffer and pH 4.5 buffer at 50

138

ad 75 rpm were more discriminating dissolution mediums and hence selected for

IVIVC model development.

A Level A correlation was developed by a two-stage procedure,

deconvolution followed by comparison of the percent dissolved Vs the percent

absorbed data for both immediate and modified release formulations. The in-vitro

and in-vivo correlation plot was constructed using percentage of drug dissolved at pH

1.2 buffer and pH 4.5 buffer dissolution media at both 50 and 75 rpm Vs the

percentage of drug absorbed. The slope of the best-fit line was examined using

linear regression analysis and coefficient of correlation (r2). The slope and intercept

values were calculated and are presented in Table 4.49 and 4.50 and in Fig. 4.34 to

4.37. The correlation coefficient (r2) of pH 1.2 buffer and pH 4.5 buffer at 50 rpm

was 0.9397 and 0.8473, respectively for modified release formulation, while for pH

1.2 buffer and pH 4.5 buffer at 50 rpm was 0.8473 and 0.7826, respectively for

immediate release formulation. The correlation coefficient (r2) of pH 1.2 buffer and

pH 4.5 buffer at 75 rpm was 0.9316 and 0.8539, respectively for modified release

formulation, while for pH 1.2 buffer and pH 4.5 buffer at 75 rpm was 0.913 and

0.8945, respectively for immediate release formulation. A good linear regression

relationship was thus observed when the dissolution studies were carried out in pH

1.2 buffer at 50 and 75 rpm and hence this was selected for further analysis.


vs the square root of time. The slope of the best-fit line for the semi-log treatment of


analysis was applied to the in-vitro and in- vivo correlation plots and coefficient of

correlation (r2), slope and intercept values were calculated. The correlation

coefficient (r2) for pH 1.2 buffer at 50 rpm for modified release and immediate

release formulation were 0.9827 and 0.9542, respectively, while at 75 rpm rpm for

modified release and immediate release formulation were 0.9914 and 0.9815,

respectively. A good linear regression relationship was thus observed using pH 1.2

buffer as dissolution medium at 75 rpm and hence this was selected at the dissolution

media of choice.

139

4.7.4 Internal validation


dissolution data and mean in-vivo pharmacokinetics of the immediate and modified

release formulations. The mean in-vitro dissolution rate constants were correlated to

the mean absorption rate constants for the modified release formulations. These two

data points, along with the zero –zero intercept were used to calculate the expected

absorption rate constants. The prediction of plasma concentration was calculated.

From this, percentage prediction errors for Cmax and AUC were calculated and are

presented in Tables 4.51 and in Fig. 4.38 and 4.39. The Cmax prediction errors for

both the immediate and modified release formulations were found to be -2.724 and

1.205, respectively. The AUCprediction errors for both the immediate and modified

release formulations were found to be -0.610 and 2.252, respectively. These values

were very close to the observed mean values.

4.7.5 External validation

The in-vitro release characteristics of the immediate and modified release

formulations of Pramipexole were determined. Cumulative percentage drug release

at various time intervals were calculated. The similarity factor (f2) was calculated.

When dissolution test was performed at pH 1.2 buffer at 75 rpm, best discrimination

was achieved between the immediate and modified release formulations of

Pramipexole. The associated f2 metric, and f2 value below 50 suggests that the two

dissolution profiles are dissimilar and reveals pH 1.2 buffer at 75 rpm was

discriminating dissolution medium.

An in-vitro and in-vivo correlation plot was constructed using percentage of

the drug dissolved at pH 1.2 buffer dissolution media at 75 rpm vs the percentage of

drug absorbed. The slope of the best fit line was examined using Linear regression

analysis and the coefficient of determination (r2), slope and intercept values

calculated. The correlation coefficient (r2) value was 0.7843. A good linear

regression relationship was observed.


vs the square root of time. The slope of the best fit line for the semi-log treatment of

140


analysis was applied to the in-vitro and in-vivo correlation plots and the coefficient of

correlation (r2), slope and intercept values calculated. The correlation coefficients (r2)

value was 0.7439.

The prediction of plasma concentration for immediate and modified release

formulations of Pramipexole was calculated. From this, percentage prediction errors

for Cmax and AUC were calculated. The Cmax prediction error for the immediate and

modified release formulations of Pramipexole was found to be -2.724 and 1.205,

respectively. These values were very close to the observed mean values. The AUC

prediction error was -0.610 and 2.252 for immediate and modified release

formulations of Pramipexole, respectively and is presented in Table 4.52. The Cmax

and AUC prediction error was within the specified limit and hence, the IVIVC is

considered as validated both in terms of internal and external validation.

141

141

Table 4.38 Individual plasma concentrations (mcg/ml) and pharmacokinetic parameters for Pramipexole Immediate Release

Formulation


0 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

0.5 0.721 0.357 1.643 1.734 0.265 1.924 1.231 1.238 1.488 1.430 0.118 1.501

1 0.985 0.849 3.352 2.318 0.869 2.370 1.435 2.123 2.674 2.283 2.601 2.409

1.5 1.586 1.380 3.478 2.366 2.528 2.037 1.847 3.680 2.355 2.373 2.375 3.657

2 1.615 2.462 2.898 2.445 1.970 1.722 1.971 2.539 2.248 2.473 2.026 3.390

3 1.357 1.634 2.130 2.063 1.830 1.317 1.428 1.726 1.590 1.495 1.537 2.201

4 1.213 1.587 1.678 1.350 1.528 1.141 1.134 1.419 1.204 1.229 1.256 1.626

6 0.472 0.733 1.055 0.877 1.157 0.859 0.731 0.958 0.917 0.866 0.877 1.108

8 0.312 0.305 0.698 0.645 0.944 0.710 0.583 0.759 0.701 0.608 0.553 0.717

12 0.148 0.268 0.286 0.582 0.758 0.382 0.301 0.442 0.395 0.32 0.328 0.347

18 0.122 0.083 0.088 0.111 0.317 0.076 0.170 0.239 0.198 0.079 0.146 0.127

24 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

Cmax 1.615 2.462 3.478 2.445 2.528 2.370 1.971 3.680 2.674 2.473 2.601 3.390

Tmax 2 2 1.5 2 1.5 1 2 1.5 1 2 1 1.5

AUC 0-t 10.452 11.732 18.008 16.782 18.532 14.672 12.021 17.211 16.043 15.126 13.543 17.513

Keli 0.163 0.231 0.223 0.178 0.249 0.195 0.183 0.162 0.134 0.221 0.173 0.243

T-half 4.275 4.159 3.105 4.956 4.298 4.674 5.211 5.709 5.744 4.674 5.217 4.978

AUC0-∞ 10.854 12.453 18.453 16.976 19.564 15.001 13.229 17.924 16.532 15.453 15.832 17.453

142

142

Table 4.38 (continued) Individual plasma concentrations (mcg/ml) and pharmacokinetic parameters for Pramipexole

Immediate Release Formulation


0.0 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

0.5 0.521 0.854 1.134 1.018 0.058 0.387 1.629 1.386 1.837 0.411 0.828 0.620

1 1.908 1.376 1.863 1.890 0.492 1.767 3.705 2.548 2.170 1.065 1.694 2.482

1.5 1.971 1.432 1.906 1.926 0.521 1.789 3.720 2.573 2.128 1.093 1.672 2.532

2 2.100 2.678 3.617 2.204 1.837 2.926 5.449 3.814 2.100 1.295 2.637 3.297

3 1.816 1.712 2.320 2.208 1.779 2.754 2.278 3.348 2.049 1.242 1.848 1.783

4 1.231 0.846 1.148 0.878 1.272 1.390 0.982 1.489 0.878 0.832 0.897 0.827

6 1.231 0.846 1.148 0.878 1.272 1.390 0.982 1.489 0.878 0.832 0.897 0.827

8 1.127 0.601 0.820 0.589 0.893 0.729 0.578 0.915 0.595 0.601 0.714 0.643

12 0.806 0.345 0.193 0.331 0.523 0.533 0.464 0.553 0.307 0.332 0.401 0.380

18 0.099 0.095 0.142 0.111 0.212 0.123 0.078 0.193 0.191 0.129 0.175 0.093

24 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

Cmax 2.100 2.678 3.617 2.204 1.837 2.926 5.449 3.814 2.128 1.295 2.637 3.297

Tmax 1.5 2 2 1.5 1.5 2 2 2 1.5 2 2 1.5

AUC 0-t 20.439 14.045 18.901 15.554 17.453 20.991 21.323 19.564 16.003 12.655 15.563 17.444

Keli 0.228 0.163 0.223 0.167 0.156 0.148 0.224 0.184 0.221 0.19 0.185 0.178

T-half 4.967 3.519 4.158 4.554 5.887 4.668 3.527 4.921 4.334 5.322 4.894 4.807

AUC0-∞ 21.047 14.564 19.328 16.001 17.855 20.964 21.457 20.487 16.531 13.275 16.445 18.209

143

143

Table 4.39 Individual plasma concentrations (mcg/ml) and pharmacokinetic parameters for Pramipexole Modified Release

Formulation


0 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

0.5 0.033 0.272 0.062 0.337 0.155 0.741 0.360 0.268 0.080 0.198 0.179 0.089

1 0.137 0.546 0.209 0.405 0.315 0.985 0.712 0.490 0.138 0.407 0.301 0.175

1.5 0.392 1.208 0.410 0.722 0.996 2.268 1.411 1.414 0.249 0.478 0.556 0.225

2 0.645 2.006 1.082 1.185 1.526 4.507 1.730 2.578 0.371 0.901 1.187 0.303

3 2.081 3.108 2.612 2.484 2.175 3.038 2.129 3.802 0.816 1.505 2.457 1.260

4 3.202 4.334 3.466 3.608 3.074 2.083 3.148 3.979 2.011 2.031 3.872 1.892

6 2.498 1.781 1.968 1.772 2.017 1.012 1.545 2.036 2.251 3.867 1.533 3.624

8 1.978 1.559 1.784 1.521 1.773 0.749 1.337 1.784 2.084 3.269 1.363 3.273

12 1.158 0.975 0.872 1.008 0.941 0.484 0.909 1.072 1.263 1.239 0.856 1.552

18 0.589 0.420 0.466 0.369 0.364 0.162 0.425 0.393 0.424 0.449 0.448 0.450

24 0.257 0.313 0.245 0.350 0.277 0.227 0.245 0.238 0.204 0.332 0.357 0.254

Cmax 3.202 4.334 3.466 3.608 3.074 4.507 3.148 3.979 2.251 3.867 3.872 3.624

Tmax 4 4 4 4 4 2 4 4 6 6 4 6

AUC 0-t 30.776 31.821 23.113 25.956 27.121 20.810 24.896 31.098 27.113 33.901 26.278 33.987

Keli 0.130 0.129 0.139 0.123 0.132 0.145 0.126 0.153 0.164 0.157 0.115 0.178

T-half 5.674 5.394 5.041 5.559 5.461 4.824 5.670 4.384 4.108 4.369 6.023 3.700

AUC0-∞ 31.352 31.326 28.197 28.932 28.242 21.737 26.377 32.447 26.107 35.613 28.140 34.592

144

144

Table 4.39 (continued) Individual plasma concentrations (mcg/ml) and pharmacokinetic parameters for Pramipexole modified

release reference product


0.0 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

0.5 0.159 0.023 0.151 0.015 0.011 0.095 0.019 0.032 0.170 0.122 0.119 0.075

1 0.261 0.149 0.247 0.139 0.104 0.224 0.104 0.107 0.230 0.239 0.178 0.168

1.5 0.309 0.371 0.681 0.394 0.168 0.330 0.144 0.615 0.388 0.416 0.362 0.239

2 0.524 0.764 0.982 0.631 0.397 0.581 0.282 0.994 0.760 0.756 0.963 0.299

3 1.381 1.450 1.719 1.670 1.340 1.507 1.042 2.075 1.453 1.559 1.710 1.097

4 2.713 1.646 2.624 3.032 2.583 1.796 1.522 2.760 1.645 2.125 2.534 1.587

6 1.916 2.986 2.143 5.232 4.529 4.456 4.436 1.225 4.470 4.930 2.084 4.198

8 1.688 1.990 1.971 2.664 3.442 3.336 2.167 1.773 2.010 2.375 1.754 3.631

12 1.287 1.044 1.296 1.392 1.385 1.201 0.990 1.105 1.290 1.157 1.165 1.722

18 0.392 0.421 0.439 0.536 0.474 0.593 0.417 0.437 0.518 0.458 0.553 0.682

24 0.216 0.186 0.253 0.213 0.217 0.259 0.144 0.185 0.209 0.234 0.183 0.269

Cmax 2.713 2.986 2.624 5.232 4.529 4.456 4.436 2.760 4.470 4.930 2.534 4.198

Tmax 4 6 4 6 6 6 6 4 6 6 4 6

AUC 0-t 23.339 24.268 26.526 25.839 35.233 31.998 26.358 25.047 29.556 31.267 25.461 35.173

Keli 0.148 0.143 0.484 0.133 0.213 0.215 0.162 0.143 0.083 0.133 0.288 0.386

T-half 4.897 4.147 5.691 3.933 3.963 3.850 3.569 4.780 4.164 3.970 5.395 4.220

AUC0-∞ 24.375 25.289 28.204 36.974 36.400 32.901 27.023 26.102 30.731 32.535 26.723 36.294

Table 4.40 Plasma concentrations (mcg/ml) of Pramipexole

Time

(h)

Immediate Release

Formulation

Modified Release

Formulation

Mean S.D Mean S.D

0.00 0.000 0.000 0.000 0.000

0.50 1.014 0.578 0.157 0.159

1.00 1.968 0.788 0.290 0.213

1.50 2.205 0.814 0.614 0.507

2.00 2.571 0.882 1.081 0.924

3.00 1.894 0.480 1.895 0.729

4.00 1.210 0.266 2.636 0.826

6.00 0.970 0.227 2.855 1.324

8.00 0.681 0.181 2.136 0.755

12.00 0.405 0.157 1.140 0.254

18.00 0.142 0.060 0.453 0.099

24.00 0.000 0.000 0.244 0.053

145

146

146

Axis

Tit

le

Axis

Tit

le

3

2.5

2

1.5

1

0.5

0

AxisTitle

Immediate Release Formulation Modifed Release Formulation

Fig 4.32: Mean Concentration Time Curve for Pramipexole

147

147

Table 4.41 Pharmacokinetic profile of Pramipexole

Parameters

Immediate release product Modified Release product

Mean S.D Mean S.D

Cmax 2.736 0.878 3.700 0.826

Tmax 1.688 0.355 4.833 1.167

AUC 0-t 16.315 2.945 28.206 4.111

Cmax 0.193 0.032 0.176 0.091

Tmax 4.690 0.696 4.699 0.756

AUC 0-t 16.912 2.823 29.859 4.200

148

148

Table 4.42 Statistical data for Pramipexole Immediate Release Vs Modified Release Formulation

Dependent variable: Cmax Tests of Between-Subjects Effect

Source Type III

sum of

squares

df Mean

square

F Sig. Partial Eta

squared

Noncent.

parameter

Observed

power a


Error

4.765

.798

1

30.987

4.765

2.554E-02b

131.564 .000 .843 131.564 1.000

SEQ Hypothesis

Error

8.109E-02

.600

1

22

8.324E-02

2.006E-02C

3.765 .060 .159 3.432 .540

PERIOD Hypothesis

Error

.000

.

0

.

.

.d

. . . . .

TREATME

NT

Hypothesis

Error

.000

.

0

.

.

.d

. . . . .

SUBJECT Hypothesis

Error

2.543

.432

23

22

9.549E-02

2.087E-02c

4.443 .000 .843 106.998 1.000

e. Computed using alpha = .1

f. 5.266E-02 MS(SUBJECT) +.870 MS (Error)

g. MS (Error)

h. Cannot compute the appropriate error term using Satterthwaite’s method

149

149


Dependent variable: AUC 0-t Tests of Between-Subjects Effect

Source Type III

sum of

squares

df Mean

square

F Sig. Partial Eta

squared

Noncent.

parameter

Observed

power a


Error

23.886

.508

1

28.654

23.886

1.421E-02b

1760.667 .000 .832 1760.667 1.000

SEQ Hypothesis

Error

5.987E-02

.342

1

22

3.843E-02

1.293E-02C

.332 .832 .000 .000 .100

PERIOD Hypothesis

Error

.000

.

0

.

.

.d

. . . . .


Error

.000

.

0

.

.

.d

. . . . .

SUBJECT Hypothesis

Error

.664

.421

23

22

3.565E-02

1.332E-02c

2.432 .009 .031 57.987 .998



g. MS (Error)


150

150


Dependent variable: AUC 0-inf Tests of Between-Subjects Effect

Source Type III

sum of

squares

df Mean

square

F Sig. Partial Eta

squared

Noncent.

parameter

Observed

power a


Error

26.997

.443

1

29.654

26.997

1.676E-02b

1978.443 .000 .569 1978.443 1.000

SEQ Hypothesis

Error

3.867E-02

.232

1

22

3.854E-02

1.67E-02C

.006 .659 .000 .430 .100

PERIOD Hypothesis

Error

.000

.

0

.

.

.d

. . . . .

TREATME

NT

Hypothesis

Error

.000

.

0

.

.

.d

. . . . .

SUBJECT Hypothesis

Error

.665

.321

23

22

3.887E-02

1.556E-02c

2.558 .000 .675 59.332 .564



g. MS (Error)


151

151

Table 4.45 Paired Sample Test for Pramipexole

Paired Differences

t df Sig. (2-

tailed)Mean

Std.

Deviation

Std.

Error

Mean

95% Confidence

Interval of the

Difference

Lower Upper

Pair 1 C max -.005 .217 .044 -.097 .085 -.109 23 .967

Pair 2 AUC 0-t -.092 .160 .032 -.160 -.024 -2.232 23 .013

Pair 3 AUC 0-inf -.086 .157 .031 -.153 -.028 -2.45 23 .01

152

152

Table 4.46 Cumulative percentage dissolved at 50 rpm for Pramipexole test formulations

Time

(h)

Square

root of

time (h)



MR IR MR IR MR IR MR IR MR IR

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

0.50 0.71 6.17 15.83 8.63 16.53 4.22 5.92 5.55 4.21 4.32 4.53

1.00 1.00 12.60 27.05 13.12 30.98 9.74 11.43 11.53 12.67 10.43 12.93

1.50 1.22 16.32 41.53 19.47 39.01 13.95 15.37 16.30 19.56 17.83 18.55

2.00 1.41 21.76 55.92 23.86 66.91 20.56 22.54 19.54 23.67 21.55 23.56

3.00 1.73 28.54 73.73 32.75 83.28 28.48 31.26 30.20 33.49 23.67 26.54

4.00 2.00 34.95 87.32 46.91 93.64 35.21 42.54 44.67 49.54 35.26 39.43

6.00 2.45 40.87 97.38 70.42 98.54 53.90 56.48 62.54 66.37 49.32 55.32

8.00 2.83 49.21 99.80 79.32 100.55 67.02 70.43 75.20 83.24 65.34 72.10

12.00 3.46 71.55 100.04 90.76 100.69 83.20 86.34 86.77 91.17 74.21 79.00

18.00 4.24 91.77 100.08 96.09 101.76 97.03 97.97 99.21 97.56 83.24 90.53

24.00 4.90 95.51 100.92 99.53 102.20 101.32 98.10 99.55 98.20 93.42 89.41

153

153

AX

IS

TIT

LEC H A R TT I T L E

100

80

60

40

20

00 5 10 15

20 25

AXISTITLE

Fig 4.33: Cumulative Pregabalin Release Vs Time Profile for Immediate and


154

154

Table 4.47 Cumulative percentage dissolved at 75 rpm for Pramipexole test formulations

Time

(h)

Square

root of

time (h)



MR IR MR IR MR IR MR IR MR IR

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

0.50 0.71 9.45 18.54 10.49 20.42 9.43 17.43 7.32 09.67 8.09 11.76

1.00 1.00 16.56 33.21 15.32 33.89 14.78 21.86 14.98 18.56 14.89 18.34

1.50 1.22 22.89 49.27 20.98 46.92 20.54 26.89 18.08 23.05 19.45 21.75

2.00 1.41 25.94 55.98 26.79 57.23 26.97 35.01 22.65 28.53 22.67 25.56

3.00 1.73 33.01 71.45 35.64 76.07 35.74 58.21 32.95 36.78 28.06 35.78

4.00 2.00 38.90 88.21 44.10 95.31 45.82 69.02 48.94 53.11 40.21 45.20

6.00 2.45 44.21 99.65 72.21 99.00 59.20 79.98 65.20 72.05 57.93 63.56

8.00 2.83 54.67 100.43 83.43 100.63 72.34 89.04 77.55 84.43 71.22 75.65

12.00 3.46 75.23 100.76 96.29 101.69 88.30 99.00 89.08 96.21 79.03 82.08

18.00 4.24 92.43 100.90 99.06 101.77 100.05 100.34 100.56 100.07 89.32 100.65

24.00 4.90 99.76 101.15 100.62 101.98 101.32 100.94 101.67 100.76 97.54 100.71

155

155

AX

IS

TIT

LE

C H A R TT I T L E

100

80

60

40

20

00 5 10 15

20 25

AXISTITLE



156

Table 4.48 Similarity Factors for Pramipexole Modified Release Formulations

in Various Dissolution Conditions

S.No pH Condition Formulation Similarity factor

(f2)

1 pH 1.2 buffer 50 rpm

Immediate

Release verses

Modified

Release

45.87

2 pH 1.2 buffer 75 rpm 47.34

3 pH 4.5 buffer 50 rpm 43.76

4 pH 4.5 buffer 75 rpm 42.91

5 pH 6.8 buffer 50 rpm 93.10

6 pH 6.8 buffer 75 rpm 77.20

7 Distilled water 50 rpm 91.67

8 Distilled water 75 rpm 95.21

9 pH 7.4 buffer 50 rpm 87.45

10 pH 7.4 buffer 75 rpm 88.76

157

Table 4.49 IVIVC model regression of % absorbed vs. % dissolved for


Time

(Hours)


(pH 1.2)


(pH 4.5)

Percentage absorbed

MR IR MR IR MR IR

0.00 0.00 0.00 0.00 0.00 0.00 0.00

0.50 6.17 15.83 8.63 16.53 2.10 3.10

1.00 12.60 27.05 13.12 30.98 4.53 11.72

1.50 16.32 41.53 19.47 39.01 10.76 23.03

2.00 21.76 55.92 23.86 66.91 20.54 51.04

00 28.54 73.73 32.75 83.28 47.98 73.00

00 34.95 87.32 46.91 93.64 82.84 88.21

00 40.87 97.38 70.42 98.54 94.21 95.49

00 49.21 99.80 79.32 100.55 96.04 95.98

12.00 71.55 100.04 90.76 100.69 96.31 96.39

18.00 91.77 100.08 96.09 101.76 99.01 97.78

24.00 95.51 100.92 99.53 102.20 99.41 98.12

158

100

90

80

70

60

50

40

30

20

10

0

0 20 40 60 80 100

Fig. 4.35: IVIVC model Linear Regression Plot of % Absorbed Vs % Dissolved for

Immediate and Modified Release Pramipexole Formulations using pH 1.2 Buffer at 50

RPM

100

90

80

70

60

50

40

30

20

10

0

0 20 40 60 80 100


for Immediate and Modified Release Pramipexole Formulations using pH 4.5

Buffer at 50 RPM

Table 4.50 IVIVC model regression of % absorbed vs. % dissolved for


Time

(Hours)


(pH 1.2)


(pH 4.5)

Percentage absorbed

MR IR MR IR MR IR

0.00 0.00 0.00 0.00 0.00 0.00 0.00

0.50 9.45 18.54 10.49 20.42 2.10 3.10

1.00 16.56 33.21 15.32 33.89 4.53 11.72

1.50 22.89 49.27 20.98 46.92 10.76 23.03

2.00 25.94 55.98 26.79 57.23 20.54 51.04

3.00 33.01 71.45 35.64 76.07 47.98 73.00

4.00 38.90 88.21 44.10 95.31 82.84 88.21

6.00 44.21 99.65 72.21 99.00 94.21 95.49

8.00 54.67 100.43 83.43 100.63 96.04 95.98

12.00 75.23 100.76 96.29 101.69 96.31 96.39

18.00 92.43 100.90 99.06 101.77 99.01 97.78

24.00 99.76 101.15 100.62 101.98 99.41 98.12

100

90

80

70

60

50

40

30

20

10

0

0 20 40 60 80 100

Fig. 4.37: IVIVC model Linear Regression Plot of % Absorbed Vs % Dissolved for

Immediate and Modified Release Pramipexole Formulations using pH 1.2 Buffer at 75

RPM

100

90

80

70

60

50

40

30

20

10

0

0 20 40 60 80 100


for Immediate and Modified Release Pramipexole Formulations using pH 4.5

Buffer at 75 RPM

Table 4.51 Observed and IVIVC model predicted Cmax and AUC values for

Pramipexole

Time

(Hours)

IR formulation MR formulation

Fraction

observed

Fraction

predicted

Fraction

observed

Fraction

predicted

0.00 0.000 0.000 0.000 0.000

0.50 1.014 1.176 0.157 0.162

1.00 1.968 2.043 0.290 0.265

1.50 2.205 2.328 0.614 0.609

2.00 2.571 2.643 1.081 1.025

3.00 1.894 1.934 1.895 1.792

4.00 1.210 1.158 2.636 2.603

6.00 0.970 1.043 2.855 2.821

8.00 0.681 0.721 2.136 2.098

12.00 0.405 0.428 1.140 1.021

18.00 0.142 0.154 0.453 0.407

24.00 0.000 0.073 0.244 0.189

Cmax 2.571 2.643 2.855 2.821

AUC 17.432 17.539 27.654 27.045

162

Fig. 4.39: Observed and Predicted Pregabalin Plasma Concentration for the

Immediate Release Pregabalin Formulations using IVIVC Model

3.5

3

2.5

2

1.5

1

0.5

00 5 10 15 20 25


Fig. 4.40: Observed and Predicted Pregabalin Plasma Concentration for the

Modified Release Pregabalin Formulations using IVIVC Model

163

Table 4.52 Prediction errors (%) associated with Cmax and AUC for

Pramipexole

Formulation Cmax AUC

Immediate -2.724 -0.610

Modified 1.205 2.252

Average -0.759 0.821

164

CHAPTER 5

SUMMARY AND CONCLUSION

This thesis deals with the studies carried out by the writer for the past three

years on the “Development and Validation of in-vitro and in-vivo correlations for

Pregabalin and Pramipexole formulations”.

The first chapter begins with a brief account of the in-vitro and in-vivo

correlations, biopharmaceutical classification system, IVIVC models, in-vitro and in-

vivo dissolutions and estimation of drugs in biological medium. The methods used

for the IVIVC model development, validation, the steps involved in bio-analytical

method development, in-vitro dissolution methods and their importance have also

been discussed.

The second chapter briefs the review of literature on the LC-MS/MS methods

available for the estimation of the selected drugs in biological fluids, IVIVC model

development, validation, in-vitro dissolution methods.

The third chapter deals with the scope and object of the present investigation.

The merits of IVIVC in the development of dosage forms and how IVIVC model

development necessitates development of in-vitro dissolution methods, bio-analytical

method development and validation are discussed. The objectives of the present

study, namely, to optimize the chromatographic conditions, to develop and validate

the methods to estimate the selected drugs in the biological fluids LC-MS/MS,

development of in-vitro dissolution methods and IVIVC model development and

validation, have been described.

The fourth chapter deals with the experimental procedures adopted. It describes

in detail the procedures adopted for the bioequivalence study design and data

165

handling, optimization and validation of the chromatographic conditions for the

estimation of the drugs in plasma and selected MR formations, IVIVC model

development and validation.

In the fifth chapter, the results obtained are presented, supported by tables and

figures and discussed in detail.

The discussion includes,

Bioequivalence study design and data handling

Optimization and validation of the chromatographic conditions for the

estimation of the drugs in plasma and selected MR formulations

Chromatograms obtained

Accuracy

Reproducibility (intraday and interday variations)

Specificity

Linearity and range

LOD and LOQ

Ruggedness and robustness

Stability and

System suitability studies

in-vitro – in-vivo data analysis

in-vitro – in-vivo correlation

Model development

Internal and external validation

166

The following are some of the salient features of the present study;

A single dose, randomized, complete two way and two treatments cross

over study was conducted in healthy human subjects and plasma

concentrations were estimated by sensitive and validated LC-MS/MS

methods.

The selected drug candidates Pramipexole and Pregabalin are water

soluble drugs that are predominantly ionized in gastrointestinal pH ranges

and are well absorbed after oral administration.

The selected drugs can be categorized as high solubility/high permeability

drugs under the proposed Class I Biopharmaceutical Classification System

(BCS) and hence it becomes necessary to determine the in-vitro and in-

vivo correlations for these drugs.

The target to find out a predictive in-vitro dissolution method was reached

gradually. The first step was taken by observing which in-vitro dissolution

method predicted best similarities and differences in bioavailability.

Apparatus I, pH 6.8 at 75 rpm was found to yield acceptable IVIVC for

Pregabalin, whereas, Apparatus I, pH 1.2 at 75 rpm was found to yield

acceptable IVIVC for Pramipexole.

From a comparison of the differences in the in-vitro pharmacokinetic

parameters and the differences in the in-vitro dissolution curves, it may be

concluded that the developed dissolution method will discriminate batches

which are non-bioequivalent.

Level A correlation was observed for the selected formulations at the in-

vitro dissolution conditions developed. These dissolution methods

predicted also the best absorption rate for the selected modified release

formulations.

167

The validity of the correlation was also assessed by determining how well

the IVIVC model could predict the rate and extent of absorption as

characterized by Cmax and AUC. The percent prediction error of ≤ 10 % for

Cmax and AUC was obtained, which establishes the predictability of the

developed IVIVC model. It may, thus, be concluded that the developed

dissolution methods can surrogate for human bioequivalence studies.

In conclusion, it may be pointed out that the developed in-vitro dissolution

methods can replace absorption studies during the pre-approval processes to develop

a desirable formulation and to ensure batch-to-batch bioequivalence. It will also be

very useful in performing possible post-approval changes in the formulation scale-up

or changes in the drug substance or excipients supplier.

168

REFERENCES

Abib, JR, Eduardo, Duarte, Luciana Fernandes, Pereira & Renata 2012, ‘A

comparative bioavailability studies of two Pramipexole formulations in healthy

volunteers’, Journal of Bioequivalence & Bioavailability, vol. 4, no. 5, pp. 56-60

Alessandro Musenga, Ernst Kenndler, Emanuele Morganti, Fabrizio Rasi &

Maria Augusta Raggi 2008, ‘An analysis of the anti-parkinson drug Pramipexole

in human urine by capillary electrophoresis with laser-induced fluorescence

detection’, Analytica Chimica Acta, vol. 626, no. 1, pp. 89-96

Chakshu Bhatia, Monika Sachdeva & Meenakshi Bajpai 2012, ‘Formulation and

evaluation of transdermal patch of Pregabalin’, International Journal for

Pharmaceutical Sciences and Research, vol. 3, no. 2, pp. 232-245

Charles, P, Taylora, Timothy Angelottib & Eric Faumanc 2007, ‘The

pharmacology and mechanism of action of Pregabalin’, Epilepsy Research,

vol. 73, no. 2, pp. 137-150

Chwieduk, CM & Curran, MP 2010, ‘The use of once-daily Pramipexole

extended release formulation for the treatment of early and advanced idiopathic

Parkinson’s disease’, CNS Drugs, vol. 24, no. 4, pp. 327-36

Daniel, M, Tassone, Eric Boyce, Jennifer Guyer & Donald Nuzum 2007, ‘The

pharmacology, pharmacokinetics, efficacy, and tolerability of Pregabalin’,

Clinical Therapeutics, vol. 29, no. 1, pp. 26-48

Dansirikul, C, Staab, A, Salin, L, Haertter, S & Lehr, T 2009, ‘Population

pharmacokinetic analysis of pramipexole extended-release formulation in

169

Parkinson's disease (PD) patients’, Proceedings of the 18th Annual Meeting of

the Population Approach Group in Europe (PAGE '09), St. Petersburg, Russia

Dickinson, PA, Lee, WW, Stott, PW, Townsend, AI, Smart, JP, Ghahramani, P

et al. 2008, ‘Clinical relevance of dissolution testing in quality by design’,

American Association of Pharmaceutical Scientists Journal, vol. 10, no. 2,

pp. 380-390

Dziedzicka-Wasylewska, M, Ferrari, F & Johnson, RD 2001, ‘Mechanisms of

action of pramipexole: effects on receptors’, Reviews in Contemporary

Pharmacotherapy, vol. 12, no. 1-2, pp. 1-31

Elena Soto, Sebastian Haertter, Michael Koenen Bergmann, Alexander Staab &

Iñaki F Troconiz 2010, ‘An in-vitro and in-vivo correlation model for

Pramipexole slow-release oral formulations’, Pharmaceutical Research, vol. 27,

no. 2, pp. 340-349

Gomez-Mantilla, JD, Schaefer, UF, Casabo, VG, Lehr, T & Lehr, CM 2014, ‘A

statistical comparison of dissolution profiles to predict the bioequivalence of

extended release formulations’, Journal of the American Association of

Pharmaceutical Scientists, vol. 16, no. 4, pp. 791-801

Gregor Bender, James Gosset , Keith Tan , Mark Field, Scott Marshall , Joost

DeJongh et al. 2009, ‘Population pharmacokinetic model of the Pregabalin-

sildenafil interaction in rats, application of simulation to preclinical PK- PD

study design’, Pharmaceutical Research, vol. 26, no. 10, pp. 2259-2269

Grosset, KA, Bone, I & Grosset, DG 2005, ‘Suboptimal medication adherence in

Parkinson's disease’, Movement Disorders, vol. 20, no. 11, pp. 1502-1507

Hauser, R, Salin, L & Koester, J 2009, ‘Double-blind evaluation of pramipexole

extended-release (ER) in early Parkinson's disease’, Neurology, vol. 72, no. 11,

pp. A412-A413

170

Hauser, M, Schapira, RA, Rascol, AH, Barone, O, Mizuno, P, Salin, Y et al.

2010, ‘An evaluation of Pramipexole extended release once daily in early

Parkinson's disease’, Movement Disorders, vol. 25, no. 15, pp. 2542-2549

Jantratid, E, De Maio, V, Ronda, E, Mattavelli, V, Vertzoni, M & Dressman, JB

2009, ‘Application of biorelevant dissolution tests to the prediction of in-vivo

performance of diclofenac sodium from an oral modified-release pellet dosage

form’, European Journal of Pharmaceutics and Biopharmaceutics, vol. 37,

no. 3-4, pp. 434-441

Jenner, P, Könen-Bergmann, M, Schepers, C & Haertter, S 2009,

‘Pharmacokinetics of a Once-Daily extended-release formulation of pramipexole

in healthy male volunteers: three studies’, Clinical Therapeutics, vol. 31, no. 11,

pp. 2698-2711

Jose David, Gomez Mantillaa, Vicente German Casaboc, Ulrich, F, Schaefera &

Claus Michael Lehra 2013, ‘The permutation test (PT) and tolerated difference

test (TDT) for statistical comparison of dissolution profiles’, International

Journal of Pharmaceutics, vol. 441, no. 1-2, pp. 458-467

Jost, WH 2010, ‘The clinical studies of Pramipexole Immediate-release and

extended-release tablets’, Journal of the Neurological Sciences, vol. 289, no. 1-2,

pp. 69-73

Kasawar, GB & Farooqui, MN 2010, ‘HPLC method for the determination of

Pregabalin in capsule dosage form’, Indian Journal of Pharmaceutical Sciences,

vol. 72, no. 4, pp. 517-519

Koenen-Bergmann, M, Haertter, S & Schepers, C 2008, ‘A multiple rising-dose

bioequivalence phase I study with a pramipexole extended release (ER)

formulation’, Europian journal of neorology, vol. 15, no. 1, pp. 97-98

171

Kortejarvi, H, Mikkola, J, Bäckman, M, Antila, S & Marvola, M 2002,

‘Development of level A, B and C in-vitro-in-vivo correlations for modified-

release levosimendan capsules’, International Journal of Pharmaceutics ,

vol. 241, no. 1, pp. 87-95

Lake, OA, Olling M & Barends, DM 1999, ‘In-vitro/in-vivo correlations of

dissolution data of carbamazepine immediate release tablets with

pharmacokinetic data obtained in healthy volunteers’, European Journal of

Biopharmaceutics, vol. 48, no. 1, pp.13-19

Malte Selch Larsen, Sidsel Frølund, Martha Kampp Nøhr, Carsten Uhd Nielsen,

Mats Garmer, Mads Kreilgaard et al. 2015, ‘An in-vivo and in-vitro Evaluations

of Intestinal Gabapentin’, Pharmaceutical Research, vol. 32, no. 3, pp. 898-909

Meihua Rose Feng, Daniel, Jim Burleigh, Richard Lister, Conglin Fan, Anne

Middlebrook et al. 2001, ‘A brain microdialysis and PK/PD correlation of

Pregabalin in rats’, European Journal of Drug Metabolism and

Pharmacokinetics, vol. 26, no. 1, pp. 123-128

Pathare, DB, Jadhav, AS & Shingare, MS 2006, ‘A validated chiral liquid

chromatographic method for the enantiomeric separation of Pramipexole

dihydrochloride monohydrate’, Journal of Pharmaceutical and Biomedical

Analysis, vol. 41, no. 4, pp. 1152-1156

Peter Jenner, Michael Konen Bergmann, Cornelia Schepers & Sebastian Haertter

2009, ‘Pharmacokinetic properties of a variety of prototypes for a once daily

extended release (ER) formulation of Pramipexole’, Clinical Therapeutics,

vol. 31, no. 11, pp. 2698-2711

Poewe, W, Barone, P & Hauser, RA 2009, ‘Pramipexole extended-release is

effective in early Parkinson's disease’, Journal of Movement Disorders, vol. 24,

no. 1, pp. 273-279

172

Pui Shan Chana, Chunbo Zhanga, Zhong Zuoa, Patrick Kwanb, C & Larry

Bauma 2014, ‘An in-vitro transport assays of rufinamide, Pregabalin, and

zonisamide by human P-glycoprotein’, Epilepsy Research, vol. 108, no. 3,

pp. 359-366

Quinones, L, Sasso, J, Tamayo, E, Catalan, J, Gonzalez, JP, Escala, M et al.

2010, ‘A comparative bioavailability study of two formulations of Pregabalin in

healthy Chilean volunteers’, Therapeutic Advances in Chronic Disease, vol. 1,

no. 4, pp. 141-148

Rascol, O, Barone, P & Debieuvre, C 2009, ‘Overnight switching from

immediate-to extended-release (ER) in early Parkinson's disease’, Neurology,

vol. 72, no. 11, pp. 320-325

Rascol, O, Barone, P, Hauser, RA, Mizuno, Y, Poewe, W, Schapira, AH et al.

2010, ‘Pramipexole Switch Study Group’, Journal of Movement Disorders,

vol. 25, no. 14, pp. 2326-2332

Reza Ahmadkhaniha, Siavash Mottaghi, Mohammad Zargarpoor & Effat Souri

2014, ‘A validated HPLC method for quantification of Pregabalin in human

plasma using 1-fluoro-2,4-dinitrobenzene as derivatization agent’, International

Journal of Chromatography Research, vol. 2014, no. 1, pp. 1-6

Robert Lee, Cantu, Monab, Lindenfeld, JoAnnb, Hergott et al. 2008, ‘The

possible heart failure exacerbation associated with Pregabalin’, Journal of

Cardiovascular Medicine, vol. 9, no. 9, pp. 922-925

Rossi, RC, Dias, CL & Donato, EM 2007, ‘Development and validation of

dissolution test for ritonavir soft gelatin capsules based on in-vivo data’,

International Journal of Pharmaceutics, vol. 338, no. 1-2, pp.119-124

173

Salin, K, Hauser, R & Koester, J 2009, ‘Double-blind evaluation of maintenance

of efficacy of pramipexole extended-release in early Parkinson's disease’, Mov

Disorder, vol. 25, no. 15, pp. 2542-9

Schapira, P, Barone & Hauser, R 2009, ‘Efficacy and safety of pramipexole

extended-release for advanced Parkinson's disease’, Proceedings of the 13th

Annual International Congress of Parkinson's Disease and Movement Disorders,

Poster WE-199, Australia

Soto, E, Haertter, S, Koenen Bergmann, M, Staab, A & Troconiz, IF 2010,

‘Population in-vitro and in-vivo correlation model for Pramipexole slow-release

oral formulations’, Journal of Pharmaceutical Research, vol. 27, no. 2,

pp. 340-349

Thrasivoulos G Tzellos, Georgios Papazisis, Ekaterini Amaniti & Dimitrios

Kouvelas 2008, ‘The efficacy of Pregabalin and gabapentin for neuropathic pain

in spinal-cord injury’, European Journal of Clinical Pharmacology, vol. 64,

no. 9, pp. 851-858

Trond Kvernmo, Sebastian Härtter & Erich Burger 2006, ‘A dopamine agonists

(DAs) for the treatment of Parkinson's disease’, Clinical Therapeutics, vol. 28,

no. 8, pp. 1065-1078

Wolfram Eisenreich, Bernd Sommer, Sebastian Hartter & Wolfgang, H 2010, ‘A

novel treatment option in Parkinson's disease using Pramipexole extended

release formulations’, Parkinson's Disease, vol. 2010, no. 2, pp. 143-149

Yi Lau Yau, Glenn, D, Hanson & Nita Ichhpurani 1996, ‘Determination of

Pramipexole (U-98,528) in human plasma and urine by high-performance liquid

chromatography with electrochemical and ultraviolet detection’, A Journal of

Chromatography B: Biomedical Sciences and Applications, vol. 683, no. 2,

pp. 217-223

174

LIST OF PUBLICATIONS

Uma, G, Manimala, M, Vasudevan, M, Karpagam, S & Deecaraman, M 2012,

‘LC-MS-MS method for the determination of Pregabalin in human plasma’,

International Journal of Pharmacy and Pharmaceutical Sciences, vol. 4,

no. 3, pp. 108-112 (Scopus indexed)

Uma, G, Manimala, M, Vasudevan, M, Karpagam, S & Deecaraman, M 2012,

‘Development and Validation of LCMS method for the estimation of

Pramipexole in Human Plasma’, International Journal of Pharmacy and

Pharmaceutical Sciences, vol. 2, no. 1, pp. 10-11 (Scopus indexed)

Manimala, M, Karpagam, S & Deecaraman, M 2013, ‘LC-MS-MS method

for the determination of Digoxin in human plasma’, International Journal of

Pharmacy and Pharmaceutical Sciences, vol. 5, no. 2, pp. 131-132 (Scopus

indexed)

Manimala, M, Clement Atlee, W, Sheik Mohamed, AA & Purushoth Prabhu,

T 2014, ‘Effect of Coccinia grandis on ammonium chloride and ethylene

glycol induced urolithiasis in rats’, International Journal of Drug

Development and Research, vol. 6, no. 3, pp. 138-146 (Scopus indexed)

Manimala, M, Karpagam, S, Deecaraman, M, Clement Atlee, W & Purushoth

Prabhu, T 2015, ‘Evaluation of nephroprotective and antioxidant activity of

ethanoic extracts of Momordica dioica leaves’, Scholars research Library ,

vol. 7, no. 4, pp. 153-156

Documents

sg.inflibnet.ac.in · ii DECLARATION BY THE CANDIDATE I declare that the thesis entitled “DEVELOPMENT AND VALIDATION OF IN-VITRO AND IN-VIVO CORRELATIONS FOR PREGABALIN AND PRAMIPEXOLE