PowerPoint PresentationAPS Virtual Webinar Series "VIRTUAL WEBINAR 2021 SERIES – Developing Clinically Relevant
Dissolution Specifications (CRDS) for Oral Drug Products"
June 15th 2021
Overview
1. Virtual Bioequivalence
a. Automated Software Tools (e.g., safe space identification)
b. Physiology / covariates – Between and Within Subject Variability (BSV and WSV)
2. Mechanistic Models
a. Handling BSV and WSV of physiology, extrapolation to other populations
b. How best to parameterise these models
c. Limitations
3. Advanced Models – surface pH, salts, excipient Handling, time variant [bile salts] …
4. Brief examples
Comment from previous APS CRDS presentation– “PBPK models have focussed on average subject rather than variability”
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ADAM Model Structure
Segregated Blood Flows
Total Small Bowel Water Volumes
1 hr Mean ~80 mL
4
Time from fluid intake (mins)
Imaging at Intervals after 240 mL Water Drink (Fasted)
UBL Water
Regional and Between Subject Variability of Permeability
Embracing Variability: Gut Wall Permeability
The BSV in Peff predicted by the MechPeff model derives from the BSV of the underlying parameters and is NOT simply the addition of a CV to an “average” Peff.
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Example of Manifestation of Between Subject Variability: precipitation
% of Simulated Volunteers
2-Phase/Serial Dilution
Model verification: At the level of the gut much of the experimental luminal data are in a few subjects and often duodenal only
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A Selection of Gut-Related Parameters with BSV Available in Simcyp
7
Fasted Buffer capacity
Monolith Transit (fasted)
Fluid Transit (fasted)
100 simulated HV subjects All underlying data based on literature meta-analysis of clinical data
This information is used by the Surface pH model (discussed in a previous webinar, acalabrutinib)
Monte Carlo Sampling
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The Complexity of Covariate Effects
Age
Correlated Monte Carlo Sampling
subjects
For gut physiology covariate data are mostly not available or available for very few subjects …
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Mechanistic Models / Systems Data form the Core – Various “Wrappers” are Available
Physiologically-Based IVIVC (PB-IVIVC)
Sensitivity Analysis (SA) • Local SA (parameter scan) • Global SA ( Sobol or Morris )
Virtual Bioequivalence (VBE) (Simcyp v20)
WSV (IOV) (Within Subject or Inter-Occasion Variability)
of Physiology
Mechanistic Models are essential for capturing regional differences of gut physiology, time variant factors, interindividual variability and WSV (IOV)
BSV Generate virtual subjects via Monte Carlo (MC) or correlated MC sampling
Parameter Estimation Tools
Bottom-up PBPK
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1) VBE Trial Design - Most common designs available plus custom option
– Crossover 2 Treatment, 2 Period, 2 Sequence (typical crossover BE)
– Crossover 2T, 2P and 4S
– Crossover partial replicate (2T, 3P, 4S)
– Crossover full replicate (2T, 4P, 2S)
– Crossover full replicate (2T, 4P, 4S)
– Parallel (up to four treatments) – different population allowed per treatment
– Crossover custom design
2) Within Subject Variability (WSV) is added to Physiological Parameters
3) BE Analysis - Phoenix
Scope of VBE Tool
NCA + BE Analysis
VBE Trials
For the purposes of VBE simulations the input can be either in vitro dissolution or, where available, a mechanistic model can be used.
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Implications for BE of Crystallization of Tacrolimus in Generic Drug Products
12
Mean Profiles for 50
Fully amorphous
Fully crystalline
Formulation Fg
100% Amorphous
0.45
13© Copyright 2020 Certara, L.P. All rights reserved. Grimm 2018 Eur J Pharm Biopharm
Subject 1 Subject 3
Subject 4 Subject 6
Subject 7 Subject 8
to whole subject group variability
Minimal
WSV
High
WSV
Fasted Gastric Fluid Volume & Gastric Emptying (GE) (MRI study)
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Handling Dissolution with PBPK / VBE Models: Dissolution Rate (DR)
In Vitro % dissolved
Modelling of In Vitro
In vivo physiology pH, fluid volumes etc. with variability
Mechanistic model informed/verified/ parameterised by in vitro experiment
In vivo physiology pH, fluid volumes etc. with variability
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Mechanistic Prediction of Oral Drug Absorption of Drug Products: Current Status
*BSV, WSV – Between, Within Subject Variability
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DLM Scalar vs Z-Factor vs P-PSD
DR(t) = dissolution rate at time t SDR = DLM scalar (empirical)
Wang & Flanagan DLM
=0
2 3
− ()
= 3
t=0
DLM with Z-factor
More mechanistic (can be improved of course) Greater sensitivity to physiology and its variability (BSV/WSV)
Less mechanistic Low sensitivity to physiology and its variability (BSV/WSV) May be sufficient …
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PSD Estimated With/Without Mechanistic Fluid Dynamics (USP 2)
Batch 12A015 QC Dissolution
Input to SIVA 4
SIVA Simulations (no fitting)
Fluid Dynamics heff (“FD heff”)
Hintz-Johnson heff
Data from Pepin et al 2017 Lesinurad P-PSD Mol Pharmaceut
This FD approach enables us to factor out USP 2 hydrodynamics
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Same Data with PSD Estimated Within SIVA 4 (USP 2 Paddle)
Fluid Dynamics heff Monodisperse PSD
Polydisperse PSD N Bins = 5, min = 50, max = 200 um
Fluid Dynamics heff
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ADAM Population PBPK
A Strategy for PBPK Modelling: Biopharmaceutic IVIVE
• PBPK / PBBM modelling o Informed by in vitro experiments o Estimate and/or gain confidence in intrinsic parameters prior to their use in a PBPK Model o Reduces the need for estimation within the PBPK model (parameter identifiability) o Permits extrapolation to different conditions
Biopharmaceutic Modelling
Estimated/Confirmed Parameters
Ptrans,0 (MechPeff)
SIVA is a stand alone software for modelling of in vitro experiments
Transporter Jmax KM
For non-PBPK purposes:
Gain insight into API/drug product behaviour, qualitative (eg ranking) or quantitative …
Predict %dose dissolved vs time or in vivo gut lumen time concentration profile - for an “average” subject
inForm/T3USP II
µDiss
For parameterising/informing PBPK models, simpler experiments are usually better … parameter identifiability
Experiments need not exactly match a (hypothetical?) “average” subject but do need to be in the right space …
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Recently Added Advanced Models: I
Dual Solid State Handling
Surface pH and solubility
Potential applications to salt screening … ms submitted Data: Gesenberg et al 2019
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Recently added Advanced Models: II
Dynamic GI Parameters
Dynamic Physiology - Bile Salts concentrations Fasted, low fat and high fat fed Gallbladder kinetics linked to IMMC (fasted) (BSV/WSV) Switch between fasted and fed states during simulation Enterohepatic recirculation
Time variant solubility, dissolution, permeability
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Recently added Advanced Models: III
Dynamic Solubilisation: Cyclodextrin impact on solubility and permeability of an API
Solubility at time t
Decomposition of solubility to it’s contributory factors is essential
0
20000
40000
60000
80000
100000
Lu m
in al
c on
ce nt
ra tio
n Fr
ee o
8g HPCD
, = 0 (1:1 + 1:11:2 2
Peff in this case includes within its value free fraction effects
Applications 1) Formulation design
2) Complex metabolic and excipient mediated DDI – fenebrutinib displaced excipient bound to co-dosed itraconazole
Chen et al 2020 CPT:PSP https://www.youtube.com/watch?v=77Q5RTl4VlU&list=UUj3YZgKXa8vwRXgvD2dfEcQ&index=8
Fenebrutinib
Summary
a. Automated Software Tools (e.g., safe space identification)
b. Physiology / covariates – Between and Within Subject Variability (BSV and WSV)
2. Mechanistic Models
a. Are a must have for sensitivity to BSV and WSV of physiology
b. Limitations
Numerous gaps include: multiple excipients, mechanistic disintegration, FE, etc., etc. (UNGAP reviews)
4. For parameterising biopharmaceutic PBPK Models
1. Appropriate experiments are required
2. Simple experiments preferred (parameter identifiability)
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Acknowledgements
Nikunjkumar Patel Shriram Pathak (now Quotient Sciences)
Konstantinos Stamatopoulos (now GSK)
James Clark Dan Liu (now UCB)
Certara-Simcyp and former colleagues
USP-2 Dissolution Modelling
Confirmed DLM Parameters
Biorelevant Solubility Modelling
Aqueous Solubility Modelling
Sequential in vitro Modelling of Ketoconazole Solubility & Dissolution
Transfer Experiment Modelling
Determine precipitation parameters
+ Formulation “Disintegration” (at low pH where the API dissolution is not rate limiting)
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Clinical Results – Fenebrutinib-Itraconazole – metabolic AND CD-mediated DDI
Fenebrutinib alone
Fenebrutinib + itraconazole