DRUG METABOLISM AND PHARMACOKINETICS (DMPK)

DRUG METABOLISM AND PHARMACOKINETICS (DMPK) Lena Gustavsson, H. Lundbeck A/S, LEGU@lundbeck.com November 2015

DMPK in Drug Discovery and Development Agenda

Introduction Optimizing pharmacokinetic properties

Absorption & bioavailability Distribution Elimination – Clearance

Understanding clearance mechanisms Drug metabolism Drug transporters

Drug drug interactions and interindividual variability Summary: Drug discovery and development

H. Lundbeck A/S – an introduction A pharmaceutical company with focus on brain diseases

More than 700 million people are affected by brain disease worldwide Lundbeck is dedicated to address the global burden of brain disease Psychiatric diseases e.g. bipolar disorder, depression, schizophrenia Neurologic diseases e.g. Alzheimer´s, Parkinson´s, Huntington´s

A global company with head quaters in Valby, Denmark

Total approximately 5500 employee´s Approximately 1700 employees in Denmark Full value chain from research to production

Want to know more? Go to: www.lundbeck.com/global/about-us/progress-in-mind www.youtube.com/user/progressinmind

Why study Drug Metabolism and PharmacoKinetics?

DRUG DISCOVERY Optimise compounds to get...

Good bioavailability – get to its target Appropriate duration (1-2 doses/day) Low potential for drug-drug interactions

…predicted to man Provide basics for understanding of

Toxicology Pharmacology

DRUG DEVELOPMENT Provide understanding of drug disposition

Preclinical animal species – tox coverage Human data

Assess the risk for drug drug interactions (DDI) Decrease risk for drug drug interactions in the clinic Impact on the design of clinical studies

Comply with guidelines from regulatory authorities

From Rowland and Tozer, 1995

2015-11-08 Lena Gustavsson

Reasons for compound attrition

Kola and Landis 2004

Pharmacokinetics – oral administration

ADME = Absorption Distribution Metabolism Excretion

Absorption

Lipinski’s rule of 5 to predict poor permeability/absorption (Lipinski et al, Adv Drug Delivery Rev 23:3-25, 1997)

Mw > 500 Log P > 5 H-bond donors >5 H-bond acceptors > 10

Transporter substrates are exceptions from the rule.

Is the drug absorbed? No = low bioavailability !

Permeability Caco-2

Caco-2 • Human colon epithelial cell line • Differentiates to monolayer with tight junctions

•Papp: cm/sec x 10-6

correlates to human abs

•Indication of transporter mechanisms • Automated incubations • LC-MS/MS analysis

• Alternative to Caco-2: PAMPA – artificial membrane

Bioavailability - oral administration

Fhep Fabs

F = Fgut x Fabs x Fhep

Liver Portal vein

Gut wall Gut lumen

Fhep = 1 - Ehep

Distribution • Drug distribution is the reversible transfer of drug to and from the site of measurement (blood/plasma) • Distribution is influenced by

-perfusion – blood circulation to tissues -diffusion -physicochemical properties -binding to proteins etc

Not a real volume but a mathematical expression of the extent to which a drug distributes into tissues

-Low V – drug stays in blood/plasma -High V – drug distributes extensively into tissues

V relates the concentration at site of measurement to the total amount of drug in the body (L/kg) V=Amount drug in body/plasma concentration (L/kg bw)

Volume of distribution (V)

Elimination: The concept of clearance (CL)

Clearance is the apparent volume of plasma completely cleared of drug per unit time

Rate of elimination = CL x C CL = Dose / AUC (iv dose) Unit: mL/min/kg

Hepatic clearance

Bile duct

Hepatic vein

Gall Bladder

Hepatic artery

Hepatic portal vein

The liver is the major site of drug metabolism

Drug metabolizing enzymes Route of elimination of the top 200 most

prescribed drugs in 2002

Enzymes listed in FDA guidelines • CYP: 1A2, 2B6, 2C8, 2C9,

2C19, 2D6, 3A • UGT: 1A1, 1A3, 1A4, 1A6, 1A9,

2B7, 2B15

Weinkers and Health Nat Rev Drug Discov 4:825-833, 2005

How to estimate metabolic clearance from in vitro studies?

Metabolic stability Microsomes or

hepatocytes

Phase I +II II

metabolites

How fast is the drug eliminated by the liver ? Fast = low bioavailability ! Fast = short duration !

CLint - the intrinsic capacity of a system to clear a drug (µL/min/mg protein or cells)

CLint = = V0 / [S] Vmax Km

0 20 40 60 80

Time (minutes)

Prediction of in vivo clearance from in vitro data

CLint= ln 2 /( t1/2 x protein conc)

CLint’= CLint x (mg microsomes/g liver) x (g liver/kg bw)

If well-stirred model CLhep,met,= (Qh x fu x CLint’)/ (Qh + (fu x CLint’)

CL = CL(HepMet)+CL(HepBile)+CL(Renal)+ ....

In vitro CLint

Whole liver CLint

Whole body CL

Hepatic metabolic CL

In vitro t1/2

Interplay between V and CL Rat pharmacokinetics

0 5 10 15Time (hours)

Elimination half-life T1/2 = ln 2 x V / CL

CL(mL/min/kg) Vss(L/kg) T½ (h) A 20 14 10 B 70 12 3 C 80 0.6 0.5

Volume of distribution Clearance Absorption

Dosing interval? Dose?

Half-life Oral bioavailability

Clearance mechanisms

Hepatic • Metabolism – phase I and phase II enzymes • Bile excretion – sinusoidal and canalicular transporters

Renal • Passive – glomerular filtration • Active transport

Extrahepatic metabolism • Intestinal CYP3A4 • Enzymes in blood • Other extrahepatic enzymes

Total CL = CLMetHep + CLMetBile + CLRenal + .......

Hepatic clearance mechanisms

Hepatocyte

Canalicular membrane

Bile canaliculus

Sinusoidal membrane

Efflux transporters

Metabolite

Drug uptake transporters

Drug metabolising enzymes

Uptake & Efflux Transporters SLCs Solute Carriers o OAT Organic Anion Transporter o OCT Organic Cation Transporter o OATP Organic Anion Transporting Polypeptides

ABC series ATP Binding Cassette transporters o MDR Multi Drug Resistance proteins o MRP Multi drug Resistance-like Proteins o White family Drosophila white eye pigment gene

Blood Hepatocyte 2015-11-08 Lena Gustavsson

From International Transporter Consortium Giacomini et al Nature Rev Drug Disc 2010 Modified marking EMA recommended transporters in blue

Drug transporters that influences drug disposition – clinical evidence

Pravastatin

3-methylglutaryl-coenzyme A (HMG-CoA) reductase inhibitor; key enzyme in cholesterol synthesis Used for the management of hypercholesterolaemia The target is in the liver Has short t1/2 (~2h), low F (17%) but successful Has a good safety profile compared to other statins WHY?

Chiral

Liver Systemic Circulation

Oral tablet

Disposition of Pravastatin

Kidney

Active secretion

Enterohepatic recirculation

OATP1B1

Substrate for OATP1B1 MRP2

Niemi, Clin.Pharm.Ther. 2010 Pasanen et al, Pharmacogenet. Genomics 2006 Search study N.Engl.J.Med. 2008

Simvastatin-induced myopathy increased due to increased plasma exposure - OATP1B1 polymorphism

In vitro, animal In vivo, human

In vitro, human

In vivo, animal

Prediction of Human PK

In vitro/in vivo correlation

Allometric scaling Vss (dog, human PPB) Absorption (rat)

Scaling CL Absorption (Caco-2) Drug-drug interactions

Species differences

Interindividual variability

Genetics

Enzyme content

Liver weight

Organ blood flow

Nature Reviews Drug Discovery 6, 140-148 (February 2007) | doi:10.1038/nrd2173 http://www.simcyp.com

Interindividual variation in drug response

CYP2D6 phenotypes in a Swedish population

CYP2D6

Codeine Prodrug

Morphine Active metabolite

CYP2D6 Poor

metabolizer No formation of

morphine Lack of

analgesia

CYP2D6 Ultra-rapid metabolizer

Formation of morphine

Overdosing Adverse events

Codeine metabolism to morphine is metabolised by CYP2D6

Does the drug inhibit Cytochrome P450? Yes = Potential drug interactions!

metabolite

Drug drug interactions - CYP inhibition

Metabolism of terfenadine

Terfenadine Almost complete first pass extraction in man

Active Metabolite Responsible for efficacy in man

CYP3A4

Ketoconazole

• Ketoconazole is an antifungal agent • Potent inhibitor of CYP3A4 • IC50 value <1µM • Antifungal dose is high (400mg twice

daily) • Circulating concentrations of

ketoconazole exceed IC50 for CYP3A4 inhibition

CYP3A4

Low circulating concentrations of metabolite

High circulating concentrations of terfenadine

Ketoconazole – terfenadine interaction

Implications of terfenadine – ketoconazole interaction

• High circulating concentrations of terfenadine • Potential to prolong QT interval of the ECG • Abnormal heart rhythm • Small numbers of patients go on to develop fatal

Torsade de Pointes (heart stops) • Led to withdrawal of terfenadine from the market • Increased questioning of Regulatory Authorities on QT

and DDIs

•CYP1A2, 2B6, 2C8, 2C9, 2C19, 2D6, 3A4

• Human recombinant P450 enzymes

• IC50 = µM

• If IC50 < 10 µM – potential interaction • If [I]/Ki >0.1 - need to address in clinical study

• Discovery: Automated fluorescence based

• Development: LC-MS/MS analysis of metabolite

substrate

product

CYP inhibition Recombinant enzymes Human liver microsomes

Induction of P450 enzymes Transcriptional regulation by nuclear hormone receptors

CYP3A CYP2C

PAH Hsp90

RXR CYP1A

PXR, GR?

- NUCLEUS -

Aryl hydrocarbon Receptor (AhR) • Ligands: Polyaromatic hydrocarbons, dioxins (TCDD), Omeprazol • Target genes: CYP1A1, CYP1A2, CYP1B1 Constitutive Androstane Receptor (CAR) • Ligands: Phenobarbital, CITCO • Target genes: CYP2B6

Pregnane X Receptor (PXR) • Ligands: Rifampin, Carbamazepine • Target genes: CYP3A4, CYP2C8, CYP2C9,

CYP2C19

• Cross-talk between nuclear hormone receptors (AhR, CAR, PXR, GR, Hnf4 etc)

DDI Risk Assessment

Perpetrator (inhibitor/inducer) • Enzyme/transporter IC50/Ki • Concentration plasma, liver,

intestine • Bound vs unbound • Time dependence • Also includes polymorphism

Victim (substrate) • Enzyme/transporter

phenotyping • Drug disposition e.g. clearance • Fraction of total elimination • Mechanistic understanding

Complex interactions – how to assess the risk? • Integration of data my modeling and simulation – PBPK • Iterative addition of new data • Other relevant information

- Co-medications - Biopharmaceutical Classification System etc

Physiology Based Pharmacokinetic (PBPK) Modelling and Simulation

Jones and Rowland-Yeo 2013

PBPK modelling and simulation A DDI example – compound A

Median % fm and fe in absence of inhibitor(s)

CYP3A4 Liver

CYP3A5 Liver

• Compound A is mainly metabolized by CYP3A4 • Assessment of DDI risks with compound A as a

”victim” • How will the plasma concentration change when co-

dosing a potent CYP3A4 inhibitor • How will the plasma concentration curve change

when co-dosing with a strong inducer of CYP3A4?

Prediction of the effect of a CYP3A4 inhibitor on the AUC of compound A

0.000E+00

050E+00

100E+00

150E+00

200E+00

250E+00

0 45 90 135 180 225 270 315 360 405 450

Time - Substrate (h)

CSys CSys with Interaction

200 mg itraconazole QD x 20 days 3 mg compound A on day 12 AUC ratio = 3.1

• Co-administration of itraconazole (potent CYP3A4 inhibitor) may result in a 3 fold increase in the AUC of compound A

• A clinical DDI study is required to investigate the effect in vivo

Simulation of plasma concentration curves – prediction of the effect of a CYP3A4 inducer

Compound A

• Co-administration of a strong CYP3A4 inducer, rifampicin, with compound A leads to a decrease in AUC to 20%

• High risk of loosing the pharmacological efficacy of compound A • Perform a clinical study to assess risk in vivo

Day 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30AF34134 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3rif 600 600 600 600 600 600 600 600 600 600 600

Compound A

Understanding and predicting drug disposition – an iterative process of data integration

Input data

Why study Drug Metabolism and PharmacoKinetics?

DRUG DISCOVERY Optimise compounds to get...

Good bioavailability – get to its target Appropriate duration (1-2 doses/day) Low potential for drug-drug interactions

…predicted to man Provide basics for understanding of

Toxicology Pharmacology

DRUG DEVELOPMENT Provide understanding of drug disposition

Preclinical animal species – tox coverage Human data

Assess the risk for drug drug interactions (DDI) Decrease risk for drug drug interactions in the clinic Impact on the design of clinical studies

Comply with guidelines from regulatory authorities

THANKS FOR LISTENING!

DRUG METABOLISM AND PHARMACOKINETICS (DMPK)

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