Marc R. Gastonguay, Ph.D. - CDE · METRUM RESEARCH GROUP & METRUM INSTITUTE, 2012 Application of Population Pharmacokinetic and Pharmacodynamic Modeling and Simulation Marc R. Gastonguay,

METRUM RESEARCH GROUP & METRUM INSTITUTE, 2012

Application of Population Pharmacokinetic and Pharmacodynamic Modeling and Simulation Marc R. Gastonguay, Ph.D.

Scientific Director, Metrum Institute [email protected] President & CEO, Metrum Research Group [email protected]

2 METRUM RESEARCH GROUP & METRUM INSTITUTE, 2012

Overview

Ø Population PK-PD in Modeling/Simulation Context

Ø General Types of Applications

Ø Specific Examples ►  Dosing in Neonates, Infants and Children ►  Understanding Clinical Pharmacology/Drug Metabolism ►  Impact of Adherence to Prescribed Dosing Regimen ►  Impact of Renal Impairment ►  Dose Selection ►  Projection of Target Response (Efficacy) ►  Projection of Toxicity Response ►  Clinical Trial Simulation

Ø  Further Considerations


General Types of Applications of Population PK-PD

Ø Descriptive reflection of population ►  Covariate effects ►  PK-PD relationship

Ø Dose and dosing regimen selection

Ø Dosing and labeling for special populations Ø Biomarker PK-PD for internal decision-making

►  Target attainment ►  Translation to clinical outcomes

Ø Disease Progression Ø Simulation of expected response

►  Assessment of target profile (efficacy and toxicity) Ø Clinical trial simulation

►  Optimize design


Evolution of Modeling/Simulation in Drug Development

1980 1990 2000 2010 2020

Individual Dosing & TDM

Population PK Software

M&S to Explore Patient Dose Regimens

M&S for Trial Design Decision-Making (MMF)

Multiscale Systems Biology/Pharmacology

Methods & Algorithms

FDA PKPD Conferences, NMusers, PAGE, etc.

Trial Sim for Teaching Stats

Sim for Training Pharmacologists

Cloud Computing MC Sim BE Study Designs

Simulation to Explore Labeled Dosing

MBMA of Therapeutic Areas

Probability of Technical Success

Dose-Selection

Adaptive Trial Designs

Comparative Effectiveness Trial Simulation Software

PBPK Simulation: Tox

PBPK Simulation, ADME


M&S-Based Drug Development Today (?)

Cross-Program M&S Platforms/Activities (Therapeutic Area Model Based Meta-Analysis, Multiscale Systems Models,

Disease Progression Models, Portfolio Lead Optimization)

Trial Simulations to Optimize Ph 2/3 Designs

Bayesian Analysis & Adaptive Designs, Dose Selection

Pop PKPD M&S for Labeling Support

Preclinical & Early Development PK-PD, MTD, Biomarkers

Prob. Technical Success, Proof of Concept

Comparative Effectiveness

Building Knowledge in Drug Development


Understand the Clinical/Development Questions

Should We Invest Further?!

Will this trial succeed?

What’s the target product profile?

Is toxicity a concern at this dose?


Quantitative Decision Criteria

Less than or Equal to 5 mmHg!

Less Than 12% Incidence Rate

effect size of + 3 points no more than 10 msec


dose (mg/kg)

prob

abilit

y

0.00

0.05

0.10

0 10 20 30

17 % 1 %

Focus M&S to Address Relevant Quantitative Questions

Expected Toxicity Incidence

Given our current state of knowledge… There is a 17% probability of tox. incidence being greater than 12% But.. the probability of an incidence rate greater than 30% is very low.

(Bayesian) model-based probability distribution


Some Examples


Dosing of Fluconazole in Neonates

Wade et al. Pediatr Infect Dis J 2009; 28: 717–723



Wade et al. Pediatr Infect Dis J 2009;28: 717–723



Wade et al. ANTIMICROBIAL AGENTS AND CHEMOTHERAPY, Nov. 2008, p. 4043–4049.


Pediatric Tinzaparin Pharmacodynamics

Gastonguay et al. Optimizing a Bayesian dose-adjustment scheme for a pediatric trial: A simulation study. in Simulation for designing clinical trials: A pharmacokinetic-pharmacodynamic modeling perspective. Marcel Dekker, NY, 2003.


Pediatric Tinzaparin Pharmacodynamics

Gastonguay et al. Optimizing a Bayesian dose-adjustment scheme for a pediatric trial: A simulation study. in Simulation for designing clinical trials: A pharmacokinetic-pharmacodynamic modeling perspective. Marcel Dekker, NY, 2003.

Weight based: Dose = AdultDose x weight/70 kg Allometric: Dose = AdultDose x (weight/70 kg)0.75


Dexmedetomidine Pop PK in Infants

Su et al. Anesth Analg 2010;110:1383–92


Pediatric Dosing Rules for Pantoprazole

Knebel et al. J Clin Pharmacol. 2011 Mar;51(3):333-45. Epub 2010 May 19.


Chlorzoxazone Metabolic Ratio and Renal Function

Nolin et al. Clin Pharmacol Ther 2003;74:555-68.


Adherence Effect on Pop PK

Bies et al. Am J Geriatr Psychiatry 2002; 10:696–705


Adherence Effect on Pop PK

Bies et al. Am J Geriatr Psychiatry 2002; 10:696–705


Varenicline PK-PD, Special Populations

Ravva et al. Br J Clin Pharmacol. 2009 Nov;68(5):669-81.


Varenicline PK-PD, Dose Selection

Ravva et al. Clin Pharmacol Ther. 2010 Mar;87(3):336-44. Epub 2010 Jan 27.


Istradefylline Dose Selection in Parkinson’s Disease

Knebel et al. J Clin Pharmacol. 2011 Dec 12. [Epub ahead of print]


PK-PD of Fc-Osteoprotegrin and Projected Response

Zierhut et al. J Pharmacokinet Pharmacodyn. 2008 Aug;35(4):379-99. Epub 2008 Jul 17.


Tolterodine QTc Prolongation

Sweeney et al. Drug Discoveries & Therapeutics. 2010; 4(1):44-53.


Alzheimer’s Biomarker-Based No-Go Decision - Quantitative target: beta

amyloid response (area above effect curve) defined based on MBMA of published data.

- PD model for biomarker developed from NCE data.

- Posterior probability of achieving target was too low given tox. coverage

-  Terminated development

Ruolun Qiu1, Susan Willavize1, Terrence Fullerton1, Marc R. Gastonguay2. Modeling and Simulation of Plasma Aβ in Human After Multiple Oral Doses of PF-3084014, a Potent Gamma Secretase Inhibitor. ACOP, 2009.


Brief History of Published AD Progression Models - Disease progression model published by Holford and Peace1

E[S(t)] = S(0) + α � t + EPBO(t) + EDRUG(Concentration)

- Ito et al2 developed meta-analytic version of this model (based on summary data) and applied it to new data. Ø  Inclusion of new covariates (e.g. baseline severity) and modeled

drug effect directly as a function of time and dose

E[S(t)] = S(0) + α � t + EPBO(t) + EDRUG(t, Dose)

- Gillespie et al3 Bayesian Model-Based Meta Analysis Ø  Simultaneous modeling of summary-level and patient-level data,

constrains model to capped scale.

1 Holford, N.H. and Peace, K.E. Methodologic aspects of a population pharmacodynamic model for cognitive effects in alzheimer patients treated with tacrine. Proceedings of the National Academy of Sciences of the United States of America 89 (1992):11466–11470. 2 Disease progression meta-analysis model in Alzheimer's disease. Kaori Ito, Sima Ahadieh, Brian Corrigan, Jonathan French, Terence Fullerton, Thomas Tensfeldt, Alzheimer's Disease Working Group Alzheimer's & Dementia: The Journal of the Alzheimer's Association January 2010 (Vol. 6, Issue 1, Pages 39-53) 3 http://metrumrg.com/images/stories/publications/acop2009-adascog.pdf


Disease Progression: ADAScog

Week

Expe

cted

AD

AS−c

og

20

22

24

26

28

30

0 20 40 60 80

Natural ProgressionPlaceboDonepezil 10 mg QD50% DM effect25% DM effect


Fixed Effects Models for Placebo and Symptomatic Drug


AD Proof of Concept (PoC) Trial Simulation Target product response for change in ADAScog score at 6 months:

•  must have -2.5 units •  wish for -4 units


Exploring PoC AD Trial Design Options Parallel Cross-Over


Exploring PoC AD Trial Design Options

Given quantitative criteria, explore performance under different assumptions about true drug characteristics.


Summary

- Start with clinical/development questions

- Express decision criteria quantitatively

- Model development is only part of the effort

- Use simulation to explore possible decision paths


Acknowledgements

- Metrum Research Group Staff (www.metrumrg.com)

- Industry & Academic Collaborators

Documents

Marc R. Gastonguay, Ph.D. - CDE · METRUM RESEARCH GROUP & METRUM INSTITUTE, 2012 Application of Population Pharmacokinetic and Pharmacodynamic Modeling and Simulation Marc R. Gastonguay,