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A Framework of Modeling and Simulation in Regulatory Decisions

A Framework of Modeling and Simulation in Regulatory Decisions. ACPS Nov 16, 2000 Peter Lee, Stella Machado, and Larry Lesko OCPB & OB/CDER. Terminology. Modeling: determining the mathematical equations that appropriately describe the data (mechanism of action or smoothness).

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A Framework of Modeling and Simulation in Regulatory Decisions

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  1. A Framework of Modeling and Simulation in Regulatory Decisions ACPS Nov 16, 2000 Peter Lee, Stella Machado, and Larry Lesko OCPB & OB/CDER

  2. Terminology • Modeling: determining the mathematical equations that appropriately describe the data (mechanism of action or smoothness). • Simulation: predict the outcomes under specified conditions based on models. • Clinical Trial Simulation: A specific type of simulation that predict outcomes of clinical trials. • It is not possible to review simulation without evaluating modeling process

  3. Topics for Discussion • What is the trend of modeling and simulation (M&S) in regulatory submissions? • What are regulatory experience in decision-making based on M&S ? • What are the potential applications of clinical trial simulation (CTS), specifically ? • What are the directions and next steps for evaluating the applications of simulation ?

  4. How good is the current drug development process? • 354/499 approved NME, 1980-1999 • 22% required a post-market dose change (79) • 80% were dose reduction (64) • Pre-market drug development is improvable regarding safe dose (C. Peck, CR AC, Oct 2000) • 12 year, $350-600 million (CMR Internation, 1999) • 30% NDAs non-approvable; 15% phase III failed (S. Arlington, April 2000)

  5. Protocol design Study design Knowledge extraction Investigation Simulation Data capture Reporting Data analysis Pharma 2005 Vision for Simulation - at the centre of drug development process … but can be applied more widely

  6. Molecular Structure Activity Subcellular Cellular Tissues/Organs Whole Body (animals/humans) Clinical Trials Clinical Programs Drug Portfolios Medical Care Systems Simulation - a rapidly emerging technology Discovery PreClinical Clinical Outcomes Not appropriate Not currently addressed Under Development Products Available

  7. Current Environment • Computer aided trial design (CATD) used by 17 out of top 20 PhRMA companies, and over 1200 users. • Over 15 different software packages. • Past experience with modeling & simulation to support regulatory decisions • Emerging submissions using simulation to support trial designs.

  8. Number of CTS • Over 100 (C. Peck, 10/12/00) • Therapeutic areas (D. Weiner, 9/11/00)

  9. Past Experience in M&S • New indication with new formulation • Single dose PK study • Simulate multiple dose PK for the new formulation based on single dose PK • PK Simulation • - Cisapride 20 mg • - Oxaliplatin Toxicity • BE based on PD end point (FEV) • Single dose, 4-way crossover, nasal spray • PD model parameter estimation • BE test on PD model parameter • PD Simulation • - Albuterol BE • Identify sub-population & DDI • Single and multiple doses • Multiple studies • Demographic information • 1 structure and ~10 covariate models • Population PK • - Viagra • Support the dose selection • Randomized , non-blind, multi-center, dose ranging study • 400, 600, 800, 1200 mg tid • Simulate distribution of response as a function of dose • PK/PD Simulation • - Remifentanil • - Saquinavir Dose Selection

  10. New Experiencein CTS • Physiological/Disease Models • Alzheimer’s • QTc prolongation • Diabetic • Clinical Trial Simulation • Neuropharm drug • Design phase III trial • Based on PK & phase II study • PK and PK/PD model, covariate model, assay model, drop-off, severity, statistics

  11. An Example: Drug X • Drug X showed marginal efficacy in phase II studies • Apply CTS to optimize phase III design for maximum success rate

  12. Backgrounds • Dose Regimen • Continuous IV infusion • Reason for marginal results in phase II • Drug concentration may not be optimal • Goal • Optimize the concentration in phase III

  13. Concentration-Effect Relationship 32% 9% N = ~0% 15% 12% 32%

  14. Adjust Infusion Rate

  15. Loading Dose+ Infusion

  16. Study Design/Conduct Factors • Responder/Non-responder • P450 2D6 genotype • Patient demographic • Number of patients • Timing of assay • Amount of dose adjustment • Amount of loading dose • Drop-off

  17. Three Best Designs: Number of Patients

  18. Utilities of Simulation • Predict PK under conditions not studied. • Select the optimal dose. • Study design: pop PK, exposure-response. • Evaluate change in PD due to change in formulation, dose regimen, or dosing route. • Provide bridging information for sub-populations. • Develop informative labeling language.

  19. Additional (Potential) Utilities of Simulations • Integrate preclinical, clinical pharmacology, and biopharmaceutics study results into late-phase clinical trials to ensure safe and effective study design. • Design unbiased, powered, and robust studies to maximize the treatment benefits/risk ratio in the patients. • Explore “what if” scenarios, and compare different study designs • Combine multi-discipline expertise in reviewing IND/NDA.

  20. Key Factors to Successful Simulation Projects • Prospective planning • Well-understood MOA • Robust model that are not overly sensitive to assumptions • Disease progression model • Availability of exposure-response data • Balanced inputs from relevant disciplines • How far dose it extrapolate ?

  21. Issues • No consistent approach for CDER reviewers to assure quality of M/S projects. • Other FDA guidance recommend simulation technique but not address “best practice” • Proper review of M/S submissions may require FDA standard for industry

  22. Goals of MPCC M&S WG • Assess current “state of art” of M/S • Explore potential for regulatory applications • Determine standards to assess suitability • Develop standards for M/S outputs • Develop a guidance as standards for reviewing and critiquing M&S reports • Prepare a guidance for industry for reporting M&S results

  23. Questions To ACPS Committee 1. How does industry use simulation to help the drug development process ? 2. Are modeling and simulation appropriate for drug development and regulatory decisions ? 3. What are the important attributes for a meaningful simulation practice ?

  24. Questions To ACPS Committee (cont.) 4. Do we need a FDA guidance to industry regarding the best practice of modeling and simulation for regulatory applications ? 5. If yes to # 4, what are the important information should the guidance include ? 6. If no to #4, what are the critical issues that need to be addressed before move forward to developing a guidance ?

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