1. MIDD: Perspectives and Possibilities
Dionne L. Price PhD
Director, Division of Biometrics IV
Office of Biostatistics/OTS/FDA

2. Modeling and Simulation

3. Model-based Drug Development

4. Model-Informed Drug Development
“quantitative framework for prediction and extrapolation, centered on knowledge and inference generated from integrated models of compound, mechanism, and disease level data and aimed at improving the quality, efficiency, and cost effectiveness of decision making”
*EFPIA MID3 Workgroup, CPT Pharmacometrics Syst Pharamcol. (2016) 5,

5. Organizational Structure

6. Modeling and Simulation
A Challenge
“It is a great challenge that in applying M&S, we should preferable be skilled in several scientific disciplines: statistics, mathematics, computations, pharmacology, medicine, economic, and others.” (Burman and Wiklund, 2011)
Statistics
Pharmacology
Modeling and Simulation
Medicine
Computations

7. Some Areas of Potential Collaboration
Biomarker qualification/validation
Disease progression models
Trial design
Meta-analysis
Sub-group analyses for confirmatory purposes
Dose Selection

8. PDUFA VI Pilot Programs
Enhancing regulatory decision tools to support drug development and review
Complex Innovative Designs Pilot Program
Led by the Office of Biostatistics
Includes designs involving complex adaptations, Bayesian methods, or other features requiring simulations to determine operating characteristics
Model Informed Drug Development Pilot Program
Led by the Office of Clinical Pharmacology
Excludes aforementioned designs

9. PDUFA VI Complex Innovative Design (CID)
Develop staff capacity
Conduct a pilot program
Convene a public workshop
Publish draft guidance
Develop or revise relevant MAPPs, SOPPs, and/or review templates
Objective: To facilitate the advancement and use of complex innovative designs

10. PDUFA VI Model Informed Drug Development (MIDD)
Develop staff capacity
Conduct a pilot program
Convene a series of workshops
Publish draft guidance
Develop or revise relevant MAPPs, SOPPs, and/or review templates
Objective: To facilitate the development and application of MIDD approaches

11. Model Informed Drug Development
*Excludes designs involving complex adaptations, Bayesian methods, or other features
requiring simulations to determine the operating characteristics

12. MIDD Federal Register Notice

13. MIDD Pilot Program: Priority areas
Dose selection or estimation (e.g. for dose/dosing regimen selection or refinement)
Clinical trial simulation (e.g. based on drug-trial-disease models to inform the duration of the trial, select appropriate response measures, predict outcomes)
Predictive or mechanistic safety evaluation (e.g. use of systems pharmacology/mechanistic models for predicting safety or identifying critical biomarker of interest)

14. MCP-Mod Fit for Purpose: A collaborative effort

15. Oncology dose finding: collaborative example

16. Summary There is a recognition of the utility and benefits of MIDD
MIDD requires a multi-disciplinary effort and represents multiple opportunities/possibilities for collaboration
Continued/increased dialogue and education are necessary
Internal and external strategies will be needed to bridge the gaps