Good Practices in Model Informed Drug Discovery and Development (MID3): Practice, Application, Documentation and Reporting
EFPIA MID3 workgroup : Scott Marshall (5) Rolf Burghaus (1) Valerie Cosson (2) S. Y. Amy Cheung (3) Marylore Chenel (11) Oscar DellaPasqua (4) Nicolas Frey(2) Bengt Hamren (3) Lutz Harnisch (5) Frederic Ivanow (6) Thomas Kerbusch (7) Joerg Lippert (1) Peter Milligan (5) Solange Rohou (3) Alexander Staab (8) Jean Louis Steimer (9) Christoffer Tornoe (10) Sandra Visser (7)
(1) Bayer (2) F. Hoffmann-La Roche (3) AstraZeneca (4) GlaxoSmithKline (5) Pfizer (6) Johnson & Johnson (7) Merck/MSD (8) Boehringer Ingelheim Pharma GmbH & Co. KG (9) Novartis (10) Novo Nordisk (11) Servier
Objectives: The workgroup evolved from the original 2011 EFPIA /EMA M&S workshop committee. The aim was to continue a dialogue with EMA MSWG colleagues [1], realise EFPIA’s commitments and enable an era of Model Informed Drug Discovery and Development (MID3) and Model Informed Regulatory Assessment [2-6].
Methods :A focus for the working group was the development of a “Good Practice and Standards” guidance document. Its aim was to promote a wider understanding of how MID3 could be applied across R&D (Part 1) and enhance both the clarity and efficiency in the reporting of MID3 analyses for regulatory interactions (Part 2). Detailed technical content was considered out of scope.
Results: Part 1 provides the rationale behind the MID3 paradigm, from utility in knowledge integration to provision of a framework to aid extrapolation (high regulatory impact situations). This section also provides a “good practice” grid to aid identification of pertinent questions across different themes (including Risk/Benefit and commercial viability) and activity levels (related to compound, mechanism and disease) to facilitate strategic planning of MID3 activities. A high level comparison of potential modelling approaches (from Empirical to systems pharmacology) is additionally outlined. Finally, examples illustrating this framework in practice, highlighting the internal impact across different application sub-types (from Selection and Validation of Drug Targets to Commercial Strategies) are described.
Part 2 outlines good practices in the documentation for analyses, covering some guiding principles, documentation in regulatory submissions and QA\QC. Consideration is given to the key components of the analysis plan, simulation plan and report, with suggestions for an appropriate and acceptable level of documentation (“fit for purpose“ ). An important recommendation is for an explicit statement of the underlying Stat/Math, Physiological, Pharmacological and Disease related assumptions and their evaluation, both in the planning and reporting of analyses. Members of EMA MSWG were involved in the review of the document and are aligned with the covered principles.
Conclusions:Through increasing the consistency, quality and transparency of conduct and reporting of MID3 activities, we believe this document will be an important step in achieving a greater harmonisation of these approaches across the Pharmaceutical Industry and in its interactions with Regulatory Agencies.
References:
[1] Shepard T , Brogren J, Manolis E and Hemmings R. How European Regulators Are Facilitating the Use of Modelling and Simulation: MSWG History, Activity and Future PAGE 2014
[2] Manolis E, Rohou S, Hemmings R, Salmonson T, Karlsson M, Milligan PA. The Role of Modeling and Simulation in Development and Registration of Medicinal Products:Output From the EFPIA/EMA Modeling and Simulation Workshop. CPT Pharmacometrics Syst Pharmacol. 2013 Feb 27;2:e31
[3] Visser SA, Manolis E, Danhof M, Kerbusch T. Modeling and simulation at the interface of nonclinical and early clinical drug development. CPT Pharmacometrics Syst Pharmacol. 2013 Feb 27;2:e30.
[4] Marshall SF, Hemmings R, Josephson F, Karlsson MO, Posch M, Steimer JL. Modeling and simulation to optimize the design and analysis of confirmatory trials, characterize risk-benefit, and support label claims. CPT Pharmacometrics Syst Pharmacol. 2013 Feb 27;2:e27.
[5] Harnisch L, Shepard T, Pons G, Della Pasqua O. Modeling and simulation as a tool to bridge efficacy and safety data in special populations. CPT Pharmacometrics Syst Pharmacol. 2013 Feb 27;2:e28
[6] Staab A, Rook E, Maliepaard M, Aarons L, Benson C. Modeling and simulation in clinical pharmacology and dose finding. CPT Pharmacometrics Syst Pharmacol. 2013 Feb 27;2:e29
