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CPT: pharmacometrics & systems pharmacology
08, 2021;10 (8): 804-825.

Scientific and regulatory evaluation of mechanistic in silico drug and disease models in drug development: Building model credibility.

Flora T Musuamba, Ine Skottheim Rusten, Raphaëlle Lesage, Giulia Russo, Roberta Bursi, Luca Emili, Gaby Wangorsch, Efthymios Manolis, Kristin E Karlsson, Alexander Kulesza, Eulalie Courcelles, Jean-Pierre Boissel, Cécile F Rousseau, Emmanuelle M Voisin, Rossana Alessandrello, Nuno Curado, Enrico Dall'ara, Blanca Rodriguez, Francesco Pappalardo, Liesbet Geris
Author Information
  1. Flora T Musuamba: EMA Modelling and Simulation Working Party, Amsterdam, The Netherlands. ORCID
  2. Ine Skottheim Rusten: EMA Modelling and Simulation Working Party, Amsterdam, The Netherlands. ORCID
  3. Raphaëlle Lesage: Biomechanics Section, KU Leuven, Leuven, Belgium.
  4. Giulia Russo: Department of Drug and Health Sciences, University of Catania, Catania, Italy.
  5. Roberta Bursi: InSilicoTrials Technologies, Milano, Italy.
  6. Luca Emili: InSilicoTrials Technologies, Milano, Italy.
  7. Gaby Wangorsch: EMA Modelling and Simulation Working Party, Amsterdam, The Netherlands.
  8. Efthymios Manolis: EMA Modelling and Simulation Working Party, Amsterdam, The Netherlands.
  9. Kristin E Karlsson: EMA Modelling and Simulation Working Party, Amsterdam, The Netherlands. ORCID
  10. Alexander Kulesza: Novadiscovery, Lyon, France.
  11. Eulalie Courcelles: Novadiscovery, Lyon, France.
  12. Jean-Pierre Boissel: Novadiscovery, Lyon, France.
  13. Cécile F Rousseau: Voisin Consulting Life Sciences, Boulogne (Paris), France.
  14. Emmanuelle M Voisin: Voisin Consulting Life Sciences, Boulogne (Paris), France. ORCID
  15. Rossana Alessandrello: AQuAS - Agency for Health Quality and Assessment of Catalonia, Catalonia, Spain.
  16. Nuno Curado: Exploristics, Belfast, UK.
  17. Enrico Dall'ara: Insigneo Institute, Sheffield University, Sheffield, UK.
  18. Blanca Rodriguez: Department of Computer Science, British Heart Foundation Centre of Research Excellence, University of Oxford, Oxford, UK. ORCID
  19. Francesco Pappalardo: Department of Drug and Health Sciences, University of Catania, Catania, Italy. ORCID
  20. Liesbet Geris: Biomechanics Section, KU Leuven, Leuven, Belgium.
PMID: 34102034 DOI: 10.1002/psp4.12669

Abstract

The value of in silico methods in drug development and evaluation has been demonstrated repeatedly and convincingly. While their benefits are now unanimously recognized, international standards for their evaluation, accepted by all stakeholders involved, are still to be established. In this white paper, we propose a risk-informed evaluation framework for mechanistic model credibility evaluation. To properly frame the proposed verification and validation activities, concepts such as context of use, regulatory impact and risk-based analysis are discussed. To ensure common understanding between all stakeholders, an overview is provided of relevant in silico terminology used throughout this paper. To illustrate the feasibility of the proposed approach, we have applied it to three real case examples in the context of drug development, using a credibility matrix currently being tested as a quick-start tool by regulators. Altogether, this white paper provides a practical approach to model evaluation, applicable in both scientific and regulatory evaluation contexts.

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Grants

  1. 777123/European Union's Horizon 2020 research
  2. 772418/ERC CoG
  3. 214290/Z/18/Z/Basic Biomedical Sciences
  4. 101017578/European Union's Horizon 2020 research
  5. 825843/European Union's Horizon 2020 research
  6. /Wellcome Trust
  7. 214290/Z/18/Z/Wellcome Trust Fellowship in
  8. NC/P001076/1/NC3Rs Infrastructure for Impact Award
  9. 101016496/European Union's Horizon 2020 research
  10. 101016503/European Union's Horizon 2020 research

MeSH Term

Computer Simulation
Drug Development
Humans
Models, Theoretical
Risk Assessment
Terminology as Topic
Journal Article Research Support, Non-U.S. Gov't
Article has an altmetric score of 134

Word Cloud

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