Literature DB >> 27809406

Proposed best practice for projects that involve modelling and simulation.

Michael O'Kelly1, Vladimir Anisimov2, Chris Campbell3, Sinéad Hamilton1.   

Abstract

Modelling and simulation has been used in many ways when developing new treatments. To be useful and credible, it is generally agreed that modelling and simulation should be undertaken according to some kind of best practice. A number of authors have suggested elements required for best practice in modelling and simulation. Elements that have been suggested include the pre-specification of goals, assumptions, methods, and outputs. However, a project that involves modelling and simulation could be simple or complex and could be of relatively low or high importance to the project. It has been argued that the level of detail and the strictness of pre-specification should be allowed to vary, depending on the complexity and importance of the project. This best practice document does not prescribe how to develop a statistical model. Rather, it describes the elements required for the specification of a project and requires that the practitioner justify in the specification the omission of any of the elements and, in addition, justify the level of detail provided about each element. This document is an initiative of the Special Interest Group for modelling and simulation. The Special Interest Group for modelling and simulation is a body open to members of Statisticians in the Pharmaceutical Industry and the European Federation of Statisticians in the Pharmaceutical Industry. Examples of a very detailed specification and a less detailed specification are included as appendices.
Copyright © 2016 John Wiley & Sons, Ltd.

Entities:  

Keywords:  Monte Carlo technique; best practice; modelling and simulation; pre-specification; quality control

Mesh:

Year:  2016        PMID: 27809406     DOI: 10.1002/pst.1789

Source DB:  PubMed          Journal:  Pharm Stat        ISSN: 1539-1604            Impact factor:   1.894


  3 in total

1.  Model Description Language (MDL): A Standard for Modeling and Simulation.

Authors:  Mike K Smith; Stuart L Moodie; Roberto Bizzotto; Eric Blaudez; Elisa Borella; Letizia Carrara; Phylinda Chan; Marylore Chenel; Emmanuelle Comets; Ronald Gieschke; Kajsa Harling; Lutz Harnisch; Niklas Hartung; Andrew C Hooker; Mats O Karlsson; Richard Kaye; Charlotte Kloft; Natallia Kokash; Marc Lavielle; Giulia Lestini; Paolo Magni; Andrea Mari; France Mentré; Chris Muselle; Rikard Nordgren; Henrik B Nyberg; Zinnia P Parra-Guillén; Lorenzo Pasotti; Niels Rode-Kristensen; Maria L Sardu; Gareth R Smith; Maciej J Swat; Nadia Terranova; Gunnar Yngman; Florent Yvon; Nick Holford
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2017-07-12

2.  Using simulation studies to evaluate statistical methods.

Authors:  Tim P Morris; Ian R White; Michael J Crowther
Journal:  Stat Med       Date:  2019-01-16       Impact factor: 2.497

3.  Model-Informed Drug Discovery and Development: Current Industry Good Practice and Regulatory Expectations and Future Perspectives.

Authors:  Scott Marshall; Rajanikanth Madabushi; Efthymios Manolis; Kevin Krudys; Alexander Staab; Kevin Dykstra; Sandra A G Visser
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2019-02-01
  3 in total

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