Literature DB >> 22162317

Modelling and simulation in the pharmaceutical industry--some reflections.

Carl-Fredrik Burman1, Stig Johan Wiklund.   

Abstract

Modelling and simulation (M&S) is increasingly being applied in (clinical) drug development. It provides an opportune area for the community of pharmaceutical statisticians to pursue. In this article, we highlight useful principles behind the application of M&S. We claim that M&S should be focussed on decisions, tailored to its purpose and based in applied sciences, not relying entirely on data-driven statistical analysis. Further, M&S should be a continuous process making use of diverse information sources and applying Bayesian and frequentist methodology, as appropriate. In addition to forming a basis for analysing decision options, M&S provides a framework that can facilitate communication between stakeholders. Besides the discussion on modelling philosophy, we also describe how standard simulation practice can be ineffective and how simulation efficiency can often be greatly improved.
Copyright © 2011 John Wiley & Sons, Ltd.

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Year:  2011        PMID: 22162317     DOI: 10.1002/pst.523

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


  4 in total

1.  Using common random numbers in health care cost-effectiveness simulation modeling.

Authors:  Daniel R Murphy; Robert W Klein; Lee J Smolen; Timothy M Klein; Stephen D Roberts
Journal:  Health Serv Res       Date:  2013-02-13       Impact factor: 3.402

Review 2.  Innovations in Clinical Development in Rare Diseases of Children and Adults: Small Populations and/or Small Patients.

Authors:  Robert A Beckman; Zoran Antonijevic; Mercedeh Ghadessi; Heng Xu; Cong Chen; Yi Liu; Rui Tang
Journal:  Paediatr Drugs       Date:  2022-10-15       Impact factor: 3.930

3.  Good Practices in Model-Informed Drug Discovery and Development: Practice, Application, and Documentation.

Authors:  S F Marshall; R Burghaus; V Cosson; S Y A Cheung; M Chenel; O DellaPasqua; N Frey; B Hamrén; L Harnisch; F Ivanow; T Kerbusch; J Lippert; P A Milligan; S Rohou; A Staab; J L Steimer; C Tornøe; S A G Visser
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2016-03-14

4.  A modified weighted log-rank test for confirmatory trials with a high proportion of treatment switching.

Authors:  José L Jiménez; Julia Niewczas; Alexander Bore; Carl-Fredrik Burman
Journal:  PLoS One       Date:  2021-11-15       Impact factor: 3.240

  4 in total

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