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Modelling and simulation in the pharmaceutical industry—some reflections
Author(s) -
Burman CarlFredrik,
Wiklund Stig Johan
Publication year - 2011
Publication title -
pharmaceutical statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.421
H-Index - 38
eISSN - 1539-1612
pISSN - 1539-1604
DOI - 10.1002/pst.523
Subject(s) - frequentist inference , computer science , pharmaceutical industry , management science , process (computing) , data science , bayesian probability , operations research , risk analysis (engineering) , bayesian inference , artificial intelligence , engineering , medicine , pharmacology , operating system
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.