title: Modelling and simulation in the pharmaceutical industry--some reflections.
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.
authors.affiliation: Statistics & Programming, AstraZeneca R&D, Mölndal, Sweden. carl-fredrik.burman@astrazeneca.com
authors.forename: Carl-Fredrik
authors.initials: CF
authors.lastname: Burman
authors.forename: Stig Johan
authors.initials: SJ
authors.lastname: Wiklund
mesh_terms: D003198:Computer Simulation / Q000706:statistics & numerical data*; D004305:Dose-Response Relationship, Drug; D055808:Drug Discovery / Q000379:methods* / Q000706:statistics & numerical data; D004345:Drug Industry / Q000706:statistics & numerical data*; D006801:Humans; D015233:Models, Statistical