Proposed best practice for projects that involve modelling and simulation.
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.
Quintiles, Dublin, Ireland.
Michael
M
O'Kelly
University of Glasgow, Glasgow, Scotland.
Vladimir
V
Anisimov
Mango Solutions, Chippenham, U.K.
Chris
C
Campbell
Quintiles, Dublin, Ireland.
Sinéad
S
Hamilton
D003198:Computer Simulation; D004345:Drug Industry / Q000379:methods; D006801:Humans; D015233:Models, Statistical; D009010:Monte Carlo Method; D011786:Quality Control; D012107:Research Design
Monte Carlo technique; best practice; modelling and simulation; pre-specification; quality control