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Statistical Methods in Medical Research
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Population modelling in drug development

Lewis Sheiner

Departments of Laboratory Medicine, Biopharmaceutical Sciences, and Medicine, University of California, San Fransisco, California, USA

Jon Wakefield

Department of Epidemiology and Public Health, Imperial College of Medicine at St Mary's, London, UK, j.c.wakefield{at}ic.ac.uk

In this paper we discuss the vital role that population (hierarchical) modelling can play within the drug development process. Specifically, population pharmacokinetic/pharmacodynamic models can provide reliable predictions of an individualized dose-exposure-response relationship. A predictive model of this kind can be used to simulate and hence design clinical trials, find initial dosage regimens satisfying an optimality criterion on the population distribution of responses, and individualized regimens satisfying such a criterion conditional on individual features, such as sex, age, etc. Throughout we emphasize prediction and advocate mechanistic as opposed to empirical modelling, and argue that the Bayesian approach is particularly natural in this setting.

Statistical Methods in Medical Research, Vol. 8, No. 3, 183-193 (1999)
DOI: 10.1177/096228029900800302
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