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Details of Grant 

EPSRC Reference: GR/L10437/01
Title: BAYESIAN POPULATION PHARMACOKINETIC & PHARMACODYNAMIC MODELLING: IMPLEMENTATION AND MODEL SELECTION
Principal Investigator: Wakefield, Dr J
Other Investigators:
Spiegelhalter, Professor D Best, Professor NG
Researcher Co-Investigators:
Project Partners:
GlaxoSmithKline plc (GSK) Pfizer
Department: Mathematics
Organisation: Imperial College London
Scheme: Standard Research (Pre-FEC)
Starts: 01 October 1996 Ends: 31 March 1999 Value (£): 123,811
EPSRC Research Topic Classifications:
Statistics & Appl. Probability
EPSRC Industrial Sector Classifications:
Pharmaceuticals and Biotechnology
Related Grants:
Panel History:  
Summary on Grant Application Form
Drug regulatory authorities in both Europe and the US have recently stressed importance of population modelling. Pharmacokinetic (PK) models describe the time course of a drug in a particular subject whilst pharmacodynamic (PD) models relate a response measure to concentration/dose. Population models attempt to identify and quantify sources of between-individual variability in observed data. From a statistical perspective population models are hierarchical models involving a nonlinear first stage. The analysis of these models is difficult due to nonlinearity and sparsity of data. We aim to develop new diagnostic techniques for the assessment of modelling assumptions. In particular, it is crucial to detect subpopulations of patients who exhibit altered PK behaviour, using biological and prior information. Finally, the use of such models is dependent on the availability of efficient methods for implementation. We will devise novel Markov chain Monte Carlo methods and incorporate these within the BUGS software developed at the MRC Biostatistics Unit in Cambridge.
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