EPSRC Reference: |
GR/L10437/01 |
Title: |
BAYESIAN POPULATION PHARMACOKINETIC & PHARMACODYNAMIC MODELLING: IMPLEMENTATION AND MODEL SELECTION |
Principal Investigator: |
Wakefield, Dr J |
Other Investigators: |
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Researcher Co-Investigators: |
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Project Partners: |
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Department: |
Mathematics |
Organisation: |
Imperial College London |
Scheme: |
Standard Research (Pre-FEC) |
Starts: |
01 October 1996 |
Ends: |
31 March 1999 |
Value (£): |
123,811
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EPSRC Research Topic Classifications: |
Statistics & Appl. Probability |
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EPSRC Industrial Sector Classifications: |
Pharmaceuticals and Biotechnology |
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Related Grants: |
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Panel History: |
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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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Key Findings |
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Potential use in non-academic contexts |
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Impacts |
Description |
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Summary |
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Date Materialised |
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Sectors submitted by the Researcher |
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Project URL: |
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Further Information: |
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Organisation Website: |
http://www.imperial.ac.uk |