S B Duffull1, F Mentré, L Aarons. 1. School of Pharmacy and Pharmaceutical Sciences, University of Manchester, UK. sduffull@pharmacy.uq.edu.au
Abstract
PURPOSE: To design a parsimonious population pharmacodynamic experiment that has the same or greater efficiency than that provided by two phase I studies. METHODS: The design was based on optimization of the population Fisher information matrix. Options for optimization were (1) determination of the optimal sampling times for each group ("group" represents a group of subjects that have identical design characteristics), (2) determination of the optimal doses for each group, and (3) determination of the optimal group structure. RESULTS: (1) Optimizing the sampling times, while retaining only four unique times per group, provided a more parsimonious experiment with the same efficiency as the original "study" that involved on average 10 samples per subject. Splitting sampling times between the first dose and a steady-state dose gave the most informative design. (2) The optimal dose was the same in all groups and was the upper bound of the dose range. (3) The optimal population design consisted of only one group with four unique sampling times that are the same for all subjects. CONCLUSION: A population pharmacodynamic trial design is presented that is more parsimonious than the original study and would be appropriate for inclusion in a premarketing clinical study.
PURPOSE: To design a parsimonious population pharmacodynamic experiment that has the same or greater efficiency than that provided by two phase I studies. METHODS: The design was based on optimization of the population Fisher information matrix. Options for optimization were (1) determination of the optimal sampling times for each group ("group" represents a group of subjects that have identical design characteristics), (2) determination of the optimal doses for each group, and (3) determination of the optimal group structure. RESULTS: (1) Optimizing the sampling times, while retaining only four unique times per group, provided a more parsimonious experiment with the same efficiency as the original "study" that involved on average 10 samples per subject. Splitting sampling times between the first dose and a steady-state dose gave the most informative design. (2) The optimal dose was the same in all groups and was the upper bound of the dose range. (3) The optimal population design consisted of only one group with four unique sampling times that are the same for all subjects. CONCLUSION: A population pharmacodynamic trial design is presented that is more parsimonious than the original study and would be appropriate for inclusion in a premarketing clinical study.
Authors: I Ragueneau; C Laveille; R Jochemsen; G Resplandy; C Funck-Brentano; P Jaillon Journal: Clin Pharmacol Ther Date: 1998-08 Impact factor: 6.875
Authors: Stefanie Hennig; Timothy H Waterhouse; Scott C Bell; Megan France; Claire E Wainwright; Hugh Miller; Bruce G Charles; Stephen B Duffull Journal: Br J Clin Pharmacol Date: 2006-10-30 Impact factor: 4.335