Combined Analysis of Phase I and Phase II Data to Enhance the Power of Pharmacogenetic Tests

We show through a simulation study how the joint analysis of data from phase I and phase II studies enhances the power of pharmacogenetic tests in pharmacokinetic (PK) studies. PK profiles were simulated under different designs along with 176 genetic markers. The null scenarios assumed no genetic ef...

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Bibliographic Details
Published in:CPT: pharmacometrics and systems pharmacology 2016-03, Vol.5 (3), p.123-131
Main Authors: Tessier, A, Bertrand, J, Chenel, M, Comets, E
Format: Article
Language:English
Subjects:
Clinical Trials, Phase I as Topic
Clinical Trials, Phase II as Topic
Computer Simulation
Design
Genetic Variation
Genetics
Humans
Life Sciences
Metabolic Clearance Rate
Nonlinear Dynamics
Original
Pharmaceutical industry
Pharmaceutical sciences
Pharmacogenetics - methods
Power
Quantitative Methods
Sample Size
Studies
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Summary:We show through a simulation study how the joint analysis of data from phase I and phase II studies enhances the power of pharmacogenetic tests in pharmacokinetic (PK) studies. PK profiles were simulated under different designs along with 176 genetic markers. The null scenarios assumed no genetic effect, while under the alternative scenarios, drug clearance was associated with six genetic markers randomly sampled in each simulated dataset. We compared penalized regression Lasso and stepwise procedures to detect the associations between empirical Bayes estimates of clearance, estimated by nonlinear mixed effects models, and genetic variants. Combining data from phase I and phase II studies, even if sparse, increases the power to identify the associations between genetics and PK due to the larger sample size. Design optimization brings a further improvement, and we highlight a direct relationship between η‐shrinkage and loss of genetic signal.
ISSN:2163-8306
2163-8306
DOI:10.1002/psp4.12054