Open AccessCombined Analysis of Phase I and Phase II Data to Enhance the Power of Pharmacogenetic Tests
Author(s) -
Tessier A,
Bertrand J,
Chenel M,
Comets E
Publication year - 2016
Publication title -
cpt: pharmacometrics and systems pharmacology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.53
H-Index - 37
ISSN - 2163-8306
DOI - 10.1002/psp4.12054
Subject(s) - bayes' theorem , pharmacogenetics , sample size determination , lasso (programming language) , statistical power , statistics , phase (matter) , mathematics , computer science , biology , bayesian probability , genetics , genotype , chemistry , organic chemistry , world wide web , gene
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.