Joint detection of important biomarkers and optimal dose-response model using penalties.
We propose a method to jointly detect influential biomarkers and estimate how they change with dose. The assessment is made in dose-ranging trials collecting multiple outcomes for efficacy, safety, pharmacokinetics or pharmacodynamics. We regress all these outcomes versus a non-parametric transformation of the dose. The regression coefficients and the parameters from the dose-response model are simultaneously estimated using a penalized alternating least-squares method. We illustrate the technique with a phase I clinical trial and a metabonomic experiment in rats.
Vandenhende
F
F
Global Statistics, Eli Lilly and Company, Mont-Saint-Guibert, Belgium. francois@clinbay.com
Eilers
P
P
Ledent
E
E
Renard
D
D
Tibaldi
F
F
D000818:Animals; D015415:Biomarkers / Q000032:analysis*; D056486:Chemical and Drug Induced Liver Injury; D002986:Clinical Trials as Topic / Q000379:methods; D003198:Computer Simulation; D004051:Diethylhexyl Phthalate / Q000493:pharmacokinetics / Q000633:toxicity / Q000652:urine; D004305:Dose-Response Relationship, Drug; D006801:Humans; D016018:Least-Squares Analysis; D008107:Liver Diseases / Q000378:metabolism; D008954:Models, Biological; D051381:Rats
D015415:Biomarkers; D004051:Diethylhexyl Phthalate