Model-based phase I designs incorporating toxicity and efficacy for single and dual agent drug combinations: methods and challenges.
Novel therapies are challenging the standards of drug development. Agents with specific biologic targets, unknown dose-efficacy curves, and limited toxicity mandate novel designs to identify biologically optimal doses. We review two model-based designs that utilize either a proportional odds model or a continuation ratio model to identify an optimal dose of a single or two-agent combination in a Phase I setting utilizing both toxicity and efficacy data. A continual reassessment method with straightforward dose selection criterion using accumulated data from all patients treated until that time point is employed while allowing for separate toxicity and efficacy curves for each drug in a two-drug setting. The simulation studies demonstrate considerable promise, at least theoretically, in the ability of such model-based designs to identify the optimal dose. Despite such favorable operating characteristics, there are several pragmatic challenges that hinder the routine implementation of such model-based designs in practice. We review and offer practical solutions to potentially overcome some of these challenges. The acceptance and integration of these designs in practice may be quicker and easier if they are developed in concert with a clinical paradigm.
Mandrekar
Sumithra J
SJ
Department of Health Sciences Research, Mayo Clinic, Rochester, MN 55905, USA. mandrekar.sumithra@mayo.edu
Qin
Rui
R
Sargent
Daniel J
DJ
D001499:Bayes Theorem; D017321:Clinical Trials, Phase I as Topic / Q000379:methods*; D003198:Computer Simulation; D004305:Dose-Response Relationship, Drug; D004338:Drug Combinations; D064420:Drug-Related Side Effects and Adverse Reactions; D006801:Humans; D015233:Models, Statistical
D004338:Drug Combinations