Application of Model-Based Adaptive Optimal Design to determine a recommended dosing regimen for combination therapy in oncology
Pierrillas P.B. (1), Fouliard S (2), Chenel M (2), Hooker A.C. (1), Friberg L.E. (1), Karlsson M.O. (1)
(1) Pharmacometrics Research Group Department of Pharmaceutical Biosciences Uppsala University, Uppsala, Sweden (2) Clinical Pharmacokinetics and Pharmacometrics Division, Servier, France
Objectives: Phase 1 trials in the context of combination therapy is a complex question differing from the case of single therapy. Instead of a simple linear dose range, both drug dosages can be changed resulting in a continuum of potential maximum tolerated doses (MTD), i.e. an MTD curve. This complexity can, potentially, be better explored using model based-approaches. Model-based adaptive optimal design (MBAOD) has shown to be less sensitive to initial model misspecification and can therefore be useful in bridging preclinical and clinical studies where prior information on model and parameters might differ [1,2]. In this work, MBAOD was applied for a First in Human study in oncology to determine the best dosing regimen for a phase 2 trial.
Methods: An adaptive optimal design was computed using the MBAOD R package [3]. The method was illustrated by the combination of paclitaxel and a hypothetical compound in development to be added on top of paclitaxel. Dose limiting toxicity was defined as grade 4 neutropenia and was simulated using a hematological toxicity model [4]. Two-compartment models with linear elimination were assumed as the true PK models for both drugs of the combination [5]. Information from preclinical studies on drug effect scaled up to human was used as prior information [6]. Optimization between dosing cohorts was made to target a reasonable probability of grade 4 neutropenia and maximal efficacy based on preclinical studies.
Results: MBAOD was successfully implemented with both 3+3 rules as stopping criteria and dose constraints for dose escalation strategy (increase by 50% at a time) for the new compound. MBAOD process allowed the change of paclitaxel dose amount and changes for both dosing schedule and dose amount for the hypothetical drug. MTD variability appears to be around 76% for the new drug (based on the total administered drug amount in a 4-week cycle) and 28% for paclitaxel. In most of the cases, the number of cohorts involved in the MBAOD didn’t exceed 5, meaning the enrolment of less patients compared to classical strategies considering separate trials for each of the potential dosing schedules.
Conclusions: Combining information from preclinical and clinical studies, this adaptive approach could improve the ability and the efficiency of phase 1 trials to identify the MTD curve for drug combinations and be applied to propose the best dosing regimen efficacy information available at the current stage of drug development.
References:
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