| Summary: | Background: Escalation With Overdose Control (EWOC) designs are increasingly used to ensure dose-toxicity curve of investigational oncology drugs is efficiently characterized during dose escalation steps. We propose a novel EWOC-based method that integrates the longitudinal pharmacokinetic (PK) data of individual patients in a Bayesian forecasting exposure-safety framework. Methods: The method, called exposure-driven EWOC (ED-EWOC), relies on a population PK model coupled with a Bayesian logistic regression model to make dose recommendation for the next cohort of patients. Results: We applied ED-EWOC to a real oncology clinical trial in parallel to a traditional EWOC approach. We found that for comparable priors, ED-EWOC dose recommendations were equivalent to the one suggested by EWOC when PK is dose proportional with low inter-individual variability. Conclusion: This case example demonstrates that ED-EWOC is logistically feasible during a trial conduct when PK bioanalysis can be expedited in the dose escalation phase. Overall, we anticipate that exposure-guided Bayesian designs could benefit patients and drug developers to identify the optimal dose steps of novel compounds entering the clinic with suspected liability in PK or that exhibit large inter-individual variability.
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