Pharmacometrics-Enabled DOse OPtimization (PEDOOP) for seamless phase I-II trials in oncology

ABSTRACT

We consider a dose-optimization design for a first-in-human oncology trial that aims to identify a suitable dose for late-phase drug development. The proposed approach, called the Pharmacometrics-Enabled DOse OPtimization (PEDOOP) design, incorporates observed patient-level pharmacokinetics (PK) measurements and latent pharmacodynamics (PD) information for trial decision-making and dose optimization. PEDOOP consists of two seamless phases. In phase I, patient-level time-course drug concentrations, derived PD effects, and the toxicity outcomes from patients are integrated into a statistical model to estimate the dose-toxicity response. A simple dose-finding design guides dose escalation in phase I. At the end of the phase I dose finding, a graduation rule is used to assess the safety and efficacy of all the doses and select those with promising efficacy and acceptable safety for a randomized comparison against a control arm in phase II. In phase II, patients are randomized to the selected doses based on a fixed or adaptive randomization ratio. At the end of phase II, an optimal biological dose (OBD) is selected for late-phase development. We conduct simulation studies to assess the PEDOOP design in comparison to an existing seamless design that also combines phases I and II in a single trial.

KEYWORDS:

• Adaptive randomization
• dose finding
• optimal biological dose
• pharmacodynamics
• pharmacokinetics

Acknowledgements

We thank Michael J. Fossler for providing insightful comments.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The author(s) reported that there is no funding associated with the work featured in this article.