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Immunotherapies and targeted therapies have gained popularity due to theirpromising therapeutic effects across multiple treatment areas. The focus ofearly phase dose-finding clinical trials has shifted from finding the maximumtolerated dose (MTD) to identifying the optimal biological dose (OBD), whichaims to balance the toxicity and efficacy outcomes, thereby optimizing therisk-benefit trade-off. These trials often collect multiple pharmacokinetics(PK) outcomes to assess drug exposure, which has shown correlations withtoxicity and efficacy outcomes but has not been utilized in the currentdose-finding designs for OBD selection. Moreover, PK outcomes are usuallyavailable within days after initial treatment, much faster than toxicity andefficacy outcomes. To bridge this gap, we introduce the innovativemodel-assisted PKBOIN-12 design, which enhances the BOIN12 design byintegrating PK information into both the dose-finding algorithm and the finalOBD determination process. We further extend PKBOIN-12 to the TITE-PKBOIN-12design to address the challenges of late-onset toxicity and efficacy outcomes.Simulation results demonstrate that the PKBOIN-12 design more effectivelyidentifies the OBD and allocates a greater number of patients to it thanBOIN12. Additionally, PKBOIN-12 decreases the probability of selectinginefficacious doses as the OBD by excluding those with low drug exposure.Comprehensive simulation studies and sensitivity analysis confirm therobustness of both PKBOIN-12 and TITE-PKBOIN-12 designs in various scenarios.

PKBOIN-12: A Bayesian optimal interval Phase I/II design incorporating pharmacokinetics outcomes to find the optimal biological dose