  Immunotherapies and targeted therapies have gained popularity due to their
promising therapeutic effects across multiple treatment areas. The focus of
early phase dose-finding clinical trials has shifted from finding the maximum
tolerated dose (MTD) to identifying the optimal biological dose (OBD), which
aims to balance the toxicity and efficacy outcomes, thereby optimizing the
risk-benefit trade-off. These trials often collect multiple pharmacokinetics
(PK) outcomes to assess drug exposure, which has shown correlations with
toxicity and efficacy outcomes but has not been utilized in the current
dose-finding designs for OBD selection. Moreover, PK outcomes are usually
available within days after initial treatment, much faster than toxicity and
efficacy outcomes. To bridge this gap, we introduce the innovative
model-assisted PKBOIN-12 design, which enhances the BOIN12 design by
integrating PK information into both the dose-finding algorithm and the final
OBD determination process. We further extend PKBOIN-12 to the TITE-PKBOIN-12
design to address the challenges of late-onset toxicity and efficacy outcomes.
Simulation results demonstrate that the PKBOIN-12 design more effectively
identifies the OBD and allocates a greater number of patients to it than
BOIN12. Additionally, PKBOIN-12 decreases the probability of selecting
inefficacious doses as the OBD by excluding those with low drug exposure.
Comprehensive simulation studies and sensitivity analysis confirm the
robustness of both PKBOIN-12 and TITE-PKBOIN-12 designs in various scenarios.
