Risk-benefit trade-offs and precision utilities in phase I-II clinical trials

Area of Science:

• Clinical Pharmacology
• Biostatistics
• Oncology Drug Development

Background:

• Optimal dose identification in early-phase clinical trials is critical for therapeutic success and regulatory approval.
• Suboptimal dosing can lead to ineffective or unsafe treatments, jeopardizing subsequent trial phases and market access.
• Dose-finding requires balancing biological efficacy, toxicity, and patient quality of life.

Purpose of the Study:

• To introduce a precision phase I-II clinical trial design that accounts for both efficacy and toxicity.
• To incorporate patient covariates and prognostic subgroups for personalized dose selection.
• To optimize the risk-benefit trade-off by tailoring doses to individual patient characteristics and subgroups.

Main Methods:

• Developed a stepwise process for clinical trial design, integrating clinical practice considerations.
• Proposed a precision phase I-II design utilizing utility functions tailored to prognostic subgroups.
• The design optimizes individual patient expected utility, allowing for subgroup-specific optimal doses.

Main Results:

• The precision design enables identification of optimal doses that maximize expected utility for individual patients.
• Demonstrated that different prognostic subgroups may benefit from distinct optimal doses.
• Illustrated the application of the design in a dose-finding trial for metastatic clear cell renal cell carcinoma.

Conclusions:

• Precision dose-finding designs are essential for maximizing therapeutic benefits while minimizing risks.
• Tailoring doses to prognostic subgroups improves the risk-benefit profile in early-phase trials.
• This approach enhances the likelihood of success in subsequent clinical development and regulatory approval.