Biomarker-based precision dose finding for immunotherapy combined with radiotherapy.

Area of Science:

• Oncology
• Clinical Trial Design
• Immunotherapy

Background:

• Sequential administration of immunotherapy following radiotherapy (immunoRT) shows promise.
• Existing clinical trial designs are not optimized for immunoRT's unique characteristics.

Purpose of the Study:

• To propose a novel Bayesian phase I/II clinical trial design for immunoRT.
• To identify an optimal, personalized dose of immunotherapy administered after standard-dose radiotherapy.
• To tailor dosing based on individual patient PD-L1 expression levels.

Main Methods:

• A Bayesian phase I/II design integrating immunotherapy with radiotherapy.
• Modeling of immune response, toxicity, and efficacy as functions of dose and PD-L1 expression (baseline and post-RT).
• A two-stage dose-finding algorithm utilizing a utility function to determine personalized optimal doses.

Main Results:

• Simulation studies demonstrate favorable operating characteristics for the proposed design.
• The design shows a high probability of identifying the personalized optimal dose for patients.

Conclusions:

• The proposed Bayesian design offers a robust framework for immunoRT clinical trials.
• Personalized dosing based on PD-L1 expression can optimize treatment strategies in immunoRT.