A Model-Based Trial Design With a Randomization Scheme Considering Pharmacokinetics Exposure for Dose Optimization in...

Area of Science:

• Oncology
• Clinical Trial Design
• Pharmacokinetics

Background:

• The goal of oncology dose-finding trials is shifting from maximum tolerated dose to optimal dose (OD) for better therapeutic benefit.
• Project Optimus and FDA draft guidance emphasize incorporating pharmacokinetics (PK) alongside safety and efficacy for OD selection.
• PK data offers a potentially faster alternative to efficacy data for predicting minimum efficacious dose.

Purpose of the Study:

• To propose a novel model-based trial design for oncology dose optimization.
• To implement a randomization scheme based on pharmacokinetic (PK) outcomes.
• To evaluate the proposed design's effectiveness in selecting the optimal dose (OD).

Main Methods:

• Development of a model-based trial design incorporating PK-guided randomization.
• Simulation studies to compare the proposed design against existing methods.
• Evaluation based on the percentage of correct OD selection and patient allocation to OD.

Main Results:

• The proposed model-based design demonstrated advantages in selecting the correct optimal dose (OD).
• The design showed improved average patient allocation to the optimal dose (OD) across various scenarios.
• Simulation results support the efficacy of PK-based randomization in dose optimization.

Conclusions:

• The proposed model-based trial design offers an effective approach for oncology dose optimization.
• Utilizing PK outcomes in randomization can enhance the selection of optimal doses (OD) in clinical trials.
• This design aligns with the evolving paradigm of dose selection in oncology drug development.