Toxicity Adaptive Lists Design: A Practical Design for Phase I Drug Combination Trials in Oncology

Area of Science:

• Oncology
• Clinical Trial Design
• Pharmacometrics

Background:

• Phase I oncology trials are critical for evaluating new drug combinations.
• Accurate identification of the maximum tolerated dose (MTD) is essential for patient safety and efficacy.
• Existing dose-finding methods have limitations in managing toxicity and efficiency.

Purpose of the Study:

• To introduce a novel algorithmic approach, the Toxicity Adaptive Lists Design (TALE), for phase I oncology drug combination trials.
• To provide a flexible and implementable design for dose escalation and de-escalation.
• To enable simultaneous assignment of safe dose combinations based on accrued data.

Main Methods:

• TALE utilizes prespecified parameters to define dose adjustment rules (escalation, de-escalation, reassessment).
• The design controls dose exploration and limits the occurrence of toxicities.
• It allows for the concurrent enrollment of patients into multiple dose-combination arms deemed safe.

Main Results:

• Numerical studies demonstrate TALE's comparable performance to existing methods (BOIN, COPULA, PINT, CRM) in identifying the MTD.
• TALE effectively reduces the risk of patient overdosing compared to alternative designs.
• The operative characteristics of TALE are robust and reliable.

Conclusions:

• The TALE design offers an improved balance between patient safety and MTD identification accuracy.
• TALE is practical for clinical implementation, supported by an R package and Shiny application.
• This approach facilitates the safe and efficient exploration of novel oncology drug combinations.