Estimands for Early-Phase Dose Optimization Trials in Oncology.

Area of Science:

• Clinical Trials
• Pharmacology
• Biostatistics

Background:

• Traditional Phase I oncology trials focus on maximum tolerated dose.
• Novel therapies like targeted agents show fewer dose-limiting toxicities, necessitating the optimal biological dose (OBD) concept.
• The ICH E9(R1) estimand framework enhances trial clarity but lacks specific guidance for early-phase dose optimization.

Purpose of the Study:

• To discuss the application of the estimand framework in oncology dose optimization trials.
• To integrate efficacy and toxicity data using utility functions for OBD determination.
• To provide recommendations for implementing the estimand framework in early-phase oncology studies.

Main Methods:

• Utilizing utility functions to balance efficacy and toxicity for optimal dose selection.
• Incorporating pharmacokinetic, toxicity, and efficacy data in the analysis.
• Applying the estimand framework to define trial objectives and statistical analysis for dose optimization.

Main Results:

• The proposed framework enhances clarity in dose optimization trial objectives.
• It facilitates a better understanding of the drug's properties for selecting the correct dose for Phase II.
• Recommendations for handling intercurrent events and defining treatment attributes in seamless trials are provided.

Conclusions:

• The estimand framework, when applied to dose optimization, improves the definition of the optimal biological dose (OBD).
• This approach ensures alignment between trial objectives and statistical methods, crucial for novel oncology therapeutics.
• Clearer objectives and analysis strategies enable more efficient progression of promising drugs into later clinical development stages.