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Refinement of Operating Characteristics for Model-Based TGI Metrics Decision Support to Ungate a Pivotal Trial in
Mathilde Marchand1, Kenta Yoshida2, Antonio Gonçalves1
1Certara Integrated Drug Development, Paris, France.
Abstract:
The oncology market is evolving, with an increasing number of therapeutic options making the inference of treatment benefit from early development critical. The "Go" versus "No Go" decisions from such trials usually rely on probabilities of achieving meaningful improvements (effect sizes) in endpoints like objective response rate, tailored to products' profile, supporting faster transitions to confirmatory trials. Operating characteristics are sensitive to methodological details, important for establishing an early decision framework for ungating a pivotal clinical trial.
Insights
In oncology, predicting treatment success early is crucial. This involves analyzing probabilities of meaningful improvements to guide "Go" or "No Go" decisions for pivotal trials.
Area of Science:
- Oncology
- Clinical Trial Design
- Drug Development
Background:
- The oncology market faces rapid evolution with numerous therapeutic options.
- Accurate inference of treatment benefit from early development is increasingly critical.
- Objective response rate (ORR) is a key endpoint for evaluating treatment efficacy.
Purpose of the Study:
- To highlight the importance of inferring treatment benefit in early oncology development.
- To emphasize the role of effect size probabilities in "Go"/"No Go" decisions.
- To underscore the need for an early decision framework for pivotal clinical trials.
Main Methods:
- Probabilistic analysis of achieving meaningful improvements in endpoints like ORR.
- Tailoring effect size expectations to specific product profiles.
- Evaluating the sensitivity of operating characteristics to methodological details.
Main Results:
- "Go"/"No Go" decisions are typically based on the probability of achieving desired effect sizes.
- Methodological choices significantly influence the operating characteristics of decision frameworks.
- Early decision-making frameworks require careful consideration of trial design and endpoints.
Conclusions:
- Establishing a robust early decision framework is vital for efficient drug development in oncology.
- Accurate prediction of treatment benefit accelerates the transition to confirmatory trials.
- Optimizing methodological details enhances the reliability of early-phase oncology trial decisions.
