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Tumor-Specific Success Probabilities and Factors Associated With Phase III Trials in Oncology Drug Development
Keiko Yamamoto1,2, Aya Iwase1, Hideki Maeda1
1Regulatory Science, Graduate School of Pharmaceutical Sciences, Meiji Pharmaceutical University, Tokyo, Japan.
Clinical and Translational Science
|June 8, 2026
Summary
Phase III oncology trial success is low but influenced by factors like biomarker selection and trial design. Understanding these elements can improve drug development success rates.
Area of Science:
- Oncology
- Clinical Trials
- Drug Development
Background:
- Phase III oncology trials have a low success rate despite advances in targeted therapies and immunotherapies.
- Quantitative characterization of success probabilities and associated factors in oncology drug development is needed.
Purpose of the Study:
- To quantitatively assess Phase III oncology trial success probabilities.
- To identify factors associated with trial success in oncology drug development.
Main Methods:
- Analysis of 824 Phase III interventional oncology trials registered on ClinicalTrials.gov (2007-2023) with available primary endpoint results.
- Definition of trial success as achieving at least one primary endpoint.
- Multivariable logistic regression to identify associations between trial success and characteristics like patient selection, trial initiation date, therapy type, and endpoints.
Main Results:
- Overall success probabilities were similar for solid tumors and hematologic malignancies, but varied significantly by specific solid tumor types (e.g., low for CNS and pancreatic cancers).
- Biomarker-based patient selection, recent trial initiation, specific lines of therapy, and fewer primary endpoints were linked to higher success.
- Molecularly targeted therapies and short-term endpoints showed higher success rates, while chemotherapy and overall/event-free survival endpoints had lower success rates.
Conclusions:
- Phase III oncology trial success is influenced by tumor-specific characteristics and development factors.
- Biomarker-based patient selection and optimized trial design are crucial for improving oncology drug development success.
- Quantitative insights can inform decision-making and enhance future trial designs in oncology.
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