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Exploring the Past and Current Landscape of Biomarker-Driven Clinical Trials Through Large Language Models
Margaret Guo1, Evan Passalacqua2, Erik Bao3
1Bakar Computational Health Sciences Institute, University of California-San Francisco, San Francisco, CA.
JCO Clinical Cancer Informatics
|February 3, 2026
Summary
Biomarker-driven cancer clinical trials are essential but often inaccessible due to geographic limitations. A new tool, the NCI Clinical Trials Navigator, aims to improve patient matching for these vital research studies.
Area of Science:
- Oncology
- Clinical Trials
- Genomics
- Biotechnology
Background:
- Biomarkers are crucial for cancer clinical trial eligibility and patient access.
- The National Cancer Institute Clinical Trials Reporting Program (NCI CTRP) database contains extensive trial information.
- Large language models (LLMs) offer novel applications for analyzing clinical trial data.
Purpose of the Study:
- To survey the landscape of cancer clinical trials, focusing on biomarker eligibility.
- To identify geographic disparities and common reasons for clinical trial discontinuation.
- To develop an automated tool for matching patients to biomarker-driven trials.
Main Methods:
- Extracted 20,894 trials from Cancer.gov via the NCI CTRP API.
- Quantified biomarker rates across cancer subtypes and analyzed trial site distribution.
- Identified trial failure causes and developed an LLM-based patient-to-trial matching application.
Main Results:
- 5,044 of 20,894 trials included biomarker eligibility data, often clustered around major academic centers.
- Identified 630 biomarkers across 36 cancer subtypes, with many applicable to multiple cancers.
- Trial accrual difficulties and sponsorship issues were primary reasons for discontinuation.
Conclusions:
- Geographic distribution of biomarker trials limits patient access and contributes to trial failures.
- Many individuals possess mutations making them eligible for biomarker-driven trials.
- An automated tool, NCI Clinical Trials Navigator, was developed to enhance patient-to-trial matching.
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