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MatchMiner: an open-source platform for cancer precision medicine.
Harry Klein1, Tali Mazor2, Ethan Siegel3
1Department of Data Science, Dana-Farber Cancer Institute (DFCI), Boston, MA, USA. hrklein@ds.dfci.harvard.edu.
NPJ Precision Oncology
|October 6, 2022
Summary
MatchMiner, an open-source platform, computationally matches cancer patients to precision medicine (PM) trials. This tool accelerates trial enrollment, enabling patients to access targeted therapies faster.
Area of Science:
- Oncology
- Genomics
- Bioinformatics
Background:
- Comprehensive tumor sequencing enables precision medicine (PM) drug development.
- Matching patients to PM clinical trials is challenging due to data volume and complex criteria.
Purpose of the Study:
- To introduce MatchMiner, an open-source platform for matching patients to PM trials.
- To evaluate MatchMiner's impact on PM trial enrollment at Dana-Farber Cancer Institute.
Main Methods:
- Developed MatchMiner, an open-source computational platform.
- Curated 354 PM trials with genomic and clinical eligibility criteria (March 2016-March 2021).
- Compared time to trial consent for patients matched via MatchMiner versus those not.
Main Results:
- MatchMiner facilitated 166 trial consents for 159 patients.
- Patients matched with MatchMiner consented to trials 55 days (22%) earlier than non-matched patients.
- The platform aids clinicians in identifying trial options and trial teams in finding eligible patients.
Conclusions:
- MatchMiner effectively matches patients to precision medicine trials.
- The platform accelerates clinical trial enrollment, improving patient access to targeted therapies.
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