MatchMiner
Overview
MatchMiner is an open-source platform developed by the Dana-Farber Cancer Institute that leverages artificial intelligence (AI) to connect cancer patients with suitable precision oncology clinical trials. It was launched in 2016 and initially used a rules-based engine to match patients based on structured genomic biomarkers and cancer type. The platform has since evolved to incorporate AI, enabling it to analyze unstructured data from electronic health records (EHRs) to extract crucial details like prior treatments, disease stage, and comorbidities. This allows for broader trial coverage, moving beyond just genomic eligibility to include criteria based on histology, prior treatment, and performance status. MatchMiner aims to accelerate trial enrollment, maximize potential trial options for patients, and streamline the patient-trial matching process, which has traditionally been manual and time-consuming. Studies have shown that MatchMiner can decrease the time to consent for precision medicine trials by a median of 55 days, and it has facilitated hundreds of patient enrollments. The platform is designed to be integrated into clinical workflows, providing clinicians with real-time access to trial matches and patient genomic reports.
Reviewed by Pouyan Golshani, MD — Interventional Radiologist
Key Features
- AI-powered patient-trial matching
- Analysis of structured and unstructured clinical data
- Genomic trial matching
- Broad trial coverage (beyond genomics)
- Patient summaries for quick assessment
- Trial curation interface
- Oncologist dashboard
- Investigator view
- Integration with EHR and genomic sequencing projects
- Open-source platform
Use Cases
- Accelerating patient enrollment in precision oncology clinical trials
- Maximizing potential trial options for cancer patients
- Streamlining the identification of eligible patients for clinical studies
- Providing clinicians with real-time trial match information
- Supporting proactive outreach by trial investigators
- Facilitating collaboration and innovation in precision oncology research
What Physicians Need to Know
Leverage MatchMiner's patient-centric mode to quickly identify precision medicine trial options for your patients based on their genomic and clinical profiles. Utilize the AI-powered features to gain insights from unstructured EHR data, expanding the scope of potential trial matches beyond genomic criteria. For trial investigators, the trial-centric mode can efficiently identify eligible patients for your studies, accelerating recruitment. Remember that MatchMiner serves as a pre-screening tool, and further evaluation of a patient's readiness for a trial is still necessary.
MatchMiner is designed to integrate with institutional genomic and clinical data feeds, including Electronic Medical Record (EHR) systems. It is seamlessly integrated with DFCI's Profile next-generation sequencing project. The platform uses Clinical Trial Markup Language (CTML) to structure trial eligibility criteria and can be coupled with trial management systems for real-time trial status updates. Future enhancements may include support for imaging data, lab results, and integration with national trial registries.
Details
| Category | Drug Discovery & Research, Oncology AI |
| Pricing | Free |
| Deployment | On-premise (behind institutional firewall) |
| Compliance | |
| BAA Available | Unknown |
| HIPAA Compliant | Yes AI-estimated |
| FDA Status | Unknown |
| Integrations | |
| EHR | Not specified |
| Specialties | Hematology, Oncology |
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Videos
Product demos, reviews, and walkthroughs for MatchMiner.
AACR23: Harry Klein, PhD | Dana-Farber Cancer Institute
Dana-Farber Cancer Institute
