As more patients with cancer have their tumors genomically profiled and more therapies targeting genomic alterations enter clinical trials, the task of connecting patients with trials for which they are eligible can be especially challenging. The novel computer platform MatchMiner, developed by the Knowledge Systems Group at Dana-Farber Cancer Institute, may make the matching process both easier and faster, its designers reported in a new study published by Klein et al in Nature Partner Journals (npj) Precision Oncology.
More About MatchMiner
MatchMiner was designed to help clinicians and clinical researchers find potential matches between patients and targeted therapy trials based on genetic alterations in patients’ tumors. During a 5-year period at Dana-Farber Cancer Institute, the platform helped facilitate roughly one in every five consents to join precision medicine trials among patients with genomic data in MatchMiner. It also sped up the process of enrolling patients in such trials by more than 20%, the study authors found.
“Profiling patient tumors for genomic alterations has become a widespread part of cancer care, especially as new drugs targeting those alterations go into clinical trials or are approved as cancer therapies,” said co-lead study author Tali Mazor, PhD, a computational biology scientist in the Knowledge Systems Group at Dana-Farber Cancer Institute. “The combination of this growing body of genomic data and [the] increasing number of precision medicine trials has created a kind of disconnect: finding the right trial for each patient can be a difficult task. MatchMiner helps bridge that gap.”
The platform’s development was led by Ethan Cerami, PhD, Director of the Knowledge Systems Group and a principal scientist in the Department of Data Science at Dana-Farber Cancer Institute, and physician Michael Hassett, MD, MPH, Associate Professor of Medicine at Harvard Medical School and the Chief Quality Officer at Dana-Farber Cancer Institute, and drew on the Institute's extensive programs in genomic analysis and clinical research. Over the past decade, more than 40,000 patients at the Institute have had their tumor tissue analyzed for alterations in over 400 cancer-related genes. The Institute and its partners have led or participated in thousands of clinical trials, including about 450 involving targeted therapies, since 2017. MatchMiner, which was launched in 2016, linked these systems to help match patients with appropriate trials.
“MatchMiner can be used by an oncologist or other clinician to look up trial options for an individual patient,” lead study author Harry Klein, PhD, a genomics scientist at Dana-Farber Cancer Institute, remarked. “Or it can be used by a trial team to identify potential trial participants by setting up a genomic filter that screens candidates for specific genomic criteria.”
Unlike most other matching platforms, which are designed for use at a single cancer center, MatchMiner is an open-source platform that can be adapted by other institutions. As new trials open at Dana-Farber Cancer Institute, a curator reviews them to see if they should be included in MatchMiner, ensuring the platform is up-to-date. As of March 2021, 354 precision medicine trials have been integrated into MatchMiner.
In the new paper, investigators analyzed enrollment data for precision medicine trials at the Institute to determine whether MatchMiner expedited the process of finding an appropriate trial for patients whose tumors had been genomically profiled. The researchers found 166 instances in which the platform identified a potential match between a patient and a trial, the trial team or the patient's oncologist viewed the match, and the patient consented to join the trial.
To further assess the impact of the platform, investigators compared the “time to consent”—the time between the genetic profiling of a tumor and the patient’s consent to participate in the trial—for the 166 consents obtained via MatchMiner and for 353 consents obtained without the platform. “We found the time to consent for the MatchMiner group was 55 days faster than for the non-MatchMiner group, an improvement of 22%,” Dr. Klein said.
MatchMiner links patients to trials not only by the molecular features of the patient’s tumor, but also by the patient’s age and tumor type. Other trial criteria, such as tumor stage, previous treatment, and patient’s overall health, are not considered for a patient–trial match. As a result, the matches proposed by MatchMiner are preliminary and need to be followed up to ensure that patients meet all the trial criteria, researchers noted.
“MatchMiner provides a starting point for finding appropriate trials for patients whose tumors have defined genetic alterations,” Dr. Mazor said, adding that the platform’s designers will be working to expand its capabilities for more comprehensive matches. Through a collaboration with physician Kenneth Kehl, MD, MPH, Assistant Professor of Medicine at Harvard Medical School, MatchMiner is testing artificial intelligence–based predictions to better identify patients who may soon need a new therapeutic option like a clinical trial.
MatchMiner is available for adoption at other institutions. More information is available at matchminer.org.
Disclosure: The research in this study was supported by Dana-Farber Cancer Institute and the Fund for Innovation in Cancer Informatics. For full disclosures of the study authors, visit nature.com.The content in this post has not been reviewed by the American Society of Clinical Oncology, Inc. (ASCO®) and does not necessarily reflect the ideas and opinions of ASCO®.