Connecting patients to trials for which they are eligible can be particularly difficult as more cancer patients have their malignancies genomically assessed and as additional medicines targeting genomic abnormalities enter clinical trials. According to a recent study, the makers of a computer platform created at the Dana-Farber Cancer Institute claim that it speeds up and simplifies the matching process.
The platform, called MatchMiner, aids medical professionals and clinical researchers in matching patients with targeted therapy trials based on genetic changes found in patients’ tumors.
It assisted in getting nearly one in every five patients at Dana-Farber who had genomic data in MatchMiner to consent to participate in precision medicine trials. The authors of the study, which was published in npj Precision Oncology, discovered that it also speed up the process of enrolling patients in such trials by more than 20%.
“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,” says Tali Mazor, PhD, the co-lead author of the paper with Dana-Farber colleague Harry Klein, PhD.
“The combination of this growing body of genomic data and 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.”
MatchMiner can be used by an oncologist or other clinician to look up trial options for an individual patient. 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.
Harry Klein
The platform, developed by the Knowledge Systems Group at Dana-Farber led by Ethan Cerami, PhD, and Michael Hassett, MD, MPH, draws on Dana-Farber’s extensive programs in genomic analysis and clinical research. Over the past ten years, the Institute has examined the tumor tissue of over 40,000 patients for changes in over 400 cancer-related genes.
The Institute and its partners lead or participate in thousands of clinical trials, including about 450 involving targeted therapies since 2017. MatchMiner, which was launched in 2016, links these systems to help match patients to appropriate trials.
“MatchMiner can be used by an oncologist or other clinician to look up trial options for an individual patient,” Klein remarks. “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 open-source and can be adapted by other institutions. As new trials open at Dana-Farber, 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 are integrated into MatchMiner. In the new paper, investigators analyzed enrollment data for precision medicine trials at Dana-Farber 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, and the trial team or the patient’s oncologist viewed the match, leading to the patient’s consent 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%,” Klein says.
MatchMiner links patients to trials not only by the molecular features of the patient’s tumor but also by patient 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 say.
“MatchMiner provides a starting point for finding appropriate trials for patients whose tumors have defined genetic alterations,” Mazor says. The platform’s designers will be working to expand its capabilities to make a more comprehensive match, she adds.
Through a collaboration with Kenneth Kehl, MD, MPH, MatchMiner is testing AI-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.
