Researchers at Dana-Farber Cancer Institute published encouraging data on a computer platform, dubbed MatchMiner, that helps clinicians and clinical researchers identify and match patients to appropriate targeted therapy clinical trials based on the genetic alterations of patients’ tumors. Tools such as these will become more valuable in the future as more and more patients have their tumors genomically profiled.
According to the new study, published Wednesday in npj Precision Oncology, the Dana-Farber researchers were able to bring about roughly one in every five consents to join a precision medicine trial of patients with genomic data in MatchMiner. The team also said it cuts the time it takes for patient enrollment 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,” said 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 was developed to draw upon the extensive genomic data and analysis at Dana-Farber, with more than 40,000 cancer patients having had their tumors tumros and tissues analyzed over the past ten years for genomic alterations in more than 400 genes implicated in cancer. The platform was developed in the Institute’s Knowledge Systems by Ethan Cerami, PhD, and Michael Hassett, MD. Launched in 2016, MatchMiner links these genomic data with its in-house clinical trial data, which has included more than 450 targeted therapies to help match patients with the right clinical trial.
MatchMiner is not being used as a proprietary tool by Dana-Farber, rather it is open-source and is available for use at other caner centers. Currently, the platform includes information from more than 350 precision medicine trials and as new trials come on line they are reviewed by a curator to determine whether they should be added to the existing set.
“MatchMiner can be used by an oncologist or other clinician to look up trial options for an individual patient,” Klein noted. “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.”
For the new research to determine the effect of MatchMiner, the 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 said.
