Realizing the promise of precision oncology with an open-source tool
Key Takeaways
The development of precision medicine (PM) has been hindered by the low patient participation rate in PM trials caused by the difficulty in matching patient genomic data to trial eligibility criteria.
PM has made great strides in treating cancer by targeting specific genetic mutations. However, the key is not just finding the right treatment for the right patients, but also finding the right patients for the right trial.
MatchMiner, an open-source trial matching platform, assists physicians in finding the most suitable PM clinical trials for their cancer patients.
We are getting closer to living in a world where cancer therapies are no longer one-size-fits-all, where patients do not have to endure treatments with little hope of good outcomes.
Precision medicine (PM) is the future of healthcare, involving therapies tailored to the distinct genetic makeup of an individual's disease. However, there are still obstacles to clear before PM becomes the norm.
Off to a slow start
In 2022, the FDA approved 21 precision anti-cancer treatments, including 6 therapies targeting CAR T-cells, and 15 drugs for a biomarker-defined population.[]
PM has made great strides in treating cancer by targeting specific genetic mutations. The promise of PM is similar to creating a key that unlocks the door to a personalized healthcare experience.
However, PM adoption has been hindered by the low patient participation rate in genotype-driven trials, which is estimated to be as low as 10% to 15%.[] The low enrollment rate in PM trials is partly due to the difficulty in aligning patients’ genomic data with the eligibility criteria for these trials. But it's not just about finding the right treatment for the right patient—it's also about finding the right patients for the right trials.
That's where MatchMiner comes in—a novel trial matching platform by the Knowledge Systems Group at Dana-Farber Cancer Institute (DFCI).[]
What is MatchMiner?
MatchMiner is an open-source trial matching platform that helps physicians find the best PM clinical trials for their cancer patients. At the same time, it also helps trial investigators find the most suitable patients for their trials. It does so by matching the genetic and clinical information of patients with the inclusion and exclusion criteria of the trials.
MatchMiner utilizes the Clinical Trial Markup Language (CTML) to encode PM trial eligibility criteria.[]
How is MatchMiner used?
The platform has three modes of usage—patient-centric, trial-centric, and trial search—that allow trial investigators, patients, and oncologists to use the same platform.
The patient-centric mode—which is updated daily—displays a list of all potential PM trials that may be a good fit for a patient based on their genetic information from next-generation sequencing (NGS) panels.
In the trial-centric mode, clinical trial teams can identify patients for their PM trials of interest.
In the trial search mode, clinicians can manually input search criteria to identify available trials based on external genomic reports.
The software can adapt to a wide range of users while still maintaining compliance with HIPAA regulations when installed within any institutional firewall.[]
Integration with clinical workflows
The platform has been integrated into various clinical workflows at DFCI—including the Center for Cancer Therapeutic Innovation (CCTI) and the Gastrointestinal Cancer Center (GCC). To date, MatchMiner has curated 354 trials from DFCI.[]
Several other institutions also utilize the software—including the Memorial Sloan Kettering Cancer Center and the Princess Margaret Cancer Centre of the University Health Network.
Assessing the clinical utility of MatchMiner
Dr. Harry Klein and his colleagues recently published a study that delved into the intricate details of MatchMiner and its usage—including an examination of its clinical efficacy in terms of the swiftness of patient consent to participate in PM trials.[]
The results indicate that MatchMiner has significantly increased the number of PM trial consents, with data from DFCI showing a 22% acceleration in the consent rate. The platform has reduced the time it takes for patients to consent to trials by achieving consent 55 days earlier than would have been possible without it.
There are other similar academic cancer center solutions and commercial solutions from companies like Foundation Medicine, IBM Watson, Syapse, and molecular tumor boards. But unlike other systems that rely on clinicaltrials.gov for trial matching—which may not continually have updated trial statuses—MatchMiner is updated daily.[]
However, there are still several other reasons for low participation in precision medicine trials, including low clinical awareness and a patient’s physical condition, financial constraints, and/or unwillingness to become a trial subject. MatchMiner is only addressing one of these obstacles.[]
What this means for you
The implementation of MatchMiner in oncology care means that healthcare workers will have a more efficient and effective tool to identify relevant PM trials for their patients. This will not only improve the chances of successful treatment but also increase patient participation in PM trials. This will ultimately lead to better patient outcomes and the advancement of precision medicine.