A team including physician researchers, software developers and more came up with the software concept at the MIT Hacking Medicine Grand Hack 2017. From left to right: Jason Cardinal, MD; Daniel Kezerashvili; John Silberholz, PhD; Eddy Chen, MD; Anisa Mohammed, MBA; Ned Ohringer; Rosanna Zhang; and Sean Kearin, MD.
What if you held a clinical trial and nobody came?
While plenty of patients are eager to participate, researchers often have difficulty reaching their target enrollments for clinical trials, the goal of which is to determine the safety and efficacy of new drugs or therapies before they are brought to market. This can lead to delays and to ballooning costs for the therapies’ sponsors.
Now, though, there’s help. Last month the MGH Martinos Center’s Ned Ohringer and colleagues introduced a software concept that matches patients with clinical trials they are actually likely to join, thus providing a way to overcome shortfalls in recruitment.
Here’s how it works. Typically, doctors seek to enroll patients in the trials based on specific inclusion and exclusion criteria: stage of the disease, treatment history, etc. But their efforts fail to take into account the patients’ own criteria in deciding whether to participate: for example, how far would they have to travel, does the study involve oral or intravenous medication, and what are the expected side effects? The proposed software would help to address this oversight by targeting what the developers call “patient values.” Patients could choose and rank their preferences with respect to these criteria. The software would then find the trials that best match their priorities, improving the odds they will decide to enroll.
“We’ve been surprised to see that other groups or platforms involved with clinical trial recruitment do not mention or emphasize patient values as a means of matching patients to trials,” said Ohringer, a clinical research coordinator in the Center and one of the members of the team assembled to develop the software concept. At the hackathon, he was primarily responsible for reviewing the literature for current statistics and applying his knowledge of clinical research to the conceptual framework. “We think that we can enhance the number of patients enrolling in clinical trials. Similarly, we think that if patients are able to select these trials based on their ranked preferences, the likelihood of the trial enrolling enough appropriate patients will increase.”
The software concept emerged from a heady 48 hours at the MIT Hacking Medicine “Grand Hack 2017,” an annual event where people from throughout the medical and other communities gather to brainstorm and develop innovative solutions for a host of issues in healthcare. Ohringer’s team at the hackathon—which also comprised oncologists, business professionals, clinical trial researchers, and computer scientists—identified and tackled the problem of low recruitment in clinical trials, earning them a $1000 Koch Institute Best Cancer Hack prize. They are now moving forward with development of the software.