Cancer is a rampant disease that kills many every year, and to combat it, new and improved treatments are a must. Enter Massive Bio, which believes clinical trials might hold the key to those treatments. Through its platform, the company leverages various services and smart data to ensure engagement in cancer clinical trials, both from the patients and the providers. Now, with additional funding, Massive Bio can grow and expand even further. To learn more about the company and its future, check out the following article.

Results of a study evaluating the use of artificial intelligence for matching oncology patients with clinical trials showed a 58.4% increase in trial enrollment compared with traditional screening methods. The findings from this study were presented at the IASLC 2019 World Conference on Lung Cancer hosted by the International Association for the Study of Lung Cancer in Barcelona, Spain. IBM Watson Health's Clinical Trials Matching (CTM) is a system that is trained to abstract patient- and clinical trial-specific data from a variety of sources and harnesses machine learning to find clinical trials that are appropriate for a given patient. In this study, CTM was trained and used to match patients at an academic oncology outpatient clinic to 1 or more of the approximately 42 available clinical trials in lung cancer. The matches generated by CTM were subsequently validated by clinical trial coordinators, and the validated matches were provided to oncologists prior to the patients' clinic visits.

Clinical trials represent the forefront of medicine bringing new treatment options to patients and caregivers. Unfortunately, close to 90% of clinical trials fail to meet recruitment goals. This results in expensive delays that often result in early trial termination, or simply the inability to gather sufficient data to draw efficacy conclusions. These clinical trials failures slow down research, delay patient access to life-saving treatments, and contribute to rising drug costs. Enrollment Challenges · Most patients are unaware of which clinical trials are being conducted and if they qualify to participate.