Earlier this month at HIMSS 2018, Mayo Clinic reported that IBM’s Watson system has driven an 80% increase in enrollment in clinical trials for breast cancer. The artificial intelligence (AI) platform has also significantly reduced the time to screen an individual patient for clinical trial matches, said Dr. Kyu Rhee, chief health officer of Watson Health, a business unit of IBM.
“Watson for Clinical Trial Matching understands key patient attributes and how to identify them in a variety of formats, including clinical notes, pathology reports, labs, and other key components of the medical records to effectively evaluate a patient against the inclusion or exclusion criteria for a trial,” he told us.
Mayo implemented the system in July 2016, at which time it was trained on breast cancer, but it has since evolved with the addition of new cancer types, Rhee explained. Today, the system is trained to support clinical trial matching for breast, lung, colorectal, and gastrointestinal cancers, and additional training is underway, he said.
“As part of the expanded relationship, Mayo Clinic and IBM Watson Health will continue developing Watson for Clinical Trial Matching so it can include trials for other types of cancer and aspects of cancer care beyond chemotherapy therapies, such as surgery, radiation and supportive care,” Rhee added.
Moving forward, Mayo Clinic will continue to serve as IBM's training partner for the offering and will also expand its use of the system in their oncology practice.
Reaching patients sooner
IBM is working with a number of health facilities, including the contract research organization (CRO) Icon Clinical research.
Recently, Highlands Oncology Group and Novartis successfully demonstrated the ability to expedite patient screening for clinical trial eligibility, reducing processing time from 1 hour and 50 minutes to 24 minutes using Watson for Clinical Trial Matching, Rhee said. “It also omitted 94% of non-matching patients automatically – reducing screening workload dramatically,” he added.
Researchers are also using Watson for Drug Discovery to “more quickly and accurately uncover essential patterns and connections across multiple, diverse knowledge databases to accelerate new findings, which may lead to effective pharmaceuticals going to market and reaching patients sooner,” said Rhee.
Notably, Barrow Neurological Institute recently reported success applying Watson to its ALS or Lou Gehrig's disease research. The research was published in the journal Acta Neuropathologica.
“At the time of this study, there were only 11 known RNA-binding proteins (RBPs) exhibiting alterations associated with ALS. IBM Watson for Drug Discovery was applied and it generated a list of new potential ALS-linked RBP targets,” he explained. “Following multiple validation methods, IBM Watson identified 5 never-before linked proteins associated with significant alterations in ALS.”