An interview with a study author on implementing artificial intelligence into rheumatic care.
As interleukin receptor (IL) inhibitors, the monoclonal antibody drug class has come to revolutionize fields of inflammatory disease care, though the utility and resourcing of such promising agents is yet to be fully refined.
Namely, clinicians can stand to benefit from more biomarkers, more indications by which monoclonal antibodies are most impactful. New data shows a streamlined strategy for one such agent in rheumatoid arthritis, through artificial intelligence (AI).
A new study presented at the American College of Rheumatology (ACR) Convergence 2020 showed that rule-positive patients with rheumatoid arthritis identified through machine learning benefitted more greatly from IL-6 receptor inhibitor sarilumab than they did TNF inhibitor adalimumab.
Investigators, led by Dr. Ernest Choy, of Cardiff University in Wales, now believe prospective studies could verify this machine learning rule to help better treat patients with rheumatoid arthritis with the agent—which has been shown in phase 3 trials to better outcomes versus placebo and adalimumab, despite limited understanding of its characteristics.
In an interview with HCPLive® during ACR 2020, Choy discussed his team’s findings, the current understanding of salirumab in treating rheumatic disease, and what role AI has played—and can continue to play in this era of advancing drugs and telemedicine dependency due to the coronavirus 2019 (COVID-19) pandemic.
Listen to the full interview with Choy above.
The study, “Identification of a Rule to Predict Response to Sarilumab in Patients with Rheumatoid Arthritis Using Machine Learning and Clinical Trial Data,” was presented at ACR 2020.
Credit: Google News