New AI tool predicts whether aggressive small cell lung cancer will respond to treatment

Results of a new study conclude that a pathology tool powered by artificial intelligence can predict whether a patient with extensive-stage small cell lung cancer will respond to platinum-based chemotherapy—before treatment has begun, and without additional biopsies. That means patients can avoid treatments that are unlikely to help them, have a chance to enroll earlier in clinical trials of newer drugs, and may get a clearer picture of their prognosis.

The accuracy of the tool, called PhenopyCell, has been verified by the three institutions that collaborated on the study published in the journal npj Precision Oncology. PhenopyCell was developed by a research team co-led by thoracic oncologist Prantesh Jain, MD, FACP, of Roswell Park Comprehensive Center, and Anant Madabhushi, Ph.D., of Winship Cancer Institute of Emory University in Atlanta.

The team’s findings offer a ray of hope for the 70% of patients with small cell lung cancer (SCLC) who have extensive-stage disease when they are first diagnosed. At that point, the disease has spread to other parts of the body and is rapidly progressing, with most patients surviving only 12 to 13 months, so it’s critically important to quickly identify the best potential treatment.

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