Researchers develop mathematical prediction model for immunotherapy success

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Researchers at the Icahn School of Medicine at Mount Sinai have developed a mathematical model capable of predicting how cancer patients will react to certain immunotherapies. Findings are explained in a study published in Nature.

Trial and error in trying to find the most effective treatment for cancer patients wastes time and resources for patients and providers. In this study, researchers explain creating a mathematical prediction model could help providers identify tumor characteristics and administer treatment best fit for each individual.

"We present an interdisciplinary approach to studying immunotherapy and immune surveillance of tumors," said Benjamin Greenbaum, PhD, the senior author with the Tisch Cancer Institute. "This approach will hopefully lead to better mechanistic predictive modeling of response and future design of therapies that further take advantage of how the immune system recognizes tumors."

Researchers used data on melanoma and lung cancer patients being treated with immune checkpoint inhibitors for the model to track characteristics of tumors and the immune system's responses to drugs. The model then is able to take into account other patients' characteristics to predict their reaction to drugs.

"This research represents a big step forward in understanding why some tumors are more aggressive than others and being able to predict rationally which neoantigens will be the most effective at stimulating an immune response," said Vinod  Balachandran, MD, with the David M. Rubenstein Center for Pancreatic Cancer Research.