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Farcast publishes new data on predictive power of its precision cancer therapeutics platform

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Mohit, CEO Farcast Biosciences

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TruTumor Biosignatures published in Nature Communications demonstrate accurate responder and resistor patient cohorts for the popular immunotherapy nivolumab.

While FDMA 2.0 paves the way for effective predictive models, a lot more can be done in disrupting the high rates of development failures and treatment failure in oncology”

— Mohit Malhotra

PENSACOLA, FL, UNITED STATES, March 26, 2024 /EINPresswire.com/ — Farcast has published data in Nature Communications in February 2024 that demonstrates accurate pre-detection of responder and resistor patient cohorts for the popular immunotherapy nivolumab. Farcast’s technology creates biosignatures from multi-modal data extracted from live human tumors using proprietary methods and Artificial Intelligence (AI) models. The biosignatures aim to predict clinical response to existing or novel therapeutics more accurately than traditional translational oncology approaches.

Additional data will also be presented at the annual American Association for Cancer Research (AACR) Annual Meeting in San Diego in April 2024. The study examines role of CD4/CD8 double positive T cells in modulating response to anti-PD-1 treatment in renal cell carcinoma.

“Our recent data shows that the predictive power of biosignatures should be used during translation from pre-clinical to clinical development and from clinical development to real world clinical applications. It would save therapeutics developers and patients from a lot of wastage” said Mohit Malhotra, CEO and cofounder of Farcast.

“While FDMA 2.0 paves the way for effective predictive models, a lot more can be done in disrupting the high rates of development failures and treatment failure in oncology” added Mohit.

Farcast is the only platform in the world that has the experience of more than 24,000 tumors. The technology combines the orthogonal data extracted from live human tumors is combined with AI and deep learning to model the response profiles of novel therapies, identify combination strategies, and create the basis of personalized medicine.

Sanjay Virmani
Farcast Biosciences
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