AgPlenus Ltd., a subsidiary of Evogene Ltd. (NASDAQ: EVGN), announced the launch of its Antifungal Potency Predictor (APP), a machine learning model designed to forecast the antifungal potency of small molecules based on their chemical structures, before chemical synthesis or biological testing takes place.

The model has been integrated into Evogene's ChemPass AI for Ag™ platform and was trained on AgPlenus' proprietary datasets. According to the company, the APP is intended to reduce the number of molecules requiring experimental evaluation by identifying candidates with higher probabilities of success at early discovery stages.

AgPlenus said the model is expected to support its internal fungicide pipeline, which includes a target known as APTF-1, aimed at diseases such as Septoria Wheat Blotch. The company also said the model is expected to contribute to pipeline expansions targeting pathogens including Botrytis and Fusarium.

The global fungicide market is estimated at approximately $22 billion annually, based on the company's own calculations. Fungal diseases cause crop losses resulting in tens of billions of dollars in economic damage each year, according to external sources cited in the press release.

AgPlenus and Evogene said they plan to co-develop additional predictive AI models intended to forecast other biological attributes in the crop protection discovery process.

Dan J. Gelvan, CEO of AgPlenus, said: "By enabling us to forecast antifungal potency directly from molecular structure, prior to chemical synthesis, the APP model allows us to identify and prioritize high-quality candidates at the earliest stages of discovery."

AgPlenus is based in Rehovot, Israel.