The global fungicide market, valued at approximately $22 billion annually, faces a critical challenge as repetitive chemical use fuels the evolution of resistant fungal pathogens. This trend threatens food security by diminishing the performance of existing commercial products. The new APP model integrates into the broader ChemPass AI for Ag™ platform, utilizing proprietary datasets to estimate the efficacy of small molecules within fungal systems during the earliest research phases.
In section Releases
AgPlenus Expands ChemPass AI Platform to Predict Antifungal Potency
AgPlenus, a subsidiary of Evogene, has launched an Antifungal Potency Predictor (APP) model designed to identify high-efficacy crop protection molecules before chemical synthesis. By forecasting biological activity directly from chemical structures, the tool aims to accelerate the discovery of fungicides capable of overcoming rising global pathogen resistance.
This predictive approach allows researchers to filter out ineffective candidates early, focusing experimental resources on molecules with a higher probability of downstream success. According to CEO Dan J. Gelvan, the model builds on previous successes in identifying novel proteins to combat diseases like Septoria Wheat Blotch. Beyond its immediate utility, the company intends to use the APP framework as a foundation for developing further predictive models that target additional biological attributes throughout the discovery process, including upcoming work on Botrytis and Fusarium strains.
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