AgPlenus Launches Novel AI Model for Predicting Antifungal Potency, Expanding ChemPass AI for Ag™ Capabilities
New AI model enables ChemPass AI for Ag™ to identify and prioritize antifungal molecules with a higher probability of biological success at early discovery stages
REHOVOT, Israel – July 15, 2026 – AgPlenus Ltd., a company developing novel, sustainable crop protection products and a subsidiary of Evogene Ltd. (Nasdaq, TASE: EVGN), today announced the launch of its Antifungal Potency Predictor (APP). This new machine learning model predicts the antifungal potency of small molecules directly from their chemical structures, expanding the capabilities of Evogene’s ChemPass AI for Ag™ platform by forecasting biological efficacy prior to chemical synthesis and fungal assay validation.
The global fungicide market is estimated at approximately $22[1] billion annually. Fungal diseases cause significant crop loss worldwide, resulting in tens of billions of dollars in economic damage each year and posing a growing threat to global food security[2]. Concurrently, the widespread and repetitive use of existing fungicides has accelerated the emergence of resistant fungal pathogens, diminishing the long-term efficacy of many commercial products. As resistance continues to spread, the agriculture industry faces an urgent need for novel fungicides with innovative modes of action (MoAs) and distinct chemical structures.
The APP model, developed using advanced machine learning algorithms trained on AgPlenus’ proprietary curated datasets, represents a significant milestone in the company’s AI-driven fungicide discovery capabilities. Building upon the proven success of the ChemPass AI for Ag™ platform in identifying novel crop protection targets and generating molecules with high target-protein affinity, the new model further extends these capabilities to predict the small molecule activity within the fungus itself.
By forecasting antifungal potency during the earliest discovery phases, the model enables highly informed decision-making prior to chemical synthesis and biological testing. This approach significantly reduces the number of molecules requiring experimental evaluation, focusing resources on candidates with the highest probability of downstream development success and accelerating the discovery of next-generation fungicides.
The launch of the APP model is expected to support and advance AgPlenus’ internal fungicide pipeline, which includes promising targets such as APTF-1. This target is designed to combat devastating global crop diseases, including Septoria Wheat Blotch. Additionally, the model is expected to contribute to planned pipeline expansions targeting other critical pathogens, such as Botrytis and Fusarium.
Beyond its immediate application in accelerating current and future product development, the APP model lays the groundwork for additional predictive AI models that AgPlenus and Evogene plan to co-develop, aiming to forecast other critical biological attributes throughout the crop protection discovery process.
Dr. Dan J. Gelvan, CEO of AgPlenus, commented: “In 2025, we demonstrated the power of the ChemPass AI for Ag™ platform to identify novel target proteins capable of overcoming resistance, as well as novel active small molecules combating devastating crop diseases like Septoria Wheat Blotch. Today, we are taking another major step forward with the launch of our Antifungal Potency Predictor. 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. I am excited to see this breakthrough model integrated into ChemPass AI for Ag™, further strengthening our ability to advance current and future product development programs.”
About Evogene Ltd.
Evogene Ltd. (Nasdaq/TASE: EVGN) is a pioneering company in computational chemistry specializing in the generative design of small molecules for drug development and ag-chemical products. At the core of its technology is ChemPass AI™ a proprietary generative AI designed to explore vast chemical space and generate novel, highly potent small molecules optimized across multiple critical parameters. Built on this powerful technological foundation, and through strategic partnerships alongside internal product development, Evogene is focused on products for the pharmaceutical and agricultural industries, driven by the integration of scientific innovation with real-world industry needs.
For more information, please visit www.evogene.com.
About AgPlenus Ltd.
AgPlenus, a subsidiary of Evogene, is a platform company designing effective and sustainable crop protection products. At AgPlenus, we are solving pesticide resistance by infusing the discovery process with predictive biology and artificial intelligence. AgPlenus leverages the ChemPass AI™ tech-engine, licensed by Evogene, to discover and bring to market effective and sustainable crop protection products. Our target-based approach allows us to reduce risk and increase efficiency, so that we can deliver on our promise to defeat global pesticide resistance.
For more information, please visit www.agplenus.com
Forward-Looking Statements
This press release contains “forward-looking statements” within the meaning of the Private Securities Litigation Reform Act of 1995 relating to future events. These statements may be identified by words such as “may,” “could,” “expects,” “hopes,” “intends,” “anticipates,” “plans,” “believes,” “scheduled,” “estimates,” “demonstrates”, “designed to,” “intended to,” “with the goal of,” or words of similar meaning. For example, Evogene and its subsidiaries use forward-looking statements in this press release when it discusses: the Antifungal Potency Predictor’s ability to forecast biological efficacy prior to chemical synthesis and fungal assay validation and to predict the small molecule activity within the fungus itself, the ability to reduce the number of molecules requiring experimental evaluation, focusing resources on candidates with the highest probability of downstream development success and accelerating the discovery of next-generation fungicides, the new model’s contribution to planned pipeline expansions and APP model ability to lay the groundwork for additional predictive AI models. Such statements are based on current expectations, estimates, projections and assumptions, describe opinions about future events, involve certain risks and uncertainties which are difficult to predict and are not guarantees of future performance. Therefore, actual future results, performance or achievements of Evogene and its subsidiaries may differ materially from what is expressed or implied by such forward-looking statements due to a variety of factors, many of which are beyond the control of Evogene and its subsidiaries, including, without limitation, the aftermath of the recent war between Israel and each of (i) the terrorist groups, Hamas and Hezbollah, (ii) Iran, and (iii) other regional terrorist groups supported by Iran, and any potential destabilizations in Israel, neighboring territories or the Middle East region, and those risk factors contained in Evogene’s reports filed with the applicable securities authority. In addition, Evogene and its subsidiaries rely, and expect to continue to rely, on third parties to conduct certain activities, such as their and pre-clinical studies, and if these third parties do not successfully carry out their contractual duties, comply with regulatory requirements or meet expected deadlines, Evogene and its subsidiaries may experience significant delays in the conduct of their activities. Evogene and its subsidiaries disclaim any obligation or commitment to update these forward-looking statements to reflect future events or developments or changes in expectations, estimates, projections and assumptions.
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[1] Based on Company’s calculations.
[2] https://www.mpg.de/23545750/plants-fungal-diseases