Evogene Announces Major Milestone in Its Collaboration with Google Cloud, Advancing ChemPass AI™ Toward Autonomous Small Molecule Discovery and Optimization
Integration of agentic computational systems enables the early-stage definition of key clinical and biological success criteria, accelerating discovery timelines, improving scalability, and increasing the likelihood of success
REHOVOT, Israel – June 24, 2026 – Evogene Ltd. (NASDAQ & TASE: EVGN), a computational biology and chemistry company leveraging artificial intelligence (AI) to discover and develop innovative small-molecule products for the pharmaceutical and agricultural industries, today announced the successful completion of a significant milestone in its second collaboration with Google Cloud.
This milestone marks the integration of agentic computational systems within Evogene’s ChemPass AI™ platform, designed to rapidly and efficiently identify key success requirements at the earliest stages of small-molecule development. These new capabilities are expected to enable the selection of molecules that meet product definition requirements at the early stages of the discovery phase, with the goal of accelerating discovery timelines, improving scalability and most importantly, significantly enhancing the overall probability of success.
Successful small-molecule development requires identifying candidates that satisfy a broad and complex set of biological, chemical, clinical and commercial requirements. These requirements are defined by the Target Product Profile (TPP) and are critical to the eventual success of any development program. Because many of these requirements are traditionally evaluated only in the later stages of development, and since researchers often fail to anticipate these downstream challenges during early candidate selection, discovery programs often face costly delays, inefficient allocation of R&D resources, high attrition rates, and increased development risk.
To address these challenges, the enhanced ChemPass AI™ engine, enabled by Google’s Gemini models and Gemini Enterprise Agent Platform, is designed to enable earlier and deeper biological TPP profiling, with the goal of identifying the critical criteria a molecule must satisfy to progress successfully. This capability is driven by a workflow of autonomous AI agents that integrate structural, biological, chemical and clinical data to independently profile these targets. ChemPass AI™ is designed to address a broad number of requirements simultaneously throughout the molecule design and generation process. The integration of these new and existing capabilities is intended to allow research teams to anticipate downstream requirements and prioritize compounds with the highest development and commercial potential from the outset of the discovery phase, before significant resources are committed.
The milestone was achieved through the ongoing collaboration between Evogene and Google Cloud. Google Cloud’s enterprise-grade AI infrastructure and platforms provide the foundation for building scalable, next-generation autonomous discovery capabilities. The integration demonstrates how advanced cloud-based AI technologies may accelerate innovation across the life sciences sector.
This achievement represents an important step in Evogene’s vision to advance molecular discovery and optimization through artificial intelligence. The Company is advancing toward increasingly autonomous computational systems designed to predict key success requirements at the earliest stages of development.
Boaz Maoz, Managing Director, Google Cloud Israel, commented: “We are excited to see how Evogene is leveraging Google Cloud’s full AI stack to redefine the life sciences sector. By using our Gemini models and embarking on agentic AI, Evogene is positioned to innovate and significantly accelerate the discovery of new molecules, demonstrating the transformative power of AI in streamlining complex biological and chemical research.”
Ofer Haviv, President and CEO of Evogene, stated: “This milestone advances our vision to redefine molecular discovery and optimization through AI. Google Cloud’s technology provides a robust foundation for scaling these capabilities across our pipeline and future collaborations. By integrating advanced AI agents into ChemPass AI™, we believe we can generate richer target profiles earlier in discovery. This is intended to allow us to anticipate downstream requirements and prioritize high-potential candidates before committing significant resources, with the goal of moving us closer to autonomous computational systems that predict key success requirements at the earliest stages. As we enter this next phase, we believe these new capabilities may position us to address complex proteins that currently represent a challenge in the development of new therapies.”
About Evogene Ltd.:
Evogene Ltd. (Nasdaq/TASE: EVGN) is a pioneering company in computational, 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.
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 uses forward-looking statements in this press release when it discusses: the collaboration’s potential to enable the selection of molecules that meet product definition requirements at early stages of the discovery phase; the Company’s goal of accelerating discovery timelines and improving scalability; Evogene’s advancement toward increasingly autonomous computational systems designed to predict key success requirements at the earliest stages of development; and the Company’s efforts to address complex proteins that represent a challenge in the development of new therapies. 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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