The new model addresses the challenge of identifying novel small molecules that meet multiple product criteria, an essential requirement for pharma and agriculture applications
Evogene Ltd, a leading computational biology company focused on revolutionizing life-science product discovery and development, announced the completion of its generative AI foundation model, version 1.0, for small molecule design, developed in collaboration with Google Cloud. The new model expands the existing capabilities of ChemPass AI, Evogene’s tech-engine for small molecule discovery and optimization, by addressing one of the core challenges faced by both the pharmaceutical and agriculture industries: identifying novel small molecules that meet multiple complex product criteria.
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In both pharma and agriculture, successful product development depends on identifying molecules that meet complex performance criteria while also being patentable. Traditional discovery methods typically address these challenges sequentially, a process that reduces success probability. In addition, they tend to steer towards well-explored or saturated areas of chemical space. This limits the potential for innovation, making it difficult to secure robust intellectual property and achieve meaningful product differentiation.
In contrast, generative AI models support companies in their small molecule discovery process by enabling the simultaneous consideration of multiple complex product requirements, all while creating truly novel molecular structures. This approach also facilitates the development of strong, defensible IP portfolios. Evogene’s first-in-class foundation model is designed to do exactly that.
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Developed in-house by Evogene’s algorithm teams, this proprietary foundation model marks a dramatic advance over traditional generative AI. Internal computational analysis shows that it delivers approximately 90% precision in successful and precise, novel molecule designs (vs. approximately 29% in traditional GPT AI-model), ensuring that each compound simultaneously meets essential parameters. This breakthrough paves the way for creating highly potent, synthesizable, and patentable molecules across life-science products.
Built on a large dataset of approximately 38 billion molecular structures, the model was trained and deployed using Google Cloud’s advanced AI infrastructure, including high-performance GPUs and scalable storage. The result is a foundation model that not only powers Evogene’s ChemPass AI today but will also provide a scalable base for future enhancements.
Ofer Haviv, President and CEO of Evogene, stated: “Completing our foundation model is a major milestone in our offering. It unlocks new frontiers for ChemPass AI, giving us the power to generate wholly novel molecules—ones that not only perform but also create new IP space. This is key to overcoming long-standing challenges in life-science R&D: from reducing late-stage failure in pharma to developing ag-chemicals that are effective, sustainable, and proprietary.”
Boaz Maoz, Managing Director, Google Cloud Israel, commented: “We’re pleased to collaborate with Evogene’s innovation in AI-powered molecule design. Their progress with ChemPass AI highlights the strength of pairing advanced AI infrastructure with deep scientific insight. We look forward to seeing the impact of this new model in drug discovery and agriculture.”
Evogene also announces that development is already underway on version 2.0 of its generative AI foundation model, with a focus on enhanced flexibility for multi-parameter optimization. The updated version will incorporate predefined, customized parameters tailored to therapeutic contexts or specific agriculture requirements. It will enable ChemPass AI to better balance complex real-world constraints, such as efficacy, toxicity, and stability, significantly improving its ability to generate molecules optimized for clinical, commercial, and regulatory success.
Evogene welcomes continued engagement with partners across the pharmaceutical and agriculture industries interested in accessing or integrating ChemPass AI for next-generation product development.
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