Evogene appoints UCSF and Bar‑Ilan professors to strengthen ChemPass AI molecule design

Evogene taps UCSF and Bar‑Ilan scientists to strengthen AI-driven molecule design

SAB additions aim to accelerate ChemPass AI for drug and ag‑chemical discovery

Evogene appoints Prof. John J. Irwin of the University of California, San Francisco, and Prof. Dan T. Major of Bar‑Ilan University to its Scientific Advisory Board, moves the company says strengthen scientific leadership and accelerate its ChemPass AI™ generative engine. The appointments position Evogene to refine a platform purpose‑built to generate novel, highly potent small‑molecule candidates optimized simultaneously across potency, selectivity, ADMET and synthetic feasibility, supporting faster discovery cycles across pharmaceutical and agricultural programs.

The company frames the hires as a deliberate step to ensure ChemPass AI’s accuracy, robustness and scalability in real‑world discovery settings, consistent with its Real‑World Innovation approach that integrates deep scientific understanding with practical R&D requirements. Evogene expects the professors to provide strategic guidance on algorithmic development, validation frameworks and applicability to live discovery programs, helping to reduce later‑stage attrition by improving candidate quality from the outset.

Evogene also signals that the SAB additions will help expand validated libraries and strengthen collaborative research with academic and industry partners worldwide. By embedding external expertise into platform development, the company aims to accelerate timelines for hit identification and lead optimization in both therapeutic and ag‑chemical pipelines, while broadening the platform’s tested chemical space and real‑world applicability.

Academic data resources to feed platform refinement

Prof. Irwin brings a globally recognized record in ligand discovery and virtual screening and is the creator of widely used open‑access resources such as ZINC, DOCK, SEA and DUD‑E. His work, cited more than 35,000 times, is expected to inform Evogene’s data curation and benchmarking strategies, offering open‑science resources that can help validate and expand ChemPass AI’s training and test libraries.

Complementary computational design expertise and industry reach

Prof. Major contributes complementary strengths in molecular design and computational methods from Bar‑Ilan University, supporting algorithmic advances and practical application across both drug and ag‑chemical discovery. Evogene emphasizes that combining Irwin’s open‑science assets with Major’s methodological expertise will help refine algorithms, broaden validated chemical space and deepen collaborations that accelerate candidate progression across therapeutic and agricultural pipelines.