Company: EVGN
Filing Date: 2025-03-27
Form Type: 20-F
Source: 0001178913-25-001092
Chunk: 57

Company: Evogene Ltd.
Filing Date: 2025-03-27
Form: 20-F
Item: Item 4
Chunk 57
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 the candidates in the discovery phase, the CPB platform is also used in the development phase. In the development phase, the chosen candidates undergo various validation processes on the way to becoming a commercial product with certain desired attributes. In this process, the candidates’ ability to pass the validation criteria is improved, as required, by using our technology. Our technology is able to identify the best optimization proposal for a product candidate, improving a specific attribute of a product with minimal impairment of any of the other attributes.
 
In October 2024 we announced a collaboration with Google Cloud to pioneer a generative AI foundation model for novel small molecule design. This collaboration aims to position the ChemPass AI tech-engine, at the forefront of generating and optimizing novel small molecule structures with specific, desired properties.
 
The collaboration leverages Evogene’s expertise in computational predictive biology and chemistry alongside Google Cloud’s leadership in AI and machine learning. Building on the successful integration of ChemPass AI into Google Cloud, this collaboration is focused on expanding the value of our tech-engine by creating a new foundation model. This model will be designed to generate and optimize innovative small molecule structures with better specific, desired properties, by expanding the training set for the model from 6 million molecules to 40 billion molecules. The primary objective of this initiative is to improve and accelerate the discovery and development of new small molecules for drug development, sustainable crop protection, and other innovative applications across various life-science sectors.
 
CPB Platform
 
As described above, the mission of the CPB platform is to revolutionize the product discovery and development approach in life science industries by decoding the biological world using computational biology. This platform is the outcome of over a decade long multidisciplinary effort to integrate scientific concepts with big data and advanced computational analytics in order to develop predictions of potential product candidates that later undergo experimental validation and optimization toward commercialization. We believe that the uniqueness of our computational prediction approach stems from our ability to successfully address multiple product attributes at the beginning of the discovery process, and during the optimization phase.
 
These efforts have been enabled by two parallel revolutions taking place over the last decades: first, the data revolution – allowing the creation of enormous amounts of high-quality biological and chemical data in a cost-effective manner; and second, the computational processing revolution – allowing the analysis of data with advanced algorithms such as machine learning and other artificial intelligence methods.
 
The CPB platform represents a revolutionary approach for the design and prediction of novel products, based on four pillars: first, computationally modeling the specific biological challenges in the discovery