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Evogene Announces Participation in the Second Research Period of the CRISPR-IL Consortium

Israeli Innovation Authority to continue funding the on-going development of an end-to-end artificial intelligence system for genome-editing

Rehovot, Israel – November 10, 2021 – Evogene Ltd. (NASDAQ: EVGN, TASE: EVGN), a leading computational biology company targeting to revolutionize life-science product development across several market segments, announced today that it has been informed by the Israeli Innovation Authority (IIA) of the IIA’s decision to fund a second 18-month period of the CRISPR-IL consortium established last year. The consortium’s mission is to develop and validate an end-to-end artificial intelligence system – “Go-Genome” – for genome-editing in multi-species for applications in pharma, agriculture, and aquaculture.

The CRISPR-IL consortium was initially approved by the Israeli Innovation Authority for a period of 18 months with total budget of approximately ILS 40 million. This current approval, based on the achievements of the consortium to date, is for a second 18-month period and an additional budget of approximately ILS 45 million (roughly $14.4 million), partially funded by a grant from the IIA. CRISPR-IL participants include leading Israeli companies, medical institutions, and academic institutions. Dr. Eyal Emanuel, Evogene’s VP New Directions, continues to serve as Chairman of the CRISPR-IL consortium.

The first period of research was devoted to successfully developing an initial version of “Go-Genome”, an end-to-end genome editing supporting platform, encompassing diverse editing datasets aimed at improving editing efficiency. “Go-Genome” then enabled the design of thousands of gRNAs[1], performed thousands of successful editing experiments in different cells and analyzed the outcoming data. Such experiments included editing of hundreds of genetic targets across a variety of organisms in the fields of pharma (human) and agriculture (plants & animals).

During the second period of research, the consortium aims to improve “Go-Genome’s” learning models with respect to editing efficiency with a strong focus on genome-editing specificity, indicating editing exclusively on the intended target. “Go-Genome”’s computational learning models are expected to be trained[2] and validated by hundreds of genome-editing experiments, conducted by the consortium participants. These experiments aim to produce unique data from edited living cells, which is currently unavailable in such scale and diversity in the public domain.

Beyond activities within the consortium’s scope, participating companies may use “Go-Genome” for their own product development activities. In this respect, Evogene is currently conducting various proof-of-concept experiments in plant tissue examining the feasibility of increasing the production of ingredients such as natural colors and anti-aging agents for food or cosmetic purposes.

Dr. Eyal Emmanuel, Chairman of the CRISPR-IL consortium and VP New Directions of Evogene, commented, “We are delighted to be continuing our important research in one of the forefront areas of innovation – the merge of computational power and genetics. The approval of the second period of the consortium by the IIA is a vote of confidence in the Israeli research community and is a recognition of the importance of CRISPR-IL’s work. These achievements could lay the foundation for exciting new commercial directions for Evogene.”

Dr. Nir Arbel, Chief Product Officer, stated, “Through Evogene’s work in the scope of the consortium, we are broadening our artificial intelligence capabilities and extending the range of our GeneRator AI solution, for the development of genomic-based products. Evogene’s GeneRator AI solution already includes computational capabilities for identifying “where”, “which” and “how” edits should be made to achieve a specific trait, and the capabilities being developed within the framework of the consortium are anticipated to further improve and extend these capabilities.”

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About the CRISPR-IL consortium:

The CRISPR-IL consortium intends to develop an artificial intelligence-based system, “Go-Genome”, providing users improved genome-editing workflows. The system aims to provide end-to-end solutions, from user interface to an accurate measurement tool. The system is expected to include the computational design of on-target DNA modification, with minimal accidental, off-target modifications, improve modification efficiency and provide an accurate measuring tool to ensure the desired modification was made. This system is being designed to be effective in multi-species, including human, plant, and certain animal DNA applicable to market segments in pharma, agriculture and aquaculture. In addition to Evogene, key participants include BTG – Bio-technology General Israel, Colors Farm, Hazera Seeds, NRGene, Pluristem, Rahan Meristem Ltd., BetterSeeds, FreezeM; Sheba Medical Center, Schneider Children’s Medical Center; Bar-Ilan University, Ben Gurion University of the Negev, Hebrew University of Jerusalem, IDC Herzliya, Tel-Aviv University and the Weizmann Institute.

About Evogene Ltd.:

Evogene (NASDAQ: EVGN, TASE: EVGN) is a leading computational biology company focused on revolutionizing product discovery and development in multiple life-science based industries, including human health and agriculture, through the use of its broadly applicable Computational Predictive Biology (CPB) platform.  The CPB platform, incorporating a deep understanding of biology leveraged through the power of Big Data and Artificial Intelligence, has been designed to computationally discover and uniquely guide the development of life-science products based on microbes, small molecules and genetic elements.  Utilizing the CPB platform, Evogene and its subsidiaries are now advancing product pipelines for human microbiome-based therapeutics through Biomica Ltd., medical cannabis through Canonic Ltd., ag-biologicals through Lavie Bio Ltd., ag-chemicals through AgPlenus Ltd., and ag-solutions for castor oil production through Casterra Ag Ltd.  For more information, please visit: www.evogene.com.

Forward Looking Statements:

This press release contains “forward-looking statements” relating to future events. These statements may be identified by words such as “may”, “could”, “expects”, “intends”, “anticipates”, “plans”, “believes”, “scheduled”, “estimates” or words of similar meaning. For example, Evogene is using forward-looking statements in this press release when it discusses the objectives and workplans of the consortium, the benefits expected from the Go-Genome system, and the expansion of the Company’s capabilities and solutions. 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, those risk factors contained in Evogene’s reports filed with the applicable securities authorities. 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.

 

Evogene Investor Contact US Investor Relations:

 

Rivka Neufeld

Investor Relations and Public Relations Manager

E: IR@evogene.com

T: +972-8-931-1940

 

Joseph Green

Edison Group

E: jgreen@edisongroup.com

T: +1 646-653-7030

 

Laine Yonker

Edison Group

E: lyonker@edisongroup.com

T: +1 646-653-7035

 

[1] gRNA – Guide RNA is a piece of RNAs that function as guides for RNA- or DNA-targeting enzymes, which they form complexes with. Very often these enzymes will delete, insert or otherwise alter the targeted RNA or DNA.

[2] Data is gathered through experiments, then returned to “Go-Genome” to improve its learning models