Evogene and Professor Ehud Gazit of Tel Aviv University Announce a Collaboration to Develop New Therapeutics for Metabolic Diseases

Rhea-AI Summary

Evogene (NASDAQ: EVGN) has announced a strategic collaboration with Professor Ehud Gazit from Tel Aviv University to develop novel therapeutics for metabolic diseases. The partnership, facilitated by Ramot, combines Evogene's ChemPass AI platform with Professor Gazit's expertise in molecular self-assembly to target diseases caused by metabolite accumulation.

The collaboration aims to develop small molecules that can inhibit pathological self-assembly processes in diseases such as Tyrosinemia, Gout, and Maple Syrup Urine Disease (MSUD). The project will leverage ChemPass AI's advanced algorithms to understand therapeutic modes of action and design novel molecules for treatment.

Positive

• None.

Negative

• Early-stage research collaboration with no immediate revenue impact
• No specified timeline for drug development or commercialization
• Competitive landscape in metabolic disease therapeutics

News Market Reaction – EVGN

+3.31%

1 alert

+3.31% News Effect

+$338K Valuation Impact

$11M Market Cap

0.1x Rel. Volume

On the day this news was published, EVGN gained 3.31%, reflecting a moderate positive market reaction. This price movement added approximately $338K to the company's valuation, bringing the market cap to $11M at that time.

Data tracked by StockTitan Argus on the day of publication.

A failure in metabolite breakdown leads to their ordered self-assembly into pathological aggregates, such as in Tyrosinemia and Gout.

REHOVOT, Israel, Aug. 12, 2025 /PRNewswire/ -- Evogene Ltd. (Nasdaq, TASE: EVGN), a leading computational biology and chemistry company, today announced a scientific collaboration with the pioneering research group of Professor Ehud Gazit from Tel Aviv University, a world leader in the field of molecular self-assembly. This collaboration agreement was facilitated by Ramot, Tel Aviv University's tech transfer company. This partnership aims to accelerate the discovery and optimization of novel small molecules as potential drug candidates for a range of diseases caused by the ordered self-assembly of small metabolites.

Metabolite accumulation, often due to impaired metabolic breakdown of specific molecules, drives the ordered self-assembly process that forms detrimental aggregates, characterizing a range of common and rare diseases, including Tyrosinemia, Gout, and Maple Syrup Urine Disease (MSUD).

The goal of this collaboration is to design novel small molecules capable of effectively inhibiting pathological self-assembly processes, thereby paving the way for groundbreaking new therapeutics that could change the lives of millions of patients. 

The collaboration brings together Evogene's ChemPass AI's state-of-the-art computational capabilities for generative molecular design with Professor Gazit's world-renowned expertise in the characterization and manipulation of the self-organization of biological molecules. Professor Gazit's discovery of the ability of very short peptides, as well as metabolites, to form typical amyloidal nano-fibrils offers critical insights into disease mechanisms and potential therapeutic interventions. This deep scientific understanding will be coupled with Evogene's generative AI models, purpose-built to optimize across multiple key parameters, offering a synergistic solution.

The collaboration is aimed at leveraging ChemPass AI's advanced algorithms and models to:

• Decipher desired modes of action: Gaining a profound understanding of how therapeutic agents can intervene in metabolite self-assembly.
  
  
• Drive generative molecular design with ChemPass AI: Utilizing the power of AI to create entirely novel molecules tailored to exhibit a precise combination of features necessary for therapeutic efficacy.

Professor Ehud Gazit from Tel Aviv University stated: "We are excited to join forces with Evogene in this groundbreaking endeavor. For more than a decade, our research has revealed for the first time how small metabolites can self-assemble into amyloid-like structures that contribute to the pathology of numerous rare and common diseases. By integrating our fundamental understanding of molecular self-assembly with Evogene's cutting-edge AI-driven drug design platform, we have a unique opportunity to develop novel therapeutics that specifically target these pathological processes and ultimately improve treatment for patients."

Dr. Gabi Tarcic, Evogene's VP Product, stated: "This collaboration with Professor Gazit's outstanding research group at Tel Aviv University represents a significant milestone in our commitment to leveraging cutting-edge computational chemistry and AI to address complex medical challenges. By combining Professor Gazit's deep insights into molecular self-assembly with our powerful ChemPass AI platform, we aim to accelerate the discovery of truly novel therapeutics that could profoundly impact the lives of millions suffering from metabolite aggregation diseases."

About Evogene Ltd.
Evogene Ltd. (Nasdaq: EVGN, TASE: EVGN) is a computational biology and chemistry company leveraging big data and artificial intelligence, aiming to revolutionize the development of life-science-based products by utilizing cutting-edge technologies to increase the probability of success while reducing development time and cost.
Evogene has established three unique tech-engines: MicroBoost AI, ChemPass AI, and GeneRator AI. Each tech-engine focuses on the discovery and development of products based on one of the following core components: microbes (MicroBoost AI), small molecules (ChemPass AI), and genetic elements (GeneRator AI).
Evogene uses its tech-engines to develop products through strategic partnerships and collaborations, including its subsidiaries:

• Biomica Ltd. (www.biomicamed.com) – developing and advancing novel microbiome-based therapeutics to treat human disorders, powered by MicroBoost AI;
• Lavie Bio (www.lavie-bio.com) – developing and commercially advancing microbiome-based ag-biologicals, powered by MicroBoost AI;
• AgPlenus Ltd. (www.agplenus.com) – developing next-generation ag-chemicals for effective and sustainable crop protection, powered by ChemPass AI; and
• Casterra Ag (www.casterra.co) – developing and marketing superior castor seed varieties that produce high yield and high-grade oil content on an industrial scale for the biofuel and other industries, powered by GeneRator AI.

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," "hopes," "intends," "anticipates," "plans," "believes," "scheduled," "estimates," "demonstrates" or words of similar meaning. For example, Evogene and its subsidiaries are using forward-looking statements in this press release when it discusses the success of the collaboration to design novel small molecules capable of effectively inhibiting pathological self-assembly processes, and groundbreaking new therapeutics and to create entirely novel molecules tailored to exhibit a precise combination of features necessary for therapeutic efficacy and the success of the collaboration with accelerating the discovery of truly novel therapeutics.  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 current war between Israel and Hamas and any worsening of the situation in Israel such as further mobilizations or escalation in the northern border of Israel 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 field-trials 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.

Contact:
ir@evogene.com
Tel: +972-8-9311901

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SOURCE Evogene Ltd

FAQ

What is the purpose of Evogene's collaboration with Tel Aviv University?

The collaboration aims to develop novel small molecule therapeutics for metabolic diseases by combining Evogene's ChemPass AI platform with Professor Gazit's expertise in molecular self-assembly.

Which diseases will Evogene (EVGN) target through this collaboration?

The collaboration will target diseases caused by metabolite accumulation, including Tyrosinemia, Gout, and Maple Syrup Urine Disease (MSUD).

How will Evogene's ChemPass AI platform be used in this collaboration?

ChemPass AI will be used to decipher therapeutic modes of action and drive generative molecular design to create novel molecules for treating metabolic diseases.

Who is Professor Ehud Gazit and what is his role in the Evogene collaboration?

Professor Gazit is a world leader in molecular self-assembly from Tel Aviv University who discovered how short peptides and metabolites form amyloidal nano-fibrils. He will provide expertise in biological molecule self-organization.

What is the potential market impact of Evogene's metabolic disease therapeutics?

The therapeutics could potentially help millions of patients suffering from metabolite aggregation diseases, though the timeline for development and commercialization is not specified.