Key Takeaways:
- Evogene operates three proprietary tech engines—MicroBoost AI, ChemPass AI, and GeneRator AI—supporting product development in microbial, small molecule, and genomic-based solutions.
- The company applies AI not just as a tool but as a core innovation platform, developing its own custom algorithms in-house.
- Subsidiaries such as Lavie Bio and Casterra exemplify the practical application of Evogene’s technologies across geographies and sectors.
- Ofer Haviv, CEO of Evogene, supports a shift in public and regulatory perception toward GMOs and genome editing, viewing them as sustainable technologies.
- Future focus is on pharma, with the ChemPass engine leading Evogene’s ambition to develop its own drug pipeline by 2030.
Company Structure Built Around AI Computational Biology Platforms
Since its inception in 2002, Evogene has been guided by a belief that computational technologies, combined with biological insight, can radically transform the development of life science-based products. From microbial solutions to genetically modified seeds and pharmaceuticals, the Israel-based firm has adopted a dual-path structure: core technological engines developed at Evogene, and subsidiaries that deploy these tools in sector-specific product development.
“Our belief is that life science products need to evolve through the integration of computational tools and specialized datasets,” said Ofer Haviv, President & CEO of Evogene. “This allows us to predict and design solutions rather than depend on trial-and-error high-throughput screening.”
The Structure: Engines and Subsidiaries
Evogene’s work is anchored around three proprietary platforms:
- MicroBoost AI: Focuses on microbial solutions such as biostimulants and biopesticides.
- ChemPass AI: Targets small molecule discovery for applications including pharmaceuticals.
- GeneRator AI: Supports genomic modification and seed development.
These platforms power subsidiaries like Lavie Bio, which has commercialized biostimulants such as Yalos for crops like wheat, soy, and oats. Lavie Bio also partners with multinationals including Corteva, Bayer, and ICL. Another example is Casterra, which uses the GeneRator engine to accelerate castor bean breeding—used in biofuels and biopolymers—with active operations in Kenya and Brazil.
From Public Perception to Policy
Reflecting on Evogene’s earlier focus on genetically modified organisms (GMOs), Haviv acknowledged the challenges posed by public perception and regulatory hurdles, particularly in Europe.
“To me, GMO is a green technology. It reduces fertilizer and pesticide use, and can significantly improve yields,” said Haviv. “But the market’s early reaction—especially in Europe—was shaped by limited education around the science.”
While newer techniques such as genome editing have gained traction, Haviv remains cautious. “Genome editing is promising, but I’m concerned it’s still being conflated with GMO in the public eye. That could restrict investment and innovation.”
He emphasized what he sees as inconsistencies in the regulatory framework, citing the widespread import of GMO soy and corn into Europe for animal feed, even as cultivation of GMO crops remains banned. “If the grain used for feed is GMO anyway, what exactly are we trying to avoid?”
The Role of AI—and Possibly Quantum Computing
Evogene defines itself as “AI-first.” Its computational group doesn’t merely implement third-party models but builds AI engines tailored for life sciences applications. “We’re not just users—we’re builders,” Haviv noted. “We develop engines from scratch with world-class experts, even working with teams from Google Cloud.”
The convergence of AI, big data, and domain expertise in biology and chemistry allows the company to identify candidate products more effectively. The future, Haviv said, may also involve quantum computing—but he remains cautious. “Quantum computing has potential, but for now, it’s still a few years away from real-life utility.”
Outlook to 2030: Pharmaceutical Development Using AI Computational Biology Platforms
Looking ahead, Evogene plans to increase its focus on the pharmaceutical sector using its ChemPass engine. Haviv envisions a dual model of engagement with the pharma industry: collaborative partnerships with large firms, and an independent pipeline of in-house drug candidates.
“My dream is to see Evogene become a global leader in small molecule discovery. I want us to develop our own drugs using our technological edge,” said Haviv.
Final Thoughts: Building a Language of Innovation
Haviv attributes part of Evogene’s success to fostering internal communication between disciplines. “You can’t expect a computer scientist to design a biology tool without understanding the scientific needs. Biologists work in probabilities; coders work in absolutes. Putting them in the same room from day one is crucial,” he explained.
For Evogene, bridging disciplines—and perhaps public perspectives—continues to be at the heart of its strategy. From building AI in-house to deploying solutions globally, the company remains focused on transforming life sciences through precision and collaboration.
