Offers on-demand, highly scalable data processing resources
Improves querying volume from millions to 40 billion molecules
Accelerates time-to-market cycle for life science products by 2x
With Google Cloud, Evogene accelerates the discovery and development process for life science products by 50%.
The life sciences industry faces mounting pressure to deliver innovative solutions across diverse sectors, from human health and agriculture to materials science and environmental sustainability. These efforts require the discovery and development of novel compounds, encompassing a wide range of modalities including small molecules as well as microbial and genetic elements. However, traditional R&D processes struggle with the vast and complex data space, lengthy timelines, high costs, increasing complexity and low success rates in reaching the product commercialization stage. These challenges underscore the urgent need for innovative approaches that can accelerate the discovery and development of novel compounds across all modalities and sectors while improving efficiency, safety and sustainability. By overcoming these hurdles, the AI based approaches can potentially unlock their full potential to deliver transformative solutions for a healthier and a more sustainable future.
To develop breakthrough life science products and capitalize on our scientific expertise, we required robust tools to store, manage, and analyze our ever-expanding data sets. Google Cloud provides advanced analysis capabilities, enabling dramatic acceleration of development timelines and facilitating previously unattainable innovation.
Ofer Haviv
CEO and President, Evogene
Evogene’s unique computational platform, developed over 20 years, performs deep analysis of vast databases of small molecules, microbes, and genetic elements, providing critical data-based insights that guide their collaborations with partners in the development of life science products.
Because Evogene’s objectives require data analysis on a massive scale, the company was in search of a solution that could support the handling of billions of potential data points — along with the in-house models and training sets built by Evogene’s data scientists and engineers.
"Our goal is to develop breakthrough life science products, elevating worldwide health. To do that, we needed to capitalize on our biological, chemical and agronomy expertise by introducing robust tools to store, manage, and analyze our ever-expanding data sets. Google Cloud provided the technical foundation and solutions that we needed to perform advanced analysis, enabling us to dramatically accelerate development timelines and facilitate previously unattainable breakthroughs for our partners," says Ofer Haviv, CEO and President of Evogene.
"Google Cloud offers the best environment for our developers to craft our in-house training and modeling systems, giving us the solid logistical support we need to leverage billions of data points and perform queries that can transform world health."
The computational power provided by Google Cloud empowers us to create training sets of models in weeks, instead of months. This would have been impossible in an on-premises setting. We can now take on triple the number of data projects we were previously handling.
Ilia Zhidkov
VP of Computational Technologies, Evogene
Traditionally, companies test for molecular compatibility using a method dubbed "spray and pray." Millions of molecules are essentially launched at a target, while researchers hope to be able to note which molecules appear to be effective.
But this trial-and-error strategy is both incredibly costly and time-consuming, involving thousands of hours of lab time, workforce, and potential waste of resources — all ultimately leading to a low chance of success.
Evogene’s platform revolutionizes molecular development by tapping into billions of data points to efficiently identify the most promising candidates for a specific life science product. The inherent challenge, however, was having sufficient computing power to process nearly unlimited data points. On-premise capacity proved limited, and Evogene required rapid processing of vast datasets to make complex molecular simulations and ultimately accelerate life science research.
Turning to Google Cloud, Evogene’s new nearly-unlimited infrastructure now facilitates Evogene's large-scale data processing, enabling their teams to engage in deep analysis and molecular screening, positioning their partners to slash their development times by half.
"With our growing data demands, we needed a flexible infrastructure solution that could grow alongside us," says Ilia Zhidkov, VP of Computational Technologies at Evogene.
"The computational power provided by Google Cloud empowers us to create training sets of models in weeks, instead of months. This would have been impossible in an on-premises setting," continues Ilia. "We can now take on triple the number of data projects we were previously handling. Because we can learn much faster about specific molecules, we can now give our partners the insights they need in weeks, rather than months."
As a data-driven scientific company, Evogene continuously expands both the volume and diversity of its leveraged data, steadily enhancing the Computational Predictive Biology and Chemistry platform’s capabilities through new and expanded data points and machine learning modeling.
An infrastructure solution offering scalability and agility in a fast-evolving, fluid environment was essential to support Evogene's dynamic needs.
"We moved to Google Cloud seeking a true ally — someone who would collaborate with us, not just provide cloud services," says Zhidkov.
"Flexibility was a major factor in why we chose Google Cloud. They met our tight timelines and adapted on short notice. Google’s agility and commitment to match our innovative pace felt like working with a start-up, but with the experience of a corporate giant. With Google Cloud, we are able to optimize our innovative discovery process," Zhidkov says.
Zhidkov emphasized that Google Cloud provided not only the logistical support Evogene needed for in-depth data analysis and its daily operations, but also delivered stellar guidance and advice that went beyond the industry standard, contributing significantly to Evogne’s ability to increase the probability of success.
We're seeing tremendous progress in our ongoing collaboration with Google Cloud to develop our cutting-edge small-molecule foundation model. The power of Google Cloud's infrastructure, coupled with Evogene's deep knowledge of biological systems and AI-driven algorithm development, continues to be instrumental in this successful endeavor.
Ilia Zhidkov
VP of Computational Technologies, Evogene
Recommendations for additional solutions and help with strategic decisions around cloud infrastructure were all part of the package, he says, positioning Evogene to fulfill its mission of accelerating breakthrough life science product development.
Evogene's development of a foundation model for small molecule drug discovery is another ongoing collaborative effort with the Google Cloud team. This ambitious project, aimed at revolutionizing drug discovery by generating novel small molecules, is currently in progress. A key component of its development plan involves leveraging Vertex AI to train the model on an expanding dataset, starting with millions, then billions, and ultimately reaching a training set of approximately 40 billion small molecules.
"By optimizing gen-AI de-novo design across numerous complex criteria, our foundation model is poised to significantly accelerate the development of breakthrough therapeutics," says Dr. Ruth Gross, VP of Business Development.
The platform seamlessly integrates advanced AI, specifically machine learning, with a profound understanding of the science required to tackle challenging design of small molecules with high precision and efficacy. Its unique ability to optimize for multiple constraints and uncover unique ligands highlights Evogene's leadership in AI-driven life sciences.
"We're seeing tremendous progress in our ongoing collaboration with Google Cloud to develop our cutting-edge, small-molecule foundation model. This model represents a significant leap forward in our ability to design and discover novel small molecules, dramatically accelerating the process and improving the success rate of drug discovery. The power of Google Cloud's infrastructure, coupled with Evogene's deep knowledge of biological systems and AI-driven algorithm development, continues to be instrumental in this successful endeavor," concludes Zhidkov.
Evogene is an expert-based computational life science company. Utilizing big data and AI to advance life science product development in the pharmaceutical and agriculture sectors, Evogene enhances chances of success and reduces R&D investment. Its 3 proprietary engines — ChemPass AI, MicroBoost AI, and GeneRator AI —focus on small-molecule, microbial, and genetic element innovations.
Industry: Technology
Location: Israel
Products: Google Cloud, Vertex AI