Elsevier and Iktos Collaborate to Boost Drug Discovery with AI-Enhanced Chemistry Database

Elsevier, a global provider of information and analytics in science and health with 140 years of history, has entered into a strategic partnership with Iktos, a French artificial intelligence (AI) company founded in 2016 and specializing in chemical research, particularly in medicinal chemistry and new drug design.

The collaboration is a natural match since Elsevier is the creator of the world's largest chemical database, Reaxys.

Reaxys is a chemistry research and education solution providing chemical substance, properties, reaction, and medicinal chemistry information for both bench chemistry and machine learning methods used in drug discovery and chemical or pharmaceutical R&D.

Reaxys provides the most comprehensive manually extracted and curated chemistry and bioactivity database, covering over 1 billion published experimental facts, including 280 million organic, inorganic, and organometallic compounds, 74 million chemical reactions, and 46 million bioactivities from over 110 million documents, including patents and journals.

This collaboration aims to enhance Elsevier's Reaxys database by integrating Iktos’s innovative synthetic planning AI technologies. The initiative is set to provide capabilities for speeding up the identification of pre-clinical drug candidates.

The integration of Iktos's AI capabilities with Reaxys’s aims at streamlining Design-Make-Test-Analyze cycles for small molecules, ultimately reducing the time and costs associated with early-stage drug discovery.

By leveraging new predictive models, the partnership will offer advanced support for retrosynthesis, synthetic accessibility, and reaction-based analyses through a user-friendly interface and application programming interfaces (APIs).

Mirit Eldor, Managing Director at Elsevier’s Life Sciences Solutions, emphasized the goal of aiding R&D organizations by providing industry-leading predictive algorithms trained on high-quality data. 

Yann Gaston-Mathé, CEO of Iktos, highlighted the critical role of high-quality data for AI-driven innovations. The collaboration leverages Reaxys's unparalleled chemistry reaction database, enriching it with Iktos's cutting-edge retrosynthesis AI technology. There is a clear synergy. 

The new AI-driven tools, based on Iktos’s proprietary technology and trained on the Reaxys database, will introduce features such as support for stereochemistry, disconnection suggestions, intermediate inclusion or exclusion options, regioselectivity conflict avoidance, and starting material cost considerations.

Additionally, the option for customization with proprietary reactions and material libraries will be available, further enhancing research capabilities.

Reaxys customers will soon have access to these advanced predictive retrosynthesis and synthetic accessibility tools as add-on modules. 

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Building Generative AI for Drug Discovery Applications

The new collaboration reinforces Elsevier's AI-focused strategy to leverage its unique big data capabilities. 

In particular, Iktos offers a suite of tools and services, including Makya™, a generative AI-driven de novo design software for Multi-Parametric Optimization (MPO) of lead compounds. Makya™ is available as a Software-as-a-Service (SaaS) or for on-premises implementation.

Additionally, Iktos has developed Spaya™, a synthesis planning software based on the company's proprietary AI technology for retrosynthesis, and Spaya API, a high throughput synthetic accessibility scoring tool for virtual molecule libraries. These tools are designed to streamline and expedite the drug discovery process, from hit discovery to lead optimization​​​​.

In 2023, Iktos raised €15.5 million in a Series A funding round to expand its AI-based drug discovery technologies and solutions. This investment was led by a syndicate including M Ventures, Debiopharm Innovation Fund, and Omnes Capital.

For in-depth research on the advent of AI in drug discovery and development, check out our report: The State of AI in the Biopharma Industry

Topics: Biotech Companies