Kyorin partners with Elix to boost drug discovery with AI platform

Kyorin Pharmaceutical has selected Elix Discovery, an AI-powered drug discovery platform developed by Elix, to support its research and development activities.

Drug development historically involves identifying potent compounds from large chemical libraries, a process that often extends R&D timelines, increases costs, and has a low success rate. Increasingly, pharmaceutical firms are turning to artificial intelligence to address these challenges, utilising technologies that can accelerate compound selection, synthesis, and evaluation, as well as improve the probability of successful outcomes.

Elix is a Tokyo-based company focused on AI-driven solutions in drug discovery. The Elix Discovery platform, first launched in 2022, is designed to be accessible to medicinal chemists and is used by a number of companies in the pharmaceutical sector. The platform features a graphical user interface intended to simplify the creation of predictive models for compound profiling. Using proprietary structure generation models, it can suggest chemical structures that may not have been previously considered by researchers.

The platform allows users to optimise models and parameters within the interface, supporting both ligand-based drug design and structure-based drug design. Tools such as docking simulations are incorporated to allow for a more comprehensive drug discovery workflow. Elix Discovery also includes options for using AI models trained on data from 16 pharmaceutical companies.

Elix offices collaborate on research projects by combining AI technology with domain knowledge in drug discovery. Through these partnerships, the company aims to encourage the development of new drug candidates.

Expectations from Kyorin

"We are dedicated to creating highly valuable new drugs that address unmet medical needs. We actively collaborate with external institutions and utilize innovative external technologies, taking on the challenge of 'drug discovery innovation' through these research activities. We expect that the implementation of Elix Discovery will accelerate our research and enhance its quality by integrating our drug discovery capabilities with AI-driven drug discovery, ultimately enabling us to create highly valuable new drugs."

This statement was given by Junichi Ishiyama, Corporate Officer CSO, Senior Director of Discovery Research HQs at Kyorin.

Comments from Elix

"We are deeply honored that KYORIN has chosen to adopt our AI drug discovery platform, Elix Discovery. Developed under the concept of 'medicinal chemists can truly use it,' the platform is designed to maximize researchers' capabilities. By combining KYORIN's long-standing expertise in drug discovery with our cutting-edge AI technology, we are confident this collaboration will accelerate drug discovery research. We look forward to shaping the future of the field together."

Shinya Yuki, Chief Executive Officer of Elix, commented on the collaboration with Kyorin.

AI in drug discovery

The adoption of AI-based tools such as Elix Discovery is part of a wider shift in the pharmaceutical industry towards data-driven drug development. These platforms offer potential benefits in modelling compounds, predicting outcomes, and reducing the time and cost associated with traditional R&D methods.

Kyorin operates according to a corporate philosophy centred on contributing to better health by creating new drugs that address medical needs. The selection of an AI-powered platform is consistent with efforts to meet these company aims.

Elix continues to work with pharmaceutical companies, universities, and biotech firms in using AI to support drug discovery projects. The company has previously announced collaborations with other organisations to develop AI-based approaches targeting specific challenges in drug discovery, including protein interactions and federated learning across multiple datasets.

The partnership between Kyorin and Elix will apply AI methodologies to Kyorin's ongoing research portfolio, with the aim of streamlining compound design and improving overall R&D efficiency.