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Will leverage AI to discover novel small molecules for rare hereditary metabolic diseases
November 21, 2018
By: Kristin Brooks
Managing Editor, Contract Pharma
Evotec AG has entered into a research collaboration with Immuneering Corp., a data-driven drug discovery provider, to discover novel small molecules for rare hereditary metabolic diseases. Financial details were not disclosed. Evotec will leverage its induced pluripotent stem cell (iPSC) platform and drug discovery capabilities and Immuneering will apply its Artificial Intelligence drug discovery platform in an effort to accelerate ligand identification for novel targets. As part of the collaboration, Evotec will use Immuneering’s computational drug discovery platform Fluency to analyze public and proprietary data to help advance identification of novel drug candidates that can ultimately lead to new medicines for rare hereditary metabolic diseases. Dr. Cord Dohrmann, chief scientific officer of Evotec, said, “We are very excited to collaborate with Immuneering on its unique AI-driven approach to ligand identification. This is a significant opportunity to develop novel drugs targeting disorders of lysosomes that drive different clinical presentations in many rare genetic metabolic and neurodegenerative diseases with high unmet medical need. We look forward to exploring the powerful combination of these technologies and enhancing our drug discovery capabilities in our core areas of focus.” Dr. Greg Koytiger, senior vice president and head of AI for Immuneering, said, “We are thrilled to combine Evotec’s industry-leading iPSC platform with our AI platform, Fluency, to rapidly identify and functionally profile novel small molecule drugs for rare hereditary metabolic diseases. This not only accelerates the drug discovery process, but opens up new targets that are understudied or difficult to drug. Evotec’s in-depth knowledge of targets of interest and their leading iPSC platform make them an ideal partner to transform in silico hits into breakthrough therapies. We look forward to integrating best in class experimental and computational approaches to break new ground together for the benefit of these patients.”
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