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- Agreement to screen discovery and early development compounds using artificial intelligence and computational biophysics
- Cloud-based in silico platform that screens small molecules to determine polypharmacological profiles
- Evaluation to include identification of potential mechanisms of action for investigational small molecules
Merck, a leading science and technology company, today announced that it has entered into a licensing agreement with Cyclica Inc. for the use of Ligand Express(R), a cloud-based in silico proteome screening platform. Ligand Express(R) is a structure-based and artificial intelligence (AI) augmented proteome screening platform that is being used to uncover novel targets that are modelled to interact with a small molecule. This year-long agreement will enable Merck to quickly and efficiently elucidate mechanisms of action, evaluate safety profiles and explore additional applications for a number of its investigational small molecules, including those identified in highly disease-relevant phenotypic screens.
"With scientific curiosity at the heart of everything we do, the pursuit of state-of-the-art research techniques and technologies is integral to complement our internal discovery engine," said Belen Garijo, Member of the Executive Board and CEO Healthcare, Merck. "Artificial intelligence has the power to make the previously unimaginable a reality - we are eager to harness these new possibilities to help drive the discoveries that can transform the lives of people affected by difficult-to-treat diseases."
"A key part of our R&D strategy is to progress highly promising compounds as efficiently and rapidly as possible," added Friedrich Rippmann, Director of Computational Chemistry & Biology at Merck. "Assessing new technologies is central to how we will advance our discovery programs, and artificial intelligence applications like Ligand Express(R) will provide important insights to enhance how we think about target identification to support phenotypic screening and off-target profiling in general."
"Current experimental protein screening approaches can take up to a year, making it virtually impossible to do this for multiple compounds. We see this as a specific opportunity for cloud-based and AI-augmented technologies to drive drug discovery more efficiently,"
