MELLODDY Consortium Employs Federated Learning and Blockchain to Enhance AI Drug Discovery

A new consortium of pharmaceutical, technology and academic partners is hoping to improve collaboration and competitive data sharing among pharmaceutical companies in ways that would address IP concerns. Utilizing blockchain and federated learning technologies, the MELLODDY (Machine Learning Ledger Orchestration for Drug Discovery) Consortium aims to use deep learning methods on the chemical libraries of 10 pharma companies to create a modeling platform that can more quickly and accurately predict promising compounds for development, all without sacrificing the data privacy of the participating companies.

Over the last few years, pharma and biotech companies have been adopting artificial intelligence (AI) and big data approaches, particularly machine learning and deep learning, in hopes that these technologies will change the way the industry discovers, develops, and manufactures medicines. Advances in computational power have opened up the possibility of creating digital models utilizing machine learning that can dramatically accelerate innovation and yield inexpensive predictions from expensive data.

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