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A system and method for feedback-driven automated drug discovery that combines machine learning algorithms with automated research facilities and equipment, comprising automated research equipment configured to perform automated assays of chemical compounds; a data platform comprising drug databases and an analysis engine; a bioactivity and de novo modules operating on the data platform; and a retrosynthesis system operating on the drug discovery platform.
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Wuhan University of Science & Technology (Wuhan, China)
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A hybrid computational system of classical and quantum computing for drug discovery, which may include a computing environment, classical computing aspect, quantum computing aspect, computational workflow and machine learning operation.
HypaHub (Sunnyvale, CA, USA)
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A drug discovery method based on relationship extraction and machine learning and computer equipment, comprising the steps of performing relationship extraction by using a preset relationship extraction model to obtain a relationship type of a substance–disease entity pair; generating a quantity vector; and inputting the quantity vector into a preset drug discovery model based on a machine learning technology to obtain an output result of whether the substance can be used as a disease treatment drug or not.
Ping An Technology Co. Ltd. (Shenzhen, China)
Zhang S
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A method and a system for machine learning-based new drug candidate discovery, which includes providing a Siamese network model for scoring drug response similarity between a first and second substance by comparing an input pair to gene expression information in a database.
Korea University Research and Business Foundation (Seoul)
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Phylumtech S.A. (Sunchales, Argentina)
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