AI solutions for scientists in the pharmaceutical industry to design, make, and test new drugs
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AI solutions for scientists in the pharmaceutical industry to design, make, and test new drugs
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Prior to founding Pending AI, Mark was a Professor of Physics at Shanghai University. He was a post-doc at a Max-Planck-Institute in Mülheim an der Ruhr and obtained his PhD from the University of Sydney.
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Significant time is spend during drug discovery on designing and making thousands of molecules to find an active lead. There needs to be a faster and cheaper way to develop drugs.
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Pending AI has developed complementary AI-driven solutions to optimise drug discovery and development pipelines, namely with regards to de novo drug design, structure based drug design, high throughput chemistry and synthesis planning. These AI-based solutions are employed to augment the cognitive abilities of individual scientists and teams to enable them to make more informed decisions in drug design.
Significant time is spend during drug discovery on designing and making thousands of molecules to find an active lead. There needs to be a faster and cheaper way to develop drugs.
Pending AI has developed complementary AI-driven solutions to optimise drug discovery and development pipelines, namely with regards to de novo drug design, structure based drug design, high throughput chemistry and synthesis planning. These AI-based solutions are employed to augment the cognitive abilities of individual scientists and teams to enable them to make more informed decisions in drug design.
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Pending AI’s models are trained across massive federated datasets that contain millions of data points across many disciplines including 138 million compounds, 21 million reactions and 146 thousand proteins. This expansive data has enabled them to develop a generative drug designer and retrosynthesis engine that extensively accelerates the drug discovery process.
Pending AI’s models are trained across massive federated datasets that contain millions of data points across many disciplines including 138 million compounds, 21 million reactions and 146 thousand proteins. This expansive data has enabled them to develop a generative drug designer and retrosynthesis engine that extensively accelerates the drug discovery process.
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