The Difficulty with Data: Considerations for Training Your AI/ML Algorithms for Drug Discovery
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The Difficulty with Data: Considerations for Training Your AI/ML Algorithms for Drug Discovery

Authors: Jones J
Keywords: absorption distribution metabolism and excretion (ADME), AI-Driven Drug Design, computer aided drug design (CADD), early drug discovery, in silico prediction, machine learning (ML), pharmacokinetic (PK) properties
Software: ADMET Predictor®, GastroPlus®
Division: Cheminformatics

Effective de novo drug design is a long-standing but elusive goal for computational chemistry.

Quickening the Pace of Drug Discovery with AI
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Quickening the Pace of Drug Discovery with AI

Authors: Levine D, Jamois E, Lawless M, Jones J
Keywords: admet predictor, AIDD, Artificial Intelligence-driven Drug Discovery (AIDD), gastroplus, machine learning, PBPK modeling
Software: ADMET Predictor®, GastroPlus®
Division: Cheminformatics

“The integration of our industry-leading ADMET Predictor and GastroPlus® mechanistic PBPK simulations into the initial generative chemical design process is what sets us apart from other machine learning drug design companies,” says AIDD Principal Scientist and former City of Hope Professor Jeremy Jones. “Our platform offers everything a medicinal chemist would want, at incredible speed.”