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- Title
Prospective evaluation and success of a machine learning hit-to-lead drug development program against phosphatidylinositol 3-kinase α.
- Authors
Kaiser, Thomas M.; Dentmon, Zackery W.; Burger, Pieter B.; Qi Shi; Snyder, James P.; Yuhong Du; Haian Fu; Liotta, Dennis C.
- Abstract
As a result of the rapidly increasing cost of drug development, efficient methods for early identification of compounds with a high probability of clinical success are needed. Herein, we describe a cheminformatics protocol which dramatically increases quality candidate identification and should reduce the attrition rate of compounds entering the clinic, increasing the cost-effectiveness of drug development. Against the oncology target phosphatidylinositol 3-kinase a, all five compounds synthesized from the protocol were found to have low nanomolar activity. We therefore propose that our protocol can be used as a tool for reducing the synthetic burden required for hit-to-lead optimization.
- Subjects
PHOSPHATIDYLINOSITOL 3-kinases; DRUG development; MACHINE learning; DRUG prices; SUCCESS
- Publication
ARKIVOC: Online Journal of Organic Chemistry, 2021, Vol 2021, p25
- ISSN
1551-7004
- Publication type
Article
- DOI
10.24820/ark.5550190.p011.304