Artificial Intelligence for Computer-Aided Drug Discovery
Drug Res (Stuttg) DOI: 10.1055/a-2076-3359The continuous implementation of Artificial Intelligence (AI) in multiple
scientific domains and the rapid advancement in computer software and hardware,
along with other parameters, have rapidly fuelled this development. The
technology can contribute effectively in solving many challenges and constraints
in the traditional development of the drug. Traditionally, large-scale chemical
libraries are screened to find one promising medicine. In recent years, more
reasonable structure-based drug design approaches have avoided the first
screening phases while still requiring chemists to design, synthesize, and test
a wide range of compounds to produce possible novel medications. The process of
turning a promising chemical into a medicinal candidate can be expensive and
time-consuming. Additionally, a new medication candidate may still fail in
clinical trials even after demonstrating promise in laboratory research. In
fact, less than 10% of medication candidates that undergo Phase I trials
really reach the market. As a consequence, the unmatched data processing power
of AI systems may expedite and enhance the drug development process in four
different ways: by opening up links to novel biological systems, superior or
distinctive chemistry, greater success rates, and faster and less ex...
Source: Drug Research - Category: Drugs & Pharmacology Authors: Kate, Aditya Seth, Ekkita Singh, Ananya Chakole, Chandrashekhar Mahadeo Chauhan, Meenakshi Kanwar Singh, Ravi Kant Maddalwar, Shrirang Mishra, Mohit Tags: Review Source Type: research
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