| Literature DB >> 33176630 |
Simona Musella1, Giulio Verna1, Alessio Fasano1, Simone Di Micco1.
Abstract
Artificial intelligence methods, in particular, machine learning, has been playing a pivotal role in drug development, from structural design to clinical trial. This approach is harnessing the impact of computer-aided drug discovery thanks to large available data sets for drug candidates and its new and complex manner of information interpretation to identify patterns for the study scope. In the present review, recent applications related to drug discovery and therapies are assessed, and limitations and future perspectives are analyzed. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.Keywords: ADMET; Machine learning; artificial intelligence; drug design.; drug repurposing; personalized medicine; synthesis planning; virtual screening
Year: 2020 PMID: 33176630 DOI: 10.2174/0929867327666201111144048
Source DB: PubMed Journal: Curr Med Chem ISSN: 0929-8673 Impact factor: 4.530