New Perspectives on Machine Learning in Drug Discovery

Title:New Perspectives on Machine Learning in Drug Discovery

Volume: 28 Issue: 32

Author(s): Simona Musella, Giulio Verna, Alessio Fasano and Simone Di Micco*

Affiliation:

• European Biomedical Research Institute of Salerno (EBRIS), Salerno,Italy

Keywords: Machine learning, artificial intelligence, drug repurposing, virtual screening, ADMET, synthesis planning, personalized medicine, drug design.

Abstract: Artificial intelligence methods, in particular, machine learning, has been playing a pivotal role in drug development, from structural design to the clinical trial. This approach is harnessing the impact of computer-aided drug discovery due 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.

Cite this article as:

Musella Simona , Verna Giulio , Fasano Alessio and Di Micco Simone *, New Perspectives on Machine Learning in Drug Discovery, Current Medicinal Chemistry 2021; 28 (32) . https://dx.doi.org/10.2174/0929867327666201111144048