Machine Learning: Approaches and Applications...

Machine Learning: Approaches and Applications in Drug Discovery

Author Name : Pratiksha S. Gangurde, Dr. S. R. Tambe, Dr. T.N. Lokhande, Dr. R. S. Bhambar

ABSTRACT

Drug discovery is the process through which potential new medicines are identified. It involves a wide range of scientific disciplines, including biology, chemistry and pharmacology. A variety of approaches is employed to identify chemical compounds that may be developed and marketed. The continuos advancements in computational techniques introduce development in drug design. Due to the tremendous amount of data available now a days with well-established machine learning techniques the designing of automated drug can be imagined. Machine learning has presented a great opportunity to the researchers. It offers efficient access and understanding of vast amounts of chemical data, potentially improving process and outcomes. Machine learning techniques are applicable in drug design stages like target validation, dentification, estimation of binding affinity and interactions. ML approaches can be used in virtual screening of drugs. Machine learning has gained rapid development in recent years and it is need in current situation to improve drug discovery process.

Keywords: Artificial intelligence, Chemoinformatics, Drug Discovery, Machine learning, Virtual screening,