Motivations, challenges and recommendations for using machine learning in drug discovery and development

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dc.contributor.authorADIL PERVAIZ
dc.date.accessioned2025-12-05T16:47:46Z
dc.date.available2025-12-05T16:47:46Z
dc.date.issued2020
dc.description.abstractEmergence of computational methods and technologies has produced a society that is fed by the data. There are tremendous amounts of data which should be sorted and characterized in order to avail the useful information. With the advancement in computational technologies especially the Machine Learning, new doors to data manipulation have been opened. Beside other domains, this has led to the change in traditional drug development process. Traditionally, drug development was target driven, whereas modern drug development process is data driven. At present, almost all the pharmaceutical companies are using Machine Learning techniques to develop new and novel drugs. Our work focuses on the review of Machine Learning techniques used in drug discovery and development and illustrates how they have changed the face of drug discovery in the last decade. The study is done by choosing more than 100 articles that meet our selection criteria, from six famous databases: Springer, IEEE, Elsevier, ChemInformatics, BMC and ACS. The information gained from these chosen articles is sorted under various headings and the main findings are presented pictorially. Since a long time, analysts have been following the pattern of Machine Learning (ML) and other computational technologies in drug disclosure in different ways, yet leaving territories or a corner for further consideration. We can conclude that a strong collaborative relationship between computer and biological scientists could boost the process of discovery and development of novel and improved drugs to cure various diseases.
dc.identifier.urihttps://escholar.umt.edu.pk/handle/123456789/15256
dc.language.isoen
dc.publisherUMT Lahore
dc.titleMotivations, challenges and recommendations for using machine learning in drug discovery and development
dc.typeThesis
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