Opportunities and challenges in application of artificial intelligence in pharmacology

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dc.contributor.authorKumar, Mandeep
dc.contributor.authorNguyen, T. P. Nhung
dc.contributor.authorKaur, Jasleen
dc.contributor.authorSingh, Thakur Gurjeet
dc.contributor.authorSoni, Divya
dc.contributor.authorSingh, Randhir
dc.contributor.authorKumar, Puneet
dc.date.accessioned2024-01-21T10:55:09Z
dc.date.accessioned2024-08-14T07:44:23Z
dc.date.available2024-01-21T10:55:09Z
dc.date.available2024-08-14T07:44:23Z
dc.date.issued2023-01-09T00:00:00
dc.description.abstractArtificial intelligence (AI) is a machine science that can mimic human behaviour like intelligent analysis of data. AI functions with specialized algorithms and integrates with deep and machine learning. Living in the digital world can generate a huge amount of medical data every day. Therefore, we need an automated and reliable evaluation tool that can make decisions more accurately and faster. Machine learning has the potential to learn, understand and analyse the data used in healthcare systems. In the last few years, AI is known to be employed in various fields in pharmaceutical science especially in pharmacological research. It helps in the analysis of preclinical (laboratory animals) and clinical (in human) trial data. AI also plays important role in various processes such as drug discovery/manufacturing, diagnosis of big data for disease identification, personalized treatment, clinical trial research, radiotherapy, surgical robotics, smart electronic health records, and epidemic outbreak prediction. Moreover, AI has been used in the evaluation of biomarkers and diseases. In this review, we explain various models and general processes of machine learning and their role in pharmacological science. Therefore, AI with deep learning and machine learning could be relevant in pharmacological research. � 2023, The Author(s) under exclusive licence to Maj Institute of Pharmacology Polish Academy of Sciences.en_US
dc.identifier.doi10.1007/s43440-022-00445-1
dc.identifier.issn17341140
dc.identifier.urihttp://10.2.3.109/handle/32116/4355
dc.identifier.urlhttps://link.springer.com/10.1007/s43440-022-00445-1
dc.language.isoen_USen_US
dc.publisherSpringer Science and Business Media Deutschland GmbHen_US
dc.subjectAlgorithmen_US
dc.subjectArtificial intelligenceen_US
dc.subjectBig dataen_US
dc.subjectBioinformaticsen_US
dc.subjectData miningen_US
dc.subjectMachine learningen_US
dc.titleOpportunities and challenges in application of artificial intelligence in pharmacologyen_US
dc.title.journalPharmacological Reportsen_US
dc.typeReviewen_US
dc.type.accesstypeOpen Accessen_US

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Pharmacology - Research Publications