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alt="" title="Open Access"> </span> AI In Drug Discovery and Development </h3> <div class="d-flex justify-content-between flex-wrap flex-md-nowrap"> <div class="mb-4 mb-md-0"> <p class="font-weight-bold"> PUBLISHED October 01, 2024 (DOI: <a href="https://doi.org/10.54985/peeref.2410p4589655" target="_blank">https://doi.org/10.54985/peeref.2410p4589655</a>) </p> <div class="bg-info text-white px-3 d-inline-block"> <small>NOT PEER REVIEWED</small> </div> </div> </div> <hr> <dl> <dt> <h4>Authors</h4> </dt> <dd> <div class="mb-3"> Hemant Vishwakarma<sup>1</sup> </div> <div class="mb-3"> <ol class="pl-4"> <li>University of Delhi</li> </ol> </div> </dd> </dl> <dl> <dt> <h4>Conference / event</h4> </dt> <dd> AI in biological Science, February 2024 (ARSD College (DU), India) </dd> </dl> <dl> <dt> <h4>Poster summary</h4> </dt> <dd>Artificial Intelligence (AI) has revolutionized the drug discovery process by providing insights into biological targets, such as receptors, enzymes, proteins, and genes, which are involved in disease processes in patients. AI can help in target identification, verification, lead identification, and lead effectiveness. The biopharmaceutical industry is increasingly using AI to improve drug discovery, reduce research and development costs, and predict potential risks in late trials. Unlike traditional drug development, which typically takes five years, AI drugs can be developed in just 12 months. The rapid growth in life sciences and machine learning algorithms has led to a significant increase in AI-based startups focused on drug innovation. This has the potential to significantly improve the efficiency and success of drug discovery in the medical care industry.</dd> </dl> <dl> <dt> <h4>Keywords</h4> </dt> <dd>AI, Drug Discovery, Drug development</dd> </dl> <dl> <dt> <h4>Research areas</h4> </dt> <dd>Biological Sciences, Molecular and Cellular Biosciences</dd> </dl> <dl> <dt> <h4>References</h4> </dt> <dd> <ol class="pl-4"> <li>https://www.sciencedirect.com/journal/drug-discovery-today-technologies</li> <li>Anil K. Philip, Aliasgar Shahiwala, Md. Faiyazuddin - A Handbook of Artificial Intelligence in Drug Delivery-Academic Press_Elsevier (2023)</li> <li>McCarthy J, Hayes PJ. Some Philosophical Problems from the Standpoint of Artificial Intelligence. Readings in Artificial Intelligence. 1981:431-50.</li> </ol> </dd> </dl> <dl> <dt> <h4>Funding</h4> </dt> <dd> <span class="text-muted">No data provided</span> </dd> </dl> <dl> <dt> <h4>Supplemental files</h4> </dt> <dd> <span class="text-muted">No data provided</span> </dd> </dl> <dl> <dt data-toggle="collapse" data-target="#collapseAdditional" style="cursor: pointer;"> <h4> Additional information <i class="ivu-icon ivu-icon-md-arrow-dropdown"></i> </h4> </dt> <dd class="collapse" id="collapseAdditional"> <dl> <dt>Competing interests</dt> <dd class="text-secondary"> No competing interests were disclosed. </dd> </dl> <dl> <dt>Data availability statement</dt> <dd class="text-secondary"> The datasets generated during and / or analyzed during the current study are available from the corresponding author on reasonable request. </dd> </dl> <dl> <dt>Creative Commons license</dt> <dd class="text-secondary"> Copyright © 2024 Vishwakarma. 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