Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Book Chapter Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource ML in drug delivery-current scenario and future trends Description An account of the resource Machine learning (ML) has enabled transformative applications and emerged as a domain-agnostic decision-making tool as a virtue of its rapid democratization. The authors believe that a systematic assortment of important publications on this issue is indispensable in this context. In terms of data ingestion, data curation, data preprocessing, data handling, and model cross-validation, this review gathers together several studies that have demonstrated a minimum ML framework approach. In general, ML models are described as black-box models, with limited information supplied about their transparency. The authors propose techniques based on the US Food and Drug Administration (FDA)'s current good ML practice (GMLP) in order to improve the ML framework and minimize the aforementioned gap, especially for data. Considering this, the conversation around a model's logic and interpretability are additionally provided. Explicitly, the authors explore the challenges and constraints that ML execution confronts throughout the development of pharmaceuticals. In this context, a structural approach in statistics is presented to allow the scientist to assess the quality of data and incorporate important ideas and techniques that would be implemented in modern ML. The data analytics tetrahedron proposed here can be applied to data of any size. To further contextualize, selected case studies capturing good practices are highlighted to provide pharmaceutical scientists, pharmaceutical ML enthusiasts, readers, reviewers, and regulatory authorities an exposure to fundamental and cuttingedge techniques of ML and data science with respect to chemistry, manufacture, and control (CMC) of drug products. In addition, the authors believe that leveraging ML within CMC procedures can assist in improving decision-making, increasing quality, and enhancing the speed of pharmaceutical product development. IOP Publishing Ltd 2023. All rights reserved. Creator An entity primarily responsible for making the resource Muthudoss P.; Ali H.; Ramasamy G.; Allada R.; Fink E.; Kalaiselvan V.; Jayakrishnan B.; Shahane S.; Ramalingam M.; Kanakaraj L.; Kaliappan I.; Paudel A. Source A related resource from which the described resource is derived Advances in Drug Delivery Systems for Healthcare: From concept to clinic, pp. 9-. Publisher An entity responsible for making the resource available Institute of Physics Publishing Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1088/978-0-7503-5613-8ch9" target="_blank" rel="noreferrer noopener">https://doi.org/10.1088/978-0-7503-5613-8ch9</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85213166704&amp;doi=10.1088%2F978-0-7503-5613-8ch9&amp;partnerID=40&amp;md5=8045231ab65d05e1466db24bf81c5b13" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85213166704&amp;doi=10.1088%2f978-0-7503-5613-8ch9&amp;partnerID=40&amp;md5=8045231ab65d05e1466db24bf81c5b13</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-075035615-2; 978-075035611-4 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Book chapter Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Muthudoss P., A2Z4.0 Research and Analytics Private Limited, Chennai, 600062, India; Ali H., Christ University, Bangalore, 560029, India; Ramasamy G., Christ University, Bangalore, 560029, India; Allada R., Novugen Pharma (Malaysia) Sdn Bhd, Hicomglenmarie Industrial Park, 3, Jalan Jururancang U1/21, Selangor, 40150, Malaysia; Fink E., Research Center Pharmaceutical Engineering GmbH (RCPE), Inffeldgasse 13, Graz, 8010, Austria; Kalaiselvan V., Indian Pharmacopoeia, Commission, Ministry of Health and Family Welfare, Government of India, Sector 23, Rajnagar, 201002, India; Jayakrishnan B., Business School, Vellore Institute of Technology (VIT), Chennai Campus, Kekottaiyur, 600127, India; Shahane S., The Machine Learning Company, Maharashtra, India; Ramalingam M., Chettinad School of Pharmaceutical Sciences, Chettinad Academy of Research and Education, Chettinad Health City, Chennai, 603103, India; Kanakaraj L., Chettinad School of Pharmaceutical Sciences, Chettinad Academy of Research and Education, Chettinad Health City, Chennai, 603103, India; Kaliappan I., SRM College of Pharmacy, SRM Institute of Science and Technology, Kattankulathur, India; Paudel A., Graz University of Technology, Institute of Process and Particle Engineering, Inffeldgasse 13/3, Graz, 8010, Austria