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 Faculty Publications Conference Paper Faculty Publications- Conference Papers 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/. Creator An entity primarily responsible for making the resource Shrikumar, M.; Kurien, Georgy P.; Saha, Saibal Kumar; Sharma, Kapila Title A name given to the resource Development of an AI Based Framework for Reverse Supply Chain of Pharmaceutical Products Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2026 Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems;Volume;1761 LNNS;pp.145-155 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-3-032-13555-1_13" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-032-13555-1_13</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105035601411?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105035601411?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Shrikumar M., Christ University, Bangalore, India; Kurien G.P., Christ University, Bangalore, India; Saha S.K., St. Xaviers University Kolkata, New Town Action Area 3, West Bengal, Kolkata, 700160, India; Sharma K., Sikkim Manipal Institute of Technology, Majitar, India Description An account of the resource The pharmaceutical reverse supply chain is an integral part of pharmaceutical industry. Due to the complex nature of the process and strict government regulations, it is important to use different AI technologies to increase the efficiency of the reverse supply chain. This research aims to design an AI driven framework for reverse supply chain of pharmaceutical products which would increase efficiency, speed, automate processes and enhance trust among the stakeholders. The framework consists of five modules namely Collection and Sorting Centre, Return Management, Real-time Inventory Management, Disposal Centre, and Data Analytics. In each module different AI technologies have been embedded to increase the efficiency of the system. The proposed framework offers a holistic approach that not only aligns with stringent pharmaceutical standards but also contributes to a more robust, transparent, and environmentally sustainable reverse supply chain. The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. Subject The topic of the resource Artificial Intelligence; Demand Forecasting; Inventory; Pharmaceutical Products; Reverse Supply Chain Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Relation A related resource ISSN: 23673370; ISBN: 978-303213554-4; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online