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      DrugRepoChatter: a drug repurposing expert chatbot curated by the REPO4EU consortium

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            Abstract

            The amount of scientific literature available is overwhelming, especially in fast-evolving fields like drug repurposing. Researchers face a significant challenge: staying up-to-date is nearly impossible due to the sheer volume of publications, databases, and tools available. This situation creates an urgent need for more efficient ways to access and integrate information from these articles.

            To tackle this problem, we developed "DrugRepoChatter", a tool designed to help researchers navigate the flood of recent literature on data sources, methods, and tools relevant for mechanism-based drug repurposing. DrugRepoChatter uses a vector database containing 285 open-access articles carefully selected by experts from the REPO4EU project to cover the latest developments in drug repurposing. The chatbot works by finding semantic similarities between a user’s question and the information stored in the database, effectively answering questions by drawing directly from the content of these articles. DrugRepoChatter is available as a web tool at https://apps.cosy.bio/drugrepochatter/

            This tool makes the review process much more efficient and ensures researchers can quickly find relevant information. By facilitating faster access to scientific literature and enabling researchers to easily find the tools and information they need, DrugRepoChatter accelerates knowledge discovery. This tool not only streamlines the process of reviewing literature but also helps integrate scattered information into a cohesive, accessible format.

            Author and article information

            Journal
            DrugRxiv
            REPO4EU
            10 July 2024
            Affiliations
            [1 ] Institute for Computational Systems Biology, University of Hamburg, Albert-Einstein-Ring 8-10, 22761 Hamburg, Germany ( https://ror.org/00g30e956)
            [2 ] Data Science in Systems Biology, TUM School of Life Sciences, Technical University of Munich, 85354 Freising, Germany ( https://ror.org/02kkvpp62)
            [3 ] Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA ( https://ror.org/04b6nzv94)
            [4 ] Ludwig Boltzmann Institute for Network Medicine at the University of Vienna, Augasse 2-6, A-1090 Vienna, Austria ( https://ror.org/03prydq77)
            [5 ] Max Perutz Labs, Vienna Biocenter Campus (VBC), Dr.-Bohr-Gasse 9, 1030, Vienna, Austria ( https://ror.org/04khwmr87)
            [6 ] University of Vienna, Center for Molecular Biology, Department of Structural and Computational Biology, Dr.-Bohr-Gasse 9, 1030, Vienna, Austria ( https://ror.org/03prydq77)
            [7 ] Faculty of Mathematics, University of Vienna, Oskar-Morgenstern-Platz 1, A-1090 Vienna, Austria ( https://ror.org/03prydq77)
            [8 ] CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Lazarettgasse 14, AKH BT 25.3, A-1090 Vienna, Austria ( https://ror.org/02z2dfb58)
            [9 ] GeneSurge GmbH, Ottostr. 3, 80333 Munich, Germany ;
            [10 ] Discovery and Data Science (DDS) Unit, STALICLA SL, Moll de Barcelona, s/n, Edif Este, 08039 Barcelona, Spain;
            [11 ] Department of Pharmacology and Personalised Medicine, FHML, MeHNS, Maastricht University, The Netherlands ( https://ror.org/02jz4aj89)
            Author notes
            Author information
            https://orcid.org/0000-0002-6171-1215
            Article
            10.58647/DRUGARXIV000018
            10.58647/DRUGARXIV.PR000014.v1
            a09010b2-67a6-4c0a-8037-7a4d6d3a5eb9

            This work has been published open access under Creative Commons Attribution License CC BY 4.0 , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com .

            History
            Funding
            Funded by: funder-id http://dx.doi.org/10.13039/100018693, HORIZON EUROPE Framework Programme;
            Award ID: 101057619
            Funded by: funder-id , Swiss State Secretariat for Education, Research and Innovation (SERI);
            Award ID: 22.00115
            Categories

            The datasets generated during and/or analysed during the current study are available in the repository: https://github.com/fmdelgado/drugrepochatter
            Computer science,Molecular medicine,Bioinformatics & Computational biology,Artificial intelligence
            Drug repurposing,literature review,retrieval augmented generation (RAG),chatbot,semantic similarity, large language models

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