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      Drug repurposing then, now, and in the future

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      REPO4EU
      RExPO23
      25-26 October 2023
      Drug repurposing, artificial intelligence, data mining, disease modules, protein structure prediction
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            Abstract

            As well as taking you on a brief journey through the history of drug repurposing - from the serendipity exploited by clever physicians and pharmacologists to the current mechanism-based and pathway-inspired strategies - this talk will discuss the future that is now taking shape: a data-driven future where medicinal chemistry and today's molecular pharmacology are only part of the foundation. The remarkable successes in drug repurposing achieved by high-throughput screening and in silico docking will continue, but will increasingly be complemented by discovery strategies such as large-scale mining of electronic health records and other unexploited repositories; target structure prediction by algorithms such as AlphaFold that allow completely unexpected ligand-protein and protein-protein interactions to be modeled; and above all new mechanistic definitions of diseases and disease modules that will take us beyond symptom-based medicine. Above all, dynamic improvements in dedicated AI systems will increasingly blur the distinction between conventional and computational drug discovery technologies. Within the next decade, human ingenuity, algorithmic power and evolving concepts of disease could synergize to create a "life science singularity" that relies at least as much on repurposed drugs as on the creation of new ones when it comes to develop new treatments.

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            Author and article information

            Conference
            REPO4EU
            14 September 2023
            Affiliations
            [1 ] H.M. Pharma Consultancy, Vienna (Austria);
            Author information
            https://orcid.org/0000-0002-1491-6250
            Article
            10.58647/REXPO.23010
            6022ef98-4bc2-4c6a-b7bc-f2481bd46845
            Authors

            Published under Creative Commons Attribution 4.0 International ( CC BY 4.0). Users are allowed to share (copy and redistribute the material in any medium or format) and adapt (remix, transform, and build upon the material for any purpose, even commercially), as long as the authors and the publisher are explicitly identified and properly acknowledged as the original source.

            RExPO23
            2
            Stockholm, Sweden
            25-26 October 2023
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            REPO4EU

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            Data sharing not applicable to this article as no datasets were generated or analysed during the current study.
            Pharmacology & Pharmaceutical medicine
            Drug repurposing,artificial intelligence,data mining,disease modules,protein structure prediction

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