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Trends in Drug Delivery Review Article

Artificial Intelligence in Drug Repurposing: A Short Impact Assessment

  1. Mekkanti Manasa Rekha Department of Pharmacy Practice, Aditya Bangalore Institute of Pharmacy Education and Research, Bangalore
  2. Soumitra Das Department of Pharmacy Practice, Aditya Bangalore Institute of Pharmacy Education and Research, Bangalore

Abstract

Artificial intelligence (AI) in pharmaceutical repurposing has become a game-changing tool that opens new avenues for the application of new drugs that have already been approved. Traditional drug discovery is a lengthy and expensive process, whereas AI can rapidly analyze vast datasets of biological, chemical, and clinical information to predict drug-disease interactions. AI-driven techniques, such as machine learning, natural language processing, and deep learning, enable the identification of potential repurposing candidates by analyzing molecular structures, gene expression profiles, and patient data. Recent success stories include AI models identifying drugs like Baricitinib for COVID-19 and different substances for uncommon illnesses, like Fragile X syndrome. AI's capacity to streamline the process of discovering drugs speeds up therapy development, cuts costs, and improves the accuracy of matching drugs to diseases, proving to be a valuable tool in combating various illnesses. Nonetheless, issues like data quality, AI model interpretability, and the requirement for clinical validation continue to be crucial areas for additional study.

Keywords

References (28)

  1. Haendel M, Vasilevsky N, Unni D, Bologa C, Harris N, Rehm H, et al. How many rare diseases are there? Nature Reviews Drug Discovery. 2019;19(2):77-78. doi:10.1038/d41573-019-00180-y
  2. Scherman D, Fetro C. Drug repositioning for rare diseases: Knowledge-based success stories. Therapies. 2020;75(2):161-167. doi:10.1016/j.therap.2020.02.007
  3. Roessler HI, Knoers NVAM, van Haelst MM, van Haaften G. Drug Repurposing for Rare Diseases. Trends in Pharmacological Sciences. 2021;42(4):255-267. doi:10.1016/j.tips.2021.01.003
  4. Choi, RY, Aaron, SC, Jayashree, K-C, Michael, FC, and Peter, JC. “Introduction to Machine Learning, Neural Networks, and Deep Learning.” Translational Vision Science & Technology (n.d.). 9: (2):14. doi:10.1167/tvst.9.2.14
  5. Khurana D, Koli A, Khatter K, Singh S. Natural language processing: state of the art, current trends and challenges. Multimedia Tools and Applications. 2022;82(3):3713-3744. doi:10.1007/s11042-022-13428-4
  6. Alowais SA, Alghamdi SS, Alsuhebany N, Alqahtani T, Alshaya AI, Almohareb SN, et al. Revolutionizing healthcare: the role of artificial intelligence in clinical practice. BMC Medical Education. 2023;23(1). doi:10.1186/s12909-023-04698-z
  7. Bajwa J, Munir U, Nori A, Williams B. Artificial intelligence in healthcare: transforming the practice of medicine. Future Healthcare Journal. 2021;8(2):e188-e194. doi:10.7861/fhj.2021-0095
  8. Brasil S, Pascoal C, Francisco R, dos Reis Ferreira V, A. Videira P, Valadão G. Artificial Intelligence (AI) in Rare Diseases: Is the Future Brighter? Genes. 2019;10(12):978. doi:10.3390/genes10120978
  9. Jonker AH, O’Connor D, Cavaller-Bellaubi M, Fetro C, Gogou M, ’T Hoen PAC, et al. Drug repurposing for rare: progress and opportunities for the rare disease community. Frontiers in Medicine. 2024;11. doi:10.3389/fmed.2024.1352803
  10. van der Pol KH, Aljofan M, Blin O, Cornel JH, Rongen GA, Woestelandt AG, et al. Drug Repurposing of Generic Drugs: Challenges and the Potential Role for Government. Applied Health Economics and Health Policy. 2023;21(6):831-840. doi:10.1007/s40258-023-00816-6
  11. Cha Y, Erez T, Reynolds IJ, Kumar D, Ross J, Koytiger G, Kusko R, Zeskind B, Risso S, Kagan E, Papapetropoulos S. Drug repurposing from the perspective of pharmaceutical companies. British journal of pharmacology. 2018 Jan;175(2):168-80.
  12. Ekins S, Gerlach J, Zorn KM, Antonio BM, Lin Z, Gerlach A. Repurposing Approved Drugs as Inhibitors of Kv7.1 and Nav1.8 to Treat Pitt Hopkins Syndrome. Pharmaceutical Research. 2019;36(9). doi:10.1007/s11095-019-2671-y
  13. Sosa, DN, Derry, A, Guo, M, Wei, E, Brinton, C, and Altman, RB. A literature-based knowledge graph embedding method for identifying drug repurposing opportunities in rare diseases. Pac Symp Biocomput. (2020) 25:463–74.
  14. Esmail S, Danter WR. Artificially Induced Pluripotent Stem Cell-Derived Whole-Brain Organoid for Modelling the Pathophysiology of Metachromatic Leukodystrophy and Drug Repurposing. Biomedicines. 2021;9(4):440. doi:10.3390/biomedicines9040440
  15. Cong Y, Shintani M, Imanari F, Osada N, Endo T. A New Approach to Drug Repurposing with Two-Stage Prediction, Machine Learning, and Unsupervised Clustering of Gene Expression. OMICS: A Journal of Integrative Biology. 2022;26(6):339-347. doi:10.1089/omi.2022.0026
  16. Foksinska A, Crowder CM, Crouse AB, Henrikson J, Byrd WE, Rosenblatt G, et al. The precision medicine process for treating rare disease using the artificial intelligence tool mediKanren. Frontiers in Artificial Intelligence. 2022;5. doi:10.3389/frai.2022.910216
  17. Zhu C, Xia X, Li N, Zhong F, Yang Z, Liu L. RDKG-115: Assisting drug repurposing and discovery for rare diseases by trimodal knowledge graph embedding. Computers in Biology and Medicine. 2023;164:107262. doi:10.1016/j.compbiomed.2023.107262
  18. Every Cure. (2024). Unlocking the hidden potential of existing drugs to save lives. Available at: https://everycure.org/. (Consulté le mars 17, 2024)
  19. REPO4EU. (2024). Euro-global platform for drug repurposing. Available at: https://repo4.eu/. (Consulté le mars 18, 2024)
  20. Open Targets. (2024). Available at: https://www.opentargets.org/. (Consulté le 17 mars, 2024)
  21. Broad Institute. (2019). Drug Repurposing Hub. Available at: https://www.broadinstitute.org/drug-repurposing-hub
  22. Corsello SM, Bittker JA, Liu Z, Gould J, McCarren P, Hirschman JE, et al. The Drug Repurposing Hub: a next-generation drug library and information resource. Nature Medicine. 2017;23(4):405-408. doi:10.1038/nm.4306
  23. EURORDIS. (2024). REMEDi4ALL, an ambitious EU-funded research initiative, launches to drive forward the repurposing of medicines in Europe. Available at: https://www.eurordis.org/press-release-remedi4all/. (Consulté le mars 18, 2024)
  24. AFM Téléthon. (2023). I-Stem, coordinateur du consortium de recherche européen DREAMS associant intelligence artificielle, cellules souches et criblage pharmacologique pour traiter des maladies neuromusculaires. Available at: https://www.afm-telethon.fr/fr/communiques-de-presse/i-stem-coordinateur-du-consortium-de-recherche-europeen-dreams-associant
  25. HealX. (2024). AI drug discovery. Rare disease treatment. Available at: https://healx.ai/. (Consulté le mars 17, 2024)
  26. Biovista. (2024). Drug positioning and prioritization-drug repositioning. Biovista drug positioning and prioritization (blog). Available at: https://www.biovista.com/solutions/drug-repositioning/. (Consulté le mars 17, 2024)
  27. Visibelli A, Roncaglia B, Spiga O, Santucci A. The Impact of Artificial Intelligence in the Odyssey of Rare Diseases. Biomedicines. 2023;11(3):887. doi:10.3390/biomedicines11030887
  28. Wojtara M, Rana E, Rahman T, Khanna P, Singh H. Artificial intelligence in rare disease diagnosis and treatment. Clinical and Translational Science. 2023;16(11):2106-2111. doi:10.1111/cts.13619
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