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Globally, drug discovery and development programs are complex, multi-decade long and prohibitively expensive. Artificial intelligence (AI) and other digital health technologies have the potential to enhance and accelerate each stage of drug discovery and development, from pre-clinical target identification to post-market repurposing, and even revolutionize the entire process. Using ophthalmology as an example, this review highlights recent AI and digital health innovations in different phases of drug discovery and development. By leveraging machine learning algorithms and vast clinical and multiomics datasets, AI can rapidly identify and validate new drug targets, optimize lead compounds, and predict pharmacokinetics, pharmacodynamics and toxicity. AI-assisted multi-modal ocular biomarkers may improve treatment monitoring and support personalized medicine. Integrating AI shortens development timelines, enhances efficiency, reduces costs, and increases the success rate of new drugs. Currently, standardized regulations for AI in ocular drug development are still lacking and urgently needed to ensure safe and equitable implementation.
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1 Singapore Eye Research Institute, Singapore National Eye Center, Singapore, Singapore (ROR: https://ror.org/029nvrb94) (GRID: grid.419272.b) (ISNI: 0000 0000 9960 1711); Duke-NUS Medical School, National University of Singapore, Singapore, Singapore (ROR: https://ror.org/01tgyzw49) (GRID: grid.4280.e) (ISNI: 0000 0001 2180 6431)
2 Singapore Eye Research Institute, Singapore National Eye Center, Singapore, Singapore (ROR: https://ror.org/029nvrb94) (GRID: grid.419272.b) (ISNI: 0000 0000 9960 1711)
3 Spencer Center for Vision Research, Byers Eye Institute, Stanford University, Stanford, CA, USA (ROR: https://ror.org/00f54p054) (GRID: grid.168010.e) (ISNI: 0000 0004 1936 8956)
4 Singapore Eye Research Institute, Singapore National Eye Center, Singapore, Singapore (ROR: https://ror.org/029nvrb94) (GRID: grid.419272.b) (ISNI: 0000 0000 9960 1711); Beijing Visual Science and Translational Eye Research Institute (BERI), Beijing Tsinghua Changgung Hospital Eye Center, Tsinghua Medicine, Tsinghua University, Beijing, China (ROR: https://ror.org/03cve4549) (GRID: grid.12527.33) (ISNI: 0000 0001 0662 3178); School of Clinical Medicine, Beijing Tsinghua Changgung Hospital, Tsinghua Medicine, Tsinghua University, Beijing, China (ROR: https://ror.org/03cve4549) (GRID: grid.12527.33) (ISNI: 0000 0001 0662 3178)
5 Singapore Eye Research Institute, Singapore National Eye Center, Singapore, Singapore (ROR: https://ror.org/029nvrb94) (GRID: grid.419272.b) (ISNI: 0000 0000 9960 1711); Duke-NUS Medical School, National University of Singapore, Singapore, Singapore (ROR: https://ror.org/01tgyzw49) (GRID: grid.4280.e) (ISNI: 0000 0001 2180 6431); Spencer Center for Vision Research, Byers Eye Institute, Stanford University, Stanford, CA, USA (ROR: https://ror.org/00f54p054) (GRID: grid.168010.e) (ISNI: 0000 0004 1936 8956)
6 Singapore Eye Research Institute, Singapore National Eye Center, Singapore, Singapore (ROR: https://ror.org/029nvrb94) (GRID: grid.419272.b) (ISNI: 0000 0000 9960 1711); Duke-NUS Medical School, National University of Singapore, Singapore, Singapore (ROR: https://ror.org/01tgyzw49) (GRID: grid.4280.e) (ISNI: 0000 0001 2180 6431); Academic Unit of Ophthalmology, Department of Inflammation and Ageing, School of Infection, Inflammation and Immunology, College of Medicine and Health, University of Birmingham, Birmingham, UK (ROR: https://ror.org/03angcq70) (GRID: grid.6572.6) (ISNI: 0000 0004 1936 7486); Birmingham and Midland Eye Centre, Sandwell and West Birmingham NHS Trust, Birmingham, UK (ROR: https://ror.org/01n70p029) (GRID: grid.414513.6) (ISNI: 0000 0004 0399 8996); Academic Ophthalmology, School of Medicine, University of Nottingham, Nottingham, UK (ROR: https://ror.org/01ee9ar58) (GRID: grid.4563.4) (ISNI: 0000 0004 1936 8868)