Ophthalmic drug discovery and development using artificial intelligence and digital health technologies
Cheng, Haoran Wong, Joy Le Yi Quek, Chrystie Wan Ning Goldberg, Jeffrey L Mahajan, Vinit B Wong, Tien Yin Mehta, Jodhbir S Ting, Daniel S W Ting, Darren Shu Jeng
Cheng, Haoran
Wong, Joy Le Yi
Quek, Chrystie Wan Ning
Goldberg, Jeffrey L
Mahajan, Vinit B
Wong, Tien Yin
Mehta, Jodhbir S
Ting, Daniel S W
Ting, Darren Shu Jeng
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Affiliation
Singapore National Eye Center; National University of Singapore; Stanford University; Sandwell and West Birmingham NHS Trust; et al.
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Publication date
2025-09-25
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Abstract
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.
Citation
Cheng H, Wong JLY, Quek CWN, Goldberg JL, Mahajan VB, Wong TY, Mehta JS, Ting DSW, Ting DSJ. Ophthalmic drug discovery and development using artificial intelligence and digital health technologies. NPJ Digit Med. 2025 Sep 25;8(1):573. doi: 10.1038/s41746-025-01954-y
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Article