Ophthalmic drug discovery and development using artificial intelligence and digital health technologies
Year: 2025
Type: review
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.
Source: npj Digital Medicine
Institutions: National University of Singapore, Singapore National Eye Center, Singapore Eye Research Institute, Duke-NUS Medical School, Stanford University, Beijing Tsinghua Chang Gung Hospital, Tsinghua University, University of Nottingham, SingHealth Duke-NUS Academic Medical Centre, Birmingham and Midland Eye Centre, University of Birmingham
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $4,090
Funders: Birmingham Health Partners, Research to Prevent Blindness, UK Research and Innovation, Duke-NUS Medical School, Fight for Sight UK, Agency for Science, Technology and Research, National Natural Science Foundation of China, Russian Science Foundation, Medical Research Council, National Medical Research Council, National Eye Institute
Awards: G1115584191, G1431295129, G1519060760, G2117806883, G2420765693, G3470946970, G3601786360, G4058520128, Development of Novel Antimicrobial Peptides for Infectious Keratitis and Antimicrobial Resistance, G5081959986, G6190647152, G6203276117, G6816730382, G7192684402, G7503630407, G7661547612, G8160389401, G8904608324, MRC IAA 2021 University of Birmingham, Stanford Vision Research Core
OpenAlex ID: W4414516182