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.
Cheng et al. (Thu,) studied this question.