Drug repurposing for reducing the risk of cataract extraction in patients with diabetes mellitus: integration of artificial intelligence-based drug prediction and clinical corroboration - Gao, Zhenxiang; Gorenflo, Maria; Kaelber, David C.; Monnier, Vincent M.; Xu, Rong (Frontiers in Pharmacology, 2023)
Diabetes mellitus (DM) increases the incidence of age-related cataract. Currently no medication is approved or known to delay clinical cataract progression. Using a novel approach based on AI we searched for drugs with potential cataract surgery suppressing effect. We developed a drug discovery strategy that combines AI-based potential candidate prediction among 2650 food and drug administration (FDA)-approved drugs and clinical corroboration leveraging multicenter electronic health records (EHRs) of approximately 800,000 cataract patients from TriNetX platform. Among top-10 AI predicted repurposed candidate drugs, we identified three DM diagnostic ICD Code groups including cataract patients with type 1 diabetes mellitus (T1DM), type 2 diabetes mellitus (T2DM), or hyperglycemia, and conducted retrospective cohorts’ analyses to evaluate the efficacy of these candidate drugs on reducing the risk of cataract extraction. Aspirin, Melatonin and Ibuprofen were associated with a reduced 5, 10 and 20-year cataract extraction risk in all types of diabetes. Acetylcysteine was associated with a reduced 5, 10 and 20-year cataract extraction risk in the T2DM and hyperglycemia but not T1DM patient groups. Suppressive effects of Aspirin, Acetylcysteine and Ibuprofen waned over time, while that of Melatonin became stronger in both genders. Thus, four repositioned drugs have the potential to delay cataract progression in both genders. All four drugs share in common the ability to directly or indirectly inhibit cyclooxygenase-2 (COX-2), an enzyme that is increased by multiple cataractogenic stimuli.