PMID- 37274099 OWN - NLM STAT- PubMed-not-MEDLINE LR - 20240421 IS - 1663-9812 (Print) IS - 1663-9812 (Electronic) IS - 1663-9812 (Linking) VI - 14 DP - 2023 TI - Drug repurposing for reducing the risk of cataract extraction in patients with diabetes mellitus: integration of artificial intelligence-based drug prediction and clinical corroboration. PG - 1181711 LID - 10.3389/fphar.2023.1181711 [doi] LID - 1181711 AB - Diabetes mellitus (DM) increases the incidence of age-related cataracts. 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 effects. We developed a drug discovery strategy that combines AI-based potential candidate prediction among 2650 Food and Drug Administration (FDA)-approved drugs with clinical corroboration leveraging multicenter electronic health records (EHRs) of approximately 800,000 cataract patients from the TriNetX platform. Among the top-10 AI-predicted repurposed candidate drugs, we identified three DM diagnostic ICD code groups, such as cataract patients with type 1 diabetes mellitus (T1DM), type 2 diabetes mellitus (T2DM), or hyperglycemia, and conducted retrospective cohort analyses to evaluate the efficacy of these candidate drugs in 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 T2DM and hyperglycemia but not in T1DM patient groups. The suppressive effects of aspirin, acetylcysteine, and ibuprofen waned over time, while those of melatonin became stronger in both genders. Thus, the four repositioned drugs have the potential to delay cataract progression in both genders. All four drugs share the ability to directly or indirectly inhibit cyclooxygenase-2 (COX-2), an enzyme that is increased by multiple cataractogenic stimuli. CI - Copyright (c) 2023 Gao, Gorenflo, Kaelber, Monnier and Xu. FAU - Gao, Zhenxiang AU - Gao Z AD - Center for Artificial Intelligence in Drug Discovery, School of Medicine, Case Western Reserve University, Cleveland, OH, United States. FAU - Gorenflo, Maria AU - Gorenflo M AD - Center for Artificial Intelligence in Drug Discovery, School of Medicine, Case Western Reserve University, Cleveland, OH, United States. AD - Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, OH, United States. FAU - Kaelber, David C AU - Kaelber DC AD - The Center for Clinical Informatics Research and Education, The Metro Health System, Cleveland, OH, United States. FAU - Monnier, Vincent M AU - Monnier VM AD - Department of Pathology and Biochemistry, School of Medicine, Case Western Reserve University, Cleveland, OH, United States. FAU - Xu, Rong AU - Xu R AD - Center for Artificial Intelligence in Drug Discovery, School of Medicine, Case Western Reserve University, Cleveland, OH, United States. LA - eng GR - P30 EY011373/EY/NEI NIH HHS/United States GR - UM1 TR004528/TR/NCATS NIH HHS/United States PT - Journal Article DEP - 20230518 PL - Switzerland TA - Front Pharmacol JT - Frontiers in pharmacology JID - 101548923 PMC - PMC10232753 OTO - NOTNLM OT - acetylcysteine OT - aging OT - aspirin OT - cataract surgery OT - ibuprofen OT - melatonin OT - pharmacological prevention COIS- The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. EDAT- 2023/06/05 13:04 MHDA- 2023/06/05 13:05 PMCR- 2023/05/18 CRDT- 2023/06/05 11:57 PHST- 2023/03/14 00:00 [received] PHST- 2023/05/05 00:00 [accepted] PHST- 2023/06/05 13:05 [medline] PHST- 2023/06/05 13:04 [pubmed] PHST- 2023/06/05 11:57 [entrez] PHST- 2023/05/18 00:00 [pmc-release] AID - 1181711 [pii] AID - 10.3389/fphar.2023.1181711 [doi] PST - epublish SO - Front Pharmacol. 2023 May 18;14:1181711. doi: 10.3389/fphar.2023.1181711. eCollection 2023.