Artificial intelligence-based drug repurposing with electronic health record clinical corroboration: A case for ketamine as a potential treatment for amphetamine-type stimulant use disorder

被引:0
|
作者
Gao, Zhenxiang [1 ]
Winhusen, T. John [2 ]
Gorenflo, Maria P. [1 ,3 ]
Dorney, Ian [1 ,4 ]
Ghitza, Udi E. [5 ]
Kaelber, David C. [6 ]
Xu, Rong [1 ]
机构
[1] Case Western Reserve Univ, Ctr Artificial Intelligence Drug Discovery, Sch Med, Cleveland, OH 44195 USA
[2] Univ Cincinnati, Coll Med, Ctr Addict Res, Cincinnati, OH 45221 USA
[3] Case Western Reserve Univ, Lerner Coll Med, Cleveland Clin, Cleveland, OH USA
[4] Case Western Reserve Univ, Sch Med, Cleveland, OH USA
[5] Natl Inst Drug Abuse NIDA, Ctr Clin Trials Network CCTN, NIH, Bethesda, MD USA
[6] Metro Hlth Syst, Ctr Clin Informat Res & Educ, Cleveland, OH USA
关键词
artificial intelligence; drug discovery; drug repurposing; electronic health records; ketamine; stimulant use disorder; DOUBLE-BLIND; CONTROLLED-TRIAL; METHAMPHETAMINE; DEPENDENCE; ASSOCIATION; COMORBIDITY; NALTREXONE; DEPRESSION; ADDICTION; RECEPTORS;
D O I
10.1111/add.16715
中图分类号
R194 [卫生标准、卫生检查、医药管理];
学科分类号
摘要
Background and aimsAmphetamine-type stimulants are the second-most used illicit drugs globally, yet there are no US Food and Drug Administration (FDA)-approved treatments for amphetamine-type stimulant use disorders (ATSUD). The aim of this study was to utilize a drug discovery framework that integrates artificial intelligence (AI)-based drug prediction, clinical corroboration and mechanism of action analysis to identify FDA-approved drugs that can be repurposed for treating ATSUD.Design and settingAn AI-based knowledge graph model was first utilized to prioritize FDA-approved drugs in their potential efficacy for treating ATSUD. Among the top 10 ranked candidate drugs, ketamine represented a novel candidate with few studies examining its effects on ATSUD. We therefore conducted a retrospective cohort study to assess the association between ketamine and ATSUD remission using US electronic health record (EHR) data. Finally, we analyzed the potential mechanisms of action of ketamine in the context of ATSUD.Participants and MeasurementsATSUD patients who received anesthesia (n = 3663) or were diagnosed with depression (n = 4328) between January 2019 and June 2022. The outcome measure was the diagnosis of ATSUD remission within one year of the drug prescription.FindingsKetamine for anesthesia in ATSUD patients was associated with greater ATSUD remission compared with other anesthetics: hazard ratio (HR) = 1.58, 95% confidence interval (CI) = 1.15-2.17. Similar results were found for ATSUD patients with depression when comparing ketamine with antidepressants and bupropion/mirtazapine with HRs of 1.51 (95% CI = 1.14-2.01) and 1.68 (95% CI = 1.18-2.38), respectively. Functional analyses demonstrated that ketamine targets several ATSUD-associated pathways including neuroactive ligand-receptor interaction and amphetamine addiction.ConclusionsThere appears to be an association between clinician-prescribed ketamine and higher remission rates in patients with amphetamine-type stimulant use disorders.
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页数:13
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