Repurposing ketamine to treat cocaine use disorder: integration of artificial intelligence-based prediction, expert evaluation, clinical corroboration and mechanism of action analyses
Zhen-Xiang Gao, T. Winhusen, Maria P Gorenflo, Udi E. Ghitza, Pamela B. Davis, D. Kaelber, Rong Xu
Addiction February 15, 2023 DOI: 10.1111/add.16168 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Observational cohort study using electronic health record data with propensity score matching, embedded in a drug repurposing strategy combining AI prediction, expert review, and genetic/pathway analysis Peer reviewed |
|---|---|
| Sample size | 15,652 |
| Population | Patients with cocaine use disorder identified in the TriNetX electronic health record database: 7742 who received anesthesia (3871 ketamine-exposed, 3871 anesthetic-controlled) and 7910 with depression (3955 ketamine-exposed, 3955 antidepressant-controlled) |
| Intervention | Ketamine |
| Duration | CUD remission diagnosis within 1 year of drug prescription |
| Topics | Esketamine Ketamine |
| Key findings | Among patients with cocaine use disorder, ketamine prescribed for anesthesia was associated with a higher one-year remission rate than other anesthetics (HR = 1.98, 95% CI = 1.42-2.78), and ketamine prescribed for depression was associated with a higher remission rate than antidepressants or midazolam (HR = 4.39, 95% CI = 2.89-6.68). The authors conclude ketamine appears to be a potential repurposed drug for cocaine use disorder. |
Abstract
Background and
Aims: Cocaine use disorder (CUD) is a significant public health issue for which there is no Food and Drug Administration (FDA) approved medication. Drug repurposing looks for new cost-effective uses of approved drugs. This study presents an integrated strategy to identify repurposed FDA-approved drugs for CUD treatment.
Design: Our drug repurposing strategy combines artificial intelligence (AI)-based drug prediction, expert panel review, clinical corroboration and mechanisms of action analysis being implemented in the National Drug Abuse Treatment Clinical Trials Network (CTN). Based on AI-based prediction and expert knowledge, ketamine was ranked as the top candidate for clinical corroboration via electronic health record (EHR) evaluation of CUD patient cohorts prescribed ketamine for anesthesia or depression compared with matched controls who received non-ketamine anesthesia or antidepressants/midazolam. Genetic and pathway enrichment analyses were performed to understand ketamine’s potential mechanisms of action in the context of CUD.
Setting: The study utilized TriNetX to access EHRs from more than 90 million patients world-wide. Genetic- and functional-level analyses used DisGeNet, Search Tool for Interactions of Chemicals and Kyoto Encyclopedia of Genes and Genomes databases.
Participants: A total of 7742 CUD patients who received anesthesia (3871 ketamine-exposed and 3871 anesthetic-controlled) and 7910 CUD patients with depression (3955 ketamine-exposed and 3955 antidepressant-controlled) were identified after propensity score-matching.
Measurements: EHR analysis outcome was a CUD remission diagnosis within 1 year of drug prescription.
Findings: Patients with CUD prescribed ketamine for anesthesia displayed a significantly higher rate of CUD remission compared with matched individuals prescribed other anesthetics [hazard ratio (HR) = 1.98, 95% confidence interval (CI) = 1.42–2.78]. Similarly, CUD patients prescribed ketamine for depression evidenced a significantly higher CUD remission ratio compared with matched patients prescribed antidepressants or midazolam (HR = 4.39, 95% CI = 2.89–6.68). The mechanism of action analysis revealed that ketamine directly targets multiple CUD-associated genes (BDNF, CNR1, DRD2, GABRA2, GABRB3, GAD1, OPRK1, OPRM1, SLC6A3, SLC6A4) and pathways implicated in neuroactive ligand-receptor interaction, cAMP signaling and cocaine abuse/dependence.
Conclusions: Ketamine appears to be a potential repurposed drug for treatment of cocaine use disorder.