Depressive DisordersSubstance Use Disorders (SUD)Health Economics & ReimbursementPublic Health, Prevention & Behaviour ChangeKetamine

Repurposing ketamine to treat cocaine use disorder: Integration of artificial intelligence-based prediction, expert evaluation, clinical corroboration, and mechanism of action analyses

This analysis of ketamine data (3800 patients who received ketamine for anaesthesia, and the same number of controls) suggest that ketamine may be useful for treating cocaine use disorder (CUD).

Authors

  • Gao, Z.
  • Winhusen, |. T. J.
  • Gorenflo, |. M.

Published

Addiction
meta Study

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.

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Research Summary of 'Repurposing ketamine to treat cocaine use disorder: Integration of artificial intelligence-based prediction, expert evaluation, clinical corroboration, and mechanism of action analyses'

Introduction

Cocaine use disorder (CUD) affects over 1.3 million adults in the United States and is associated with substantial morbidity and mortality, yet no FDA-approved pharmacotherapies exist. Standard care relies on psychosocial interventions, which are limited in effectiveness and reach. Drug repurposing offers a faster, less costly route to identify candidate medications from already approved drugs, and computational approaches such as network-, structure- and AI-based methods can generate large numbers of repurposing signals. However, many candidates flagged by such approaches fail in clinical testing, so additional vetting using clinical data and expert judgement is desirable. Gao and colleagues describe an integrated repurposing strategy that combines an AI-driven knowledge-graph prediction system (KG-Predict), advisory committee review, retrospective electronic health record (EHR) corroboration, and genetic/pathway analyses. The paper reports the outcome of applying this pipeline to CUD: ketamine emerged as a top candidate after AI ranking and unanimous expert recommendation, and the investigators then tested whether ketamine exposure in routine clinical care was associated with subsequent CUD remission and examined potential molecular pathways linking ketamine to CUD biology.

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Study Details

References (4)

Papers cited by this study that are also in Blossom

Replication of Ketamine’s Antidepressant Efficacy in Bipolar Depression: A Randomized Controlled Add-On Trial

Zarate, C. A., Brutsche, N. E., Ibrahim, L. et al. · Biological Psychiatry (2012)

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Ketamine for the treatment of addiction: Evidence and potential mechanisms

Ezquerra-Romano, I. I., Lawn, W., Krupitsky, E. M. et al. · Neuropharmacology (2018)

Mechanisms of ketamine action as an antidepressant

Zanos, P., Gould, T. D. · Molecular Psychiatry (2018)

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