384 Integrating pharmacogenomics into opioid prescribing: Improving clinical outcomes and reducing adverse effects

Objectives/Goals: This research aims to develop a regulatory and clinical framework that integrates pharmacogenomic testing into opioid prescribing in order to optimize analgesic efficacy, minimize toxicity, and reduce the incidence of serious adverse events in chronic pain and palliative care populations. Methods/Study Population: A structured literature review was conducted using PubMed, Google Scholar, and ClinicalTrials.gov (2010–2025) with the terms “CYP2D6,” “COMT,” “OPRM1,” “opioid,” “pharmacogenomics,” and “precision dosing.” Human studies evaluating genotype–response, adverse events, or dosing variability were included. The FDA REMS database and Federal Register were reviewed to determine how pharmacogenomic testing could be integrated into existing Elements to Assure Safe Use. CPIC and PharmGKB guidelines were consulted to confirm gene–drug clinical relevance, while CMS reimbursement data were analyzed to assess coverage feasibility and implementation barriers. Results/Anticipated Results: Clinical trial “Pharmacogenetics and Pharmacokinetics of Oxycodone to Personalize Post-Operative Pain Management” shows that CYP2D6 genotype significantly alters oxycodone metabolism and analgesic response. Poor metabolizers experience reduced pain relief, while ultra-rapid metabolizers face increased toxicity with codeine, tramadol, and oxycodone. COMT variants affect pain sensitivity and morphine dosing, and OPRM1 A118G influences receptor binding and opioid response. Although opioid REMS programs do not include PGx testing, Vanda v. West-Ward (2018) supports integration, while CMS data show higher reimbursement for multigene panels ~74% than single-gene tests ~43%, reinforcing feasibility. Discussion/Significance of Impact: Adverse drug reactions remain a leading cause of preventable mortality. Integrating pharmacogenomic testing into REMS would advance precision opioid prescribing, reduce toxicity, and improve pain management while creating a scalable model for personalized therapeutics.