Detection of clinically significant drug-drug interactions in serotonin syndrome: a multisource real-world data and pharmacovigilance study.

Background: Serotonin syndrome (SS) is a potentially life-threatening condition increasingly driven by complex drug-drug interactions (DDIs) as serotonergic agents expand beyond psychiatry into pain management and infectious disease treatment. Current clinical decision support tools often exhibit inconsistencies in detecting these risks, leading to potential under-recognition of severe interactions. Objectives: This study aimed to detect and validate clinically significant DDIs associated with SS by integrating multisource real-world data. We sought to identify high-priority drug combinations, evaluate the concordance of major DDI checking tools, and highlight critical information gaps to improve patient safety strategies. Design: A multisource, retrospective study combining a systematic literature review, a disproportionality analysis of spontaneous adverse event reports, and a comparative cross-sectional evaluation of online DDI databases. Methods: This study employed a multisource approach to detect and evaluate SS-related DDIs. We integrated findings from a systematic literature review (up to June 2025), a disproportionality analysis using the FDA Adverse Event Reporting System (FAERS) with four frequency statistical models, and a comparative assessment of five major DDI checkers (Micromedex, Lexi-Interact, Epocrates, Medscape, and Drugs.com). Results: The systematic review identified high-risk interactions involving not only antidepressants but also non-psychotropic drugs such as linezolid, fentanyl, and methylene blue. FAERS data revealed strong signals for combinations such as linezolid-sertraline and fentanyl-venlafaxine, indicating a rising trend in SS reporting over the past two decades. Evaluation of DDI checkers demonstrated significant discrepancies in sensitivity and severity grading. Notably, 10.16% were not indexed in any of the five databases, including several clinically documented DDIs (e.g., aripiprazole-paracetamol and trazodone-pantoprazole), highlighting critical information gaps. Conclusion: SS remains a significant clinical risk driven by increasingly complex polypharmacy. Relying on a single DDI checker may lead to an underestimation of risk due to inconsistent indexing and severity ratings. Hospital pharmacists should integrate multisource data and maintain high clinical vigilance, particularly for "hidden" serotonergic agents such as certain opioids and antibiotics, to ensure medication safety.