Opioid quantification via microsampling techniques to assess opioid use in human laboratory studies

• Published in: Scientific reports Vol. 15; no. 1; pp. 17678 - 12
• Main Authors: Fariha, Ramisa, Rothkopf, Emma, Haass-Koffler, Carolina L., Tripathi, Anubhav
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 21.05.2025; Nature Publishing Group; Nature Portfolio
• Subjects: 631/45/320; 639/166/985; 692/308/2779/777; Adult; Analgesics, Opioid - blood; Analgesics, Opioid - urine; Automation; Buprenorphine; Buprenorphine - therapeutic use; Chromatography, Liquid - methods; Clinical trials; Cross-reactivity; Data collection; Drug abuse; Drug addiction; Female; Humanities and Social Sciences; Humans; Male; Methadone; Methadone - therapeutic use; multidisciplinary; Narcotics; Opioid-Related Disorders - blood; Opioid-Related Disorders - diagnosis; Opioid-Related Disorders - drug therapy; Opioid-Related Disorders - urine; Opioids; Oxytocin; Patients; Science; Science (multidisciplinary); Substance Abuse Detection - methods; Tandem Mass Spectrometry - methods
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-025-99130-5

Despite progress in neurobiological studies with human subjects, sample availability remains a challenge. Urine samples, widely used for screening, suffer from false-positive results due to immunoassay cross-reactivity. Serum, used for confirmatory testing, offers advantages but faces limitations due to blood collection. Microsamples, with a working volume less than 50 μL, present an ideal strategy for robust quantitative data collection in investigations and human laboratory studies. We developed, validated, and automated a serum-based LC-MS/MS assay for accurate quantification of six opioids using only 20 μL of patient samples. Our method, applied in a clinical trial with patients with opioid use disorder (N = 20) receiving intranasal oxytocin, or placebo, for one week in addition to opioid agonist therapy (buprenorphine or methadone). We quantified six different opioids, undetected by urine strip tests, that were used by patients during the treatment phase. Our high-throughput, automated approach surpasses existing methods in literature, enhancing efficiency in multi-matrix studies.