Metabolite-targeted LC-HRMS quantification of emerging indazole-based synthetic cannabinoids in urine samples from an addiction treatment cohort.

Eroglu Icli H.; Arslan Z.; Yener Orum T.; Bulut C.; Kazdal F.; Civek S.; Umut G.; Elci A.; Turkmen Z. · Journal of chromatography. B, Analytical technologies in the biomedical and life sciences · 2026

**Background & Methods** This analytical validation study developed and tested a high-resolution liquid chromatography-high-resolution mass spectrometry (LC-HRMS) method to detect eight indazole-based synthetic cannabinoid metabolites in urine samples. The validated method was applied to 50 authentic urine specimens from treatment-seeking individuals at an addiction treatment clinic to assess exposure prevalence and patterns. **Key Findings** • The LC-HRMS method demonstrated robust analytical performance with limits of detection (LOD) of 0.01–0.46 ng/mL, limits of quantification (LOQ) of 0.04–1.53 ng/mL, recovery rates of 81.54–111.72%, and acceptable precision (RSD 5.12–15.03%) and matrix effects (75.92–100.03%). • Seventy-six percent (38/50) of urine samples tested positive for at least one synthetic cannabinoid marker, predominantly MDMB-4en-PINACA butanoic acid (62% of samples) and MDMB-INACA 3,3-dimethylbutanoic acid (42%), representing the first validated quantitative urine data for the latter marker. • Frequent co-detection of multiple markers across MDMB-PINACA, MDMB-BINACA, and ADB-BUTINACA analogs indicated widespread polydrug synthetic cannabinoid use within the treatment-seeking cohort, with the method successfully tracking current trends in emerging drug exposure. **Dosage & Administration** Not reported. **Safety & Adverse Effects** Not reported. **Evidence Quality** This is an analytical methods validation study with secondary application to a clinical cohort, representing lower-level evidence (Level IV). Limitations include: small sample size (n=50) from a single treatment facility limiting generalizability; lack of clinical outcome data or symptomatology correlation; cross-sectional design precluding temporal trend analysis; and inability to establish causality between metabolite detection and clinical presentations. Strengths include rigorous analytical validation with comprehensive quality assurance metrics and authentic clinical specimens. The study primarily contributes methodological capacity for detecting emerging synthetic cannabinoid exposure rather than clinical or epidemiological evidence regarding health effects or treatment outcomes.

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