Enhancement and validation of a quantitative GC–MS method for the detection of ∆9-THC and THC COOH in postmortem blood and urine samples

Cannabis is frequently detected in forensic investigations and is associated with an increased risk of fatal car crashes. This study aims to develop a method to detect and measure ∆9-tetrahydrocannabinol (∆9-THC) in blood and its metabolite, 11-nor-9-tetrahydrocannabinol-carboxylic acid (∆9-THC-COOH), in urine. The procedure employs two liquid-liquid extraction methods in conjunction with GC-MS in SIM mode. Both compounds were successfully processed, demonstrating the method's ease of use and efficiency. The method was validated for selectivity, identification capability, linearity, precision, limit of detection (LOD), limit of quantification (LOQ), and accuracy. Its effectiveness was further demonstrated by applying it to 30 authentic urine and blood samples from cannabis-related cases, establishing it as a valuable option for routine cannabinoid analysis in forensic toxicology labs.•The linearity range was 25-300 ng/mL for ∆9-THC in blood, and 50-300 ng/mL for ∆9-THC-COOH in urine, and calibration curves for both analytes showed R² values consistently above 0.989, confirming their linearity.•The LOD and LOQ for THC-COOH in hydrolyzed urine were 25 ng/mL and 50 ng/mL, respectively, and for THC in blood, they were 15 ng/mL and 25 ng/mL, respectively.•The variation coefficients were below 14%, and recoveries exceeded 81% for both compounds.

Authors

Institutions

Publication Details

Journal
MethodsX
Published
2024-09-19
DOI
https://doi.org/10.1016/j.mex.2024.102962
Citations
7
Primary Topic
Forensic Toxicology and Drug Analysis
Type
article
Field-Weighted Citation Impact
2.45
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Enhancement and validation of a quantitative GC–MS method for the detection of ∆9-THC and THC COOH in postmortem blood and urine samples

Farzaneh Jokar, Mehdi Forouzesh, Mohammad Kazem Koohi, Jalal Hassan et al.
7 citations
MethodsX
Forensic Toxicology and Drug Analysis
2.45
article

Enhancement and validation of a quantitative GC–MS method for the detection of ∆9-THC and THC COOH in postmortem blood and urine samples

Farzaneh Jokar, Mehdi Forouzesh, Mohammad Kazem Koohi, Jalal Hassan, Maryam Akhgari, Masoud Ghadipasha, Somayeh Paknahad
article en
7 citations

Abstract

Cannabis is frequently detected in forensic investigations and is associated with an increased risk of fatal car crashes. This study aims to develop a method to detect and measure ∆9-tetrahydrocannabinol (∆9-THC) in blood and its metabolite, 11-nor-9-tetrahydrocannabinol-carboxylic acid (∆9-THC-COOH), in urine. The procedure employs two liquid-liquid extraction methods in conjunction with GC-MS in SIM mode. Both compounds were successfully processed, demonstrating the method's ease of use and efficiency. The method was validated for selectivity, identification capability, linearity, precision, limit of detection (LOD), limit of quantification (LOQ), and accuracy. Its effectiveness was further demonstrated by applying it to 30 authentic urine and blood samples from cannabis-related cases, establishing it as a valuable option for routine cannabinoid analysis in forensic toxicology labs.•The linearity range was 25-300 ng/mL for ∆9-THC in blood, and 50-300 ng/mL for ∆9-THC-COOH in urine, and calibration curves for both analytes showed R² values consistently above 0.989, confirming their linearity.•The LOD and LOQ for THC-COOH in hydrolyzed urine were 25 ng/mL and 50 ng/mL, respectively, and for THC in blood, they were 15 ng/mL and 25 ng/mL, respectively.•The variation coefficients were below 14%, and recoveries exceeded 81% for both compounds.

MethodsXVol. 13
University of Tehran (IR), Iranian Legal Medicine Organization (IR)
Zero hunger
Openalex Percentile: Top 11%
Forensic Toxicology and Drug Analysis
2.45
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.