4.5 Article

Analysis of abuse drugs in urine using surfactant-assisted dispersive liquid-liquid microextraction

Journal

JOURNAL OF SEPARATION SCIENCE
Volume 34, Issue 14, Pages 1722-1729

Publisher

WILEY-V C H VERLAG GMBH
DOI: 10.1002/jssc.201100132

Keywords

Abuse drugs; Cannabinoids; Response surface methodology; Surfactant-assisted dispersive liquid-liquid microextraction; Urine sample

Funding

  1. Tarbiat Modares University
  2. Research Centers of Antinarcotics Police, Iran

Ask authors/readers for more resources

The process of surfactant-assisted dispersive liquid-liquid microextraction (SA-DLLME) followed by high-performance liquid chromatography-UV detection was successfully applied for the extraction and determination of selected cannabinoids (cannabidiol, Delta(9)-tetrahydrocannabinol, and cannabinol) in urine samples. The effective parameters on the extraction efficiency were studied and optimized utilizing two different optimization methods: one variable at a time (OVAT) and face center design (FCD). Under the optimum conditions (extraction solvent and its volume, toluene, 85 mu L; disperser agent and its concentration, 1.0 mL of ultra-pure water containing 0.5 mmol/L tetradecyl tremethyl ammonium bromide (TTAB); sample pH, 2.0 and salt concentration, 11% w/v NaCl), the limits of detection of the method were in the range of 0.1-0.5 mu g/L and the repeatability and reproducibility of the proposed method, expressed as relative deviation, varied between 4.1 and 8.5% and 6.7 and 11.6%, respectively. Linearity was found to be in the range of 1.0-200 mu g/L and under the optimum conditions, the preconcentration factors (PFs) were between 190 and 292. This proposed method was successfully applied in the analysis of three male advocate urine samples and good recoveries were obtained.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.5
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available