Lumefantrine and Glimepiride (IS) were extracted from human plasma by Precipitation followed by Solid phase extraction using Orochem (30 mg/1 CC) solid phase extraction cartridge. The chromatographic separation was performed on Hypurity C18 (50 cm×4.6 mm), 5 μ column. The mobile phase consisted of Acetonitrile: 2 mM Ammonium Acetate (pH: 3.5) (90:10, % v/v) was delivered at rate of 0.600 mL/min with Splitter. Detection and quantitation were performed by a triple quadrupole equipped with electro spray ionization and multiple reaction monitoring in positive ionization mode (API 3000). The most intense [M-H]- transition for Lume fantrine at m/z 528.0→510.0 and for IS at m/z 491.2→352.0 were used for quantification. The developed method was successfully applied for bioequivalence study of Lume fantrine. The method was found to linear over the range of 100-20000 ng/mL (r≥0.992). The lower limit of quantitation (LLOQ) was 100 ng/mL. The extraction recovery was above 75% for analyte and above 90% for IS. The intra and inter-day accuracy was found to 92.27% - 104.00%. The intra and inter-day precision expressed as % CV were 1.76% - 6.47%, respectively. The stability testing was also investigated and it was found that both drug and IS were quite stable. A simple, rapid, sensitive, accurate and precise LC-MS/MS method has been developed for the quantification of Lumefantrine from human plasma using Protein precipitation followed by SPE method. The method exhibited good linear response over the selected concentration range 100-20000 ng/mL. Selectivity and sensitivity were sufficient for detecting and quantifying Lumefantrine in human plasma. These features coupled with a short run time at 3.50 min compared to reported methods, facilitated a high analysis throughput, with the ability to quantify a larger number of clinical samples in a shorter time frame.
Citation: Patelia EM, Thakur R, Patel J (2015) Bio-Analytical Method Development and Validation for Estimation of Lume fantrine in Human Plasma by Using Lc-Ms/Ms. Biomedical Data Mining 3:111. doi: 10.4172/2090-4924.1000111