Preparation of Antihypertensive Drugs in Biological Matrix with Solvent Front Position Extraction for LC-MS/MS...

Area of Science:

• Analytical Chemistry
• Pharmaceutical Analysis

Background:

• Accurate quantification of antihypertensive drugs in biological matrices is crucial for therapeutic drug monitoring and pharmacokinetic studies.
• Traditional sample preparation methods can be time-consuming, labor-intensive, and require significant solvent volumes.

Purpose of the Study:

• To develop and validate a novel automated sample preparation method for simultaneous analysis of multiple antihypertensive drugs.
• To assess the efficiency, accuracy, and precision of the developed method using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS).

Main Methods:

• Utilized a solvent front position extraction procedure with a prototype horizontal chamber and a 3D printer-driven moving pipette.
• Investigated seven antihypertensive drugs: ramipril, lercanidipine, indapamide, valsartan, hydrochlorothiazide, perindopril, and nebivolol.
• Quantified separated substances from bovine serum albumin using LC-MS/MS.

Main Results:

• The automated method enabled simultaneous preparation of multiple samples, reducing manual operations and solvent consumption.
• Satisfactory quantitative results were obtained for most drugs, with %RSD values around 5% for six out of seven substances.
• The method demonstrated suitable accuracy, with relative error percentages below 10% for most drugs.
• Achieved low limits of detection (LOD) and quantification (LOQ) in the µg/L range.

Conclusions:

• The developed automated sample preparation technique is efficient and suitable for the quantitative analysis of antihypertensive drugs in complex biological matrices.
• The 3D-printed device offers advantages in terms of reduced manual labor, solvent usage, and synchronized sample processing.
• The method provides reliable and accurate results, making it a valuable tool for pharmaceutical analysis and therapeutic drug monitoring.