HPLC method transfer study for simultaneous determination of seven angiotensin II receptor blockers.

In this study, a sensitive high-performance liquid chromatography method was developed and validated for the simultaneous determination of seven angiotensin II receptor blockers, namely, hydrochlorothiazide, chlorthalidone, eprosartan mesylate, valsartan, losartan potassium, irbesartan, and candesartan cilexetil. Different chromatographic parameters were tested and fully optimized. Best chromatographic separation was accomplished on a reversed-phase octadecylsilyl column (250 × 4.6 mm id; 5 µm) under gradient elution using methanol/sodium phosphate monobasic buffer (0.01 M, pH 6.5) as mobile phase. The detection of target analytes was obtained at 254 nm. The pH of the buffer has been selected according to Marvin® sketch software. The proposed method was validated according to ICH guidelines and showed good precision (relative standard deviation < 1), good linearity (square of correlation coefficient ≥ 0.999), and high accuracy (between 98 and 102%) with detection limit and quantitation limit (40 and 160 ng/mL, respectively) for all the detected analytes.

Development of a fast high performance liquid chromatographic screening system for eight antidiabetic drugs by an improved methodology of in-silico robustness simulation.

Robustness of RP-HPLC methods is a crucial method quality attribute which has gained an increasing interest throughout the efforts to apply quality by design concepts in analytical methodology. Improvement to design space modeling approaches to represent method robustness was the goal of many previous works. Modeling of design spaces regarding to method robustness fulfils quality by design essence of ensuring method validity throughout the design space. The current work aimed to describe an improvement to robustness modeling of design spaces in context of RP-HPLC method development for screening of eight antidiabetic drugs. The described improvement consisted of in-silico simulation of practical robustness testing procedures thus had the advantage of modeling design spaces with higher confidence in estimated of method robustness. The proposed in-silico robustness test was performed as a full factorial design of simulated method conditions deliberate shifts for each predicted point in knowledge space with modeling error propagation. Design space was then calculated as zones exceeding a threshold probability to pass the simulated robustness testing. Potential design spaces were mapped for three different stationary phases as a function of gradient elution parameters, pH and ternary solvent ratio. A robust and fast separation for the eight compounds within less than 6 min was selected and confirmed through experimental robustness testing. The effectiveness of this approach regarding definition of design spaces with ensured robustness and desired objectives was demonstrated.