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

• New strategy for design spaces calculation and modeling was described.
• This was achieved by mapping probability to pass an in-silico robustness test.
• The in-silico test included factorial design of method factors deliberate shifts.
• Modeling error was propagated through the simulated design results.
• This strategy enabled robust fast separation of eight antidiabetic compounds.

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.