Design Space Calculation by In Silico Robustness Simulation with Modeling Error Propagation in QbD Framework of RP-HPLC Method Development

Prediction of Analyte Retention Time in Liquid Chromatography

“…Optimized separations which were fully validated resulted from this process. Mokhtar et al 103 have employed design space methodology to model error propagation in in-silico robustness simulation of a QbD RPLC method for a mixture of 6 test analytes. They applied deliberate shifts in pH, gradient time, ternary solvent ratio, initial and final percentages of organic solvent in the gradient, and instrument dwell volume, structured according to a full factorial design.…”

“…DoE and QbD approaches have been used to predict retention in RPLC. − Habyalimana et al have used a design space optimization strategy to develop screening methods for 18 antiretroviral medicines and 4 major excipients used for the treatment of HIV/AIDS. They applied a D-Optimal experimental design based on three factors: pH, gradient time, and temperature and interpreted the responses (retention times at the beginning, apex, and end of the peak were modeled by a multivariate multiple linear model).…”

Key information related to quality by design (QbD) applications in analytical methods development

“…A fast HPLC screening method for the separation of eight antidiabetic compounds: pioglitazone (PZ), rosiglitazone (RZ), glyburide (GB), glimepiride (GM), gliquidone (GQ), gliclazide (GL), glipizide (GP), and repaglinide (RG), was proposed by Mokhtar et al [114]. DS was developed using an in silico simulation of practical robustness testing procedures.…”