# AQbD-assisted central composite design optimization of an RP-HPLC method for simultaneous estimation of glimepiride and linagliptin in a synthetic mixture

“AQbD-assisted central composite design optimization of an RP-HPLC method for simultaneous estimation of glimepiride and linagliptin in a synthetic mixture” (2026), by H. B. Mehta et al. Chemistry research paper. Original abstract below, unchanged. A free PDF is available.

- Authors: H. B. Mehta, Patel Ayushi Shaileshbhai
- Published: November 4, 2026
- Field: Chemistry
- DOI: https://doi.org/10.1186/s13065-026-01953-4
- Free PDF: https://www.researchsquare.com/article/rs-9947795/latest.pdf

## Abstract

A robust and sensitive RP-HPLC method was developed for the simultaneous determination of Glimepiride and Linagliptin in synthetic mixtures by Design of Experiments approach using Central Composite Design to systematically optimize critical chromatographic variables and evaluate their interaction effects on method performance. This study describes the development and validation of an AQbD-based RP-HPLC method for the simultaneous estimation of Glimepiride (GLM) and Linagliptin (LNG) in synthetic mixtures. Critical chromatographic conditions were optimized using a three-factor, three-level Central Composite Design (CCD) to achieve a robust analytical method. Chromatographic separation was achieved on a Shim-pack C18 column (250 mm × 4.6 mm, 5 μm) using a mobile phase of acetonitrile and water (70:30, %v/v) at a flow rate of 1.0 mL/min, with detection at 254 nm. Central Composite Design was applied to study the influence of mobile phase composition, flow rate, and detection wavelength on responses including retention time, peak area, and resolution. A quadratic model was found to be significant based on ANOVA ( p < 0.05), with high coefficient of determination (R² > 0.99), confirming model fit and predictive capability. Response surface analysis and desirability function were used to establish optimized conditions. The method was validated as per ICH Q2(R2) guidelines, demonstrating linearity (r² > 0.999), high sensitivity (LOD: 0.0875 and 0.0821 µg/mL; LOQ: 0.2651 and 0.2487 µg/mL), accuracy (98.51%–99.94%), and precision (%RSD < 2%). The optimized method exhibited robustness against deliberate variations, confirming its suitability for routine pharmaceutical quality control.

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