A Systematic Design Of Experiment-Driven High Performance Thin Layer Chromatography Approach for the Quantification of Glimepiride and Linagliptin in Synthetic Blends

Background

Type 2 Diabetes Mellitus (T2DM) often requires combination therapy for improvement of blood glucose regulation, where Linagliptin (a DPP-4 inhibitor) and Glimepiride (a sulfonylurea) act synergistically. Quality assurance of such combinations necessitates dependable on analytical methods. However, reports on their simultaneous estimation are limited. The present study focuses on developing and validating a precise, accurate, and robust HPTLC method for the quantification of Linagliptin and Glimepiride in bulk and synthetic mixtures using a Design of Experiments (DoE) approach. Hence the present manuscript describes the development and subsequent validation of a precise, accurate and robust HPTLC method for the simultaneous quantification of Glimepiride and Linagliptin in bulk as well as synthetic mixture using DoE approach.

Materials and Methods

The HPTLC method was performed using silica gel 60 F₂₅₄ pre-coated plates as the stationary phase, with a mobile phase consisting of a Methanol: Toluene: Ethyl Acetate: Chloroform [2:3:0.5:4.5 v/v/v/v] mixture and detection being carried out densitometrically at 259 nm. The validated method was found to be in conformance to ICH Q2 (R2) guideline and suitable for system suitability, linearity, accuracy, precision and robustness. However, keeping solvent front in view the robustness was studied by fractional factorial design (2⁴⁻¹), taking into account variables such as solvent front, wavelength, ethyl acetate volume, and chamber saturation time.

Results

The current novel method is found to be linear (R²>0.998), highly sensitive (Low LOD and LOQ concentrations), highly accurate (recovery is equivalent to 99-100%), highly precise (%RSD <2%), robust (against minor variations).

Conclusion

The HPTLC method developed is simple, precise, accurate, and robust for the concurrent estimation of Glimepiride and Linagliptin in synthetic mixtures. Employing a fractional factorial design ensured the method's dependability under various conditions, making it ideal for routine pharmaceutical quality control.