Two green analytical approaches have been developed for the analysis of antimalarial fixed dose tablets of artemether and lumefantrine for quality control. The first approach consisted of investigating the qualitative performance of a low-cost handheld near-infrared spectrometer in combination with the principal component analysis as an exploratory tool to identify trends, similarities, and differences between pharmaceutical samples, before applying the data driven soft independent modeling of class analogy (DD-SIMCA) as a one-class classifier for proper drug falsification detection with 100% of both sensitivity and specificity in the studied cases. Despite its limited spectral range and low resolution, the handheld device allowed detecting falsified drugs with no active pharmaceutical ingredient and identifying specifically a pharmaceutical tablet brand name. The second approach was the quantitative analysis based on the green and fast RP-HPLC technique using ethanol as a green organic solvent and acetic acid as a green pH modifier. The optimal separation was achieved in 7 min using a mobile phase composed of ethanol 96% and 10 mM of acetic acid pH 3.35 (63:37, v/v). The developed method was validated according to the total error approach based on an accuracy profile, was applied to the analysis of tablets, and allowed confirming falsified drugs detected by spectroscopy.
Keywords: PCA and DD-SIMCA; accuracy profile; antimalarial artemether-lumefantrine; drug falsification detection; green chromatography; handheld NIR spectrometer; non-destructive analysis; quality control.