Sustainable and smart multi-analyte HPTLC determination of tolperisone HCl together with three pain killers using smartphone camera as a detector: Comparative study with benchtop densitometry - Mohamed Rizk; Emad Ramzy; Safaa Toubar; Amr M. Mahmoud; Marwa I. Helmy (Talanta Open)
The remarkable advancement in smartphone cameras has revolutionized their potential as highly accessible, portable, and manageable detectors in various analytical approaches. In this study, we developed a novel and cost-effective method for the simultaneous determination of four drugs (Tolperisone HCl (TOLP), aceclofenac(ACEC), Paracetamol (PARA), and etodolac (ETOD)). Our innovative approach combines high-performance thin-layer chromatography (HPTLC) with a smartphone's camera. Initially, chromatographic separation has been achieved utilizing HPTLC plates, employing an environmentally friendly mobile phase consisting of a mixture of ethyl acetate, methanol, and glacial acetic acid (8.5:1.5:0.25, by volume). The developed plates were visualized using a UV lamp and captured using the rear-facing camera of a smartphone fixed onto a specially designed chamber with a UV illumination source. Using ImageJ, a freely available image analysis program, the drug spot intensities were measured throughout a concentration range of 1.0–7.0 µg/band. Furthermore, the study expanded to include a comparison between the obtained results and a conventional benchtop densitometry method at a wavelength of 276.0 nm. The densitometry method exhibited a linear response within the range of 100.0 - 700.0 ng/band for TOLP, 100.0 - 600.0 ng/band for ACEC, and 150.0 - 600.0 ng/band for PARA and ETOD. The proposed HPTLC/smartphone method demonstrated its advantages of being fast, simple, reliable, and environmentally friendly, making it an outstanding platform for analyzing commercially available combined tablets. To evaluate the environmental impact and sustainability of the constructed methods and compare them with other published methods reported in the literature, the whiteness of the developed methods utilizing the RGB 12 algorithm combined with the two highly cited greenness assessment metrics, the analytical Eco-scale (AES) and the Analytical GREEnness (AGREE), were employed.