Solid Contact Potentiometric Sensor for The Assay of Loperamide Hydrochloride in Its Pharmaceutical Formulation and Spiked Plasma Samples

Computational chemistry induced several fast, cost-effective revolutionary solutions for chemistry laboratories. The reliability of such solutions has been questioned in several studies. The current work introduces an experimental validation for the computational selection of an ionophore during potentiometric sensor optimization. We studied the correlation of the experimental sensor performance parameters to the computational binding scores of the embedded ionophores and the drug (loperamide hydrochloride). The study included eight sensors of different PVC-membrane compositions. The PVC-membrane containing phosphotungstic acid, dioctyl phthalate, and carboxymethyl-β-cyclodextrin developed a Nernstian slope of 59.69 mV/decade and a detection limit of 2.95×10-7 mol L-1. The sensor demonstrated a fast and stable response within a linear range of 2.99×10-6-9.09×10-3 mol L-1. We examined the drug-ionophore binding using molecular modeling and docking. The docking scores (binding energy) of the cyclodextrin derivatives strongly correlate to the studied sensors' experimental performance parameters (Nernstian slope). Performance and validation parameters were computed, and the results were statistically comparable to those of the reported method. Practically, the absence of sample preparation, chromatographic separation, high-purity solvents, and costly instrumentation are incomparable advantages of the developed method relative to the reported ones.