Abstract
The physicochemical characterization of pharmaceutical materials is essential for drug discovery, development and evaluation, and for understanding and predicting their interaction with physiological systems. Amongst many measurement techniques for spectroscopic characterization of pharmaceutical materials, Electrical Impedance Spectroscopy (EIS) is powerful as it can be used to model the electrical properties of pure substances and compounds in correlation with specific chemical composition. In particular, the accurate measurement of specific properties of drugs is important for evaluating physiological interaction. The electrochemical modelling of compounds is usually carried out using spectral impedance data over a wide frequency range, to fit a predetermined model of an equivalent electrochemical cell. This paper presents experimental results by EIS analysis of four drug formulations (trimethoprim/sulfamethoxazole C14H18N4O3-C10H11N3O3, ambroxol C13H18Br2N2O.HCl, metamizole sodium C13H16N3NaO4S, and ranitidine C13H22N4O3S.HCl). A wide frequency range from 20 Hz to 30 MHz is used to evaluate system identification techniques using EIS data and to obtain process models. The results suggest that arrays of linear R-C models derived using system identification techniques in the frequency domain can be used to identify different compounds.
Highlights
In pharmaceutical research, analytical science plays an essential role in the physicochemical characterization of properties of drug materials, intermediates, drug products, drug formulation, impurity, degradation products, and biological samples containing the drugs and their metabolites [1].Amongst many analytical spectroscopic measurement techniques, Electrical Impedance Spectroscopy (EIS) is simple and cost-effective for elucidating a wide range of electrophysical properties ranging from bioanalytical to biological and food characterization [2,3]
The importance of using EIS information for electrochemical cell characterization drives the continuous report of novel mathematical methods as well as the introduction of experimental and commercial software solutions that allow for the tailoring of specific models to particular electrochemical cell arrays, based on frequency-domain experimental data
The authors focus on developing the procedure based on frequency-domain system identification methods to analyse the frequency response of the electrochemical cell that can be recalculated from frequency-domain response data, required for reproducible and precise identification and quantification of drug analysis as they are essential in discovery, development, and evaluation of drugs
Summary
Analytical science plays an essential role in the physicochemical characterization of properties of drug materials, intermediates, drug products, drug formulation, impurity, degradation products, and biological samples containing the drugs and their metabolites [1]. Amongst many analytical spectroscopic measurement techniques, Electrical Impedance Spectroscopy (EIS) is simple and cost-effective for elucidating a wide range of electrophysical properties ranging from bioanalytical to biological and food characterization [2,3]. Ragoisha [4] addresses some of these challenges, and, amongst various aspects, discusses the importance of considering multidimensional, non-stationary EIS information towards a universal electrochemical response analyser that bridges the gap between DC, single-frequency AC and EIS methods. There are incentives to further develop electrical impedance analysis methods that can provide a mathematical model, suitable for determining the electrical properties of dynamic systems and can provide a mathematical score of the feasibility of the model so as to represent the electrochemical cell processes. The authors focus on developing the procedure based on frequency-domain system identification methods to analyse the frequency response of the electrochemical cell that can be recalculated from frequency-domain response data, required for reproducible and precise identification and quantification of drug analysis as they are essential in discovery, development, and evaluation of drugs
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