## 1 Introduction  
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 electrophysiological properties ranging from bioanalytical to biological and food characterization [2; 3]. However, EIS can only analyse properties of bulk material as a whole, unlike other spectroscopy methods, by which individual chemical species can be determined. Thus, a number of factors, such as the measurement method, the experimental setup (including electrode array, test cell, and environmental conditions) and analytical development of resulting models, can influence the quality of measured data and information obtained. 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. However, there are still challenges to overcome, in particular, accounting for the non-stationary nature of electrochemical cells. [PERSON] [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.  
For instance, targeted drug delivery is a typical example of a dynamic, multidimensional process where the use of EIS measurements can have important implications for real-time analysis of drug dispersion dynamics towards improving the effectiveness of medical treatments. [PERSON] et al. [5] demonstrated that Electrical Impedance Tomography can be used for imaging changes in concentration of propranolol hydrochloride, dissolving ad hoc tablets in salty liquid media using a test phantom fitted with five 16-electrode measurement planes. On the other hand, different tissues exhibit different electrical impedance properties as a function of frequency ([PERSON] et al. [6; 7; 8]), and thus EIS can be used to distinguish different tissues. However, drug delivery alters the electrical properties of the tissue [9], and thus it is necessary to develop methods that can lead to the real-time identification of different components. Therefore, 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 also provide a mathematical score of the feasibility of the model so as to represent the electrochemical cell processes. Here, 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.