“…Depending on the nature of the structured materials engineered to cover the PGE surface, the number of experimental variates that influence the sensors' performance during the determinations can be numerous. Faced with the need to optimize many experimental parameters, multifactorial optimizations of the developed analytical procedures have been performed either by classical methods, such as Analysis of Variance (ANOVA) or the Response Surface (RS) methodology [88,[105][106][107]129,142,143,153], or by more advanced chemometric tools, such as Artificial Neural Networks (ANNs) [121,122] or Genetic Algorithms (GAs) [121,122]. As input for the employed optimization methods, data acquired in one or two sets of developed experiments have been used, with the aim of limiting the number of determinations according to the available experimental designs of the following types: Plackett-Burman (PB) [106,107,121,122,129], central composite (CCD) [104,106,121,122,129,142,143], Box-Behnken [153], or Taguchi L25 orthogonal [88].…”