M. Sagrario Sánchez

University of Burgos | UBU · Departamento de Matemáticas y Computación

In this work, strategies within Analytical Quality by Design (AQbD) with tools of the Process Analytical Technology (PAT) were used in the development of a head space-solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) procedure for the multiresidue analysis of four phthalic acid esters, benzyl butyl phthalate, bis(2-et...

Analytical Quality by Design (AQbD) is the adaptation of Quality by Design (QbD) when it is applied to the development of an analytical method. The main idea is to develop the analytical method in such a way that the desired quality of the Critical Quality Attributes (CQAs), stated via the analytical target profile (ATP), is maintained while allowi...

The paper presents a new methodology within the framework of the so-called compliant class-models, PLS2-CM, designed with the purpose of improving the performance of class-modelling in a setting with more than two classes. The improvement in the class-models is achieved through the use of multi-response PLS models with the classes encoded via Error...

The paper presents a new proposal for a single overall measure, the diagonal modified confusion entropy (DMCEN), to assess the performance of class-models jointly computed for several classes, a versatile index regarding sensitivity and specificity, and that supports class weighting. The characteristics of the proposed figure of merit are illustrat...

A chromatographic method with the Analytical Quality by Design (AQbD) methodology is developed for the simultaneous determination by HPLC-FLD of ten PAHs (naphthalene, phenanthrene, anthracene, fluoranthene, pyrene, chrysene, benzo[a]anthracene, perylene, benzo[b]fluoranthene, and benzo[a]pyrene), widely spread in the environment. The construction...

In the context of binary class-modelling techniques, the paper presents the computation in the input space of linear boundaries of a class-model constructed with given values of sensitivity and specificity. This is done by inversion of a decision threshold, set with these values of sensitivity and specificity, in the probabilistic class-models comp...

Inside the framework of Analytical Quality by Design, a model-based approach has been developed and used to identify operating conditions (control method parameters) related to the composition and flow rate of the mobile phase for a liquid chromatographic determination with preset quality characteristics. The approach starts by defining these desir...

The paper shows a procedure for selecting the control method parameters (factors) to obtain a preset ‘analytical target profile’ when a liquid chromatographic technique is going to be carried out for the simultaneous determination of five bisphenols (bisphenol-A, bisphenol-S, bisphenol-F, bisphenol-Z and bisphenol-AF), some of them regulated by the...

The paper contains a discussion about the null spaces associated to linear prediction models for the particular case of Partial Least Squares regression models. The discussion separately considers the two existing null spaces: the one in the input space related to the projection onto the latent space and the null space, coming from the projection s...

The growing demand for controls of foodstuffs, personal care products, medicines and the environment is unquestionable, as well as a better understanding of the toxicity of chemical products. This causes a growing need to propose methods of analysis for the unequivocal identification and quantification of analytes in complex samples. Several offici...

In general, the calibration of an instrument involves a set of calibration standards with known concentration to measure the response of the instrument for each standard, and to fit a model to establish the relationship between the instrumental response and the concentration of the analyte, regression model that is used to transform the measurement...

In the context of the paradigms founding the Quality by Design and Process Analytical Technology initiatives, the work herein presents a computational approach to support the decision-making process, in particular, about the feasibility of a product defined for some a priori given quality characteristics. The approach is based on the computation of...

This paper analyzes a discrete-time Geoa/Geob/1 queuing system with batch arrivals of fixed size a , and batch services of fixed size b. Both arrivals and services occur randomly following a geometric distribution. The steady-state queue length distribution is obtained as the solution of a system of difference equations. Necessary and sufficient co...

Several analytical procedures depend on multivariate calibration models, such as partial least squares (PLS) models fitted with nearinfrared (NIR) and midinfrared (MIR) spectroscopy signals. Most of these models are related to products that require the control of maximum (or minimum) legally defined limits so that assessing the risks of false nonco...

An algorithmic implementation is presented to deal with several responses in mixtures problems, without theoretical limits on the number of responses or on the factors to be blended. Also, constrained and unconstrained domains are handled, as well as domains with both mixtures and discrete variables. Besides, an alternative way of interpreting the...

An antioxidant gluten-free cracker snack was developed through the inclusion of carob by-products (germ and seed peel). The levels of formulation of these two novel ingredients were optimized through their effect on nutritional, physicochemical, sensory and antioxidant parameters of the final product. The results showed that both ingredients affect...

Numerous research activities generate data that are organized as a three-way tensor, which can be described with PARAFAC. This chapter starts by briefly describing the PARAFAC model and the properties that support its practical utility. Besides, two alternative models are presented, PARAFAC2 and Tucker3, which are useful when the data are inconsist...

ABSTRACT An antioxidant gluten-free cracker snack was developed through the inclusion of carob by-products (germ and seed peel). The levels of formulation of these two novel ingredients were optimized through their effect on nutritional, physicochemical, sensory and antioxidant parameters of the final product. The results showed that both ingredien...

An 'ad-hoc' experimental design to handle the robustness study for the simultaneous determination of dichlobenil and its main metabolite (2,6-dichlorobenzamide) in onions by programmed temperature vaporization-gas chromatography-mass spectrometry (PTV-GC-MS) is performed. Eighteen experimental factors were considered; 7 related with the extraction...

The paper shows some tools (its interpretation and usefulness) to optimize a derivatization reaction and to more easily interpret and visualize the effect that some experimental factors exert on several analytical responses of interest when these responses are in conflict. The entire proposed procedure has been applied in the optimization of equili...

The problem of blocking experimental designs is addressed, for both factorial type designs and response surface designs (i.e. for discrete and continuous experimental domains). The focus is to arrange block as orthogonally as possible. To measure the uncorrelatedness between the block and the coefficient estimates, we use directly the corresponding...

Experimental designs for a given task should be selected on the base of the problem being solved and of some criteria that measure their quality. There are several such criteria because there are several aspects to be taken into account when making a choice. The most used criteria are probably the so-called alphabetical optimality criteria (for exa...

The present work proposes an analytical procedure to determine sulfathiazole in milk by using molecular fluorescence spectroscopy. For this sulfonamide the European Union in Regulation 37/2010 has established a maximum residue limit in milk of 100 μg kg(-1). The study includes the effect of six factors on the recovery of sulfathiazole. The factors...

The paper shows tools to visualize and more easily interpret the effect that some experimental factors may exert on analytical responses of interest when optimization of several responses is needed. It is based on an adaptation of the parallel coordinate plot, a tool for graphical representation of points in multidimensional spaces that, theoretica...

In class-modelling problems, which are again becoming increasingly important, there are two parameters to value the quality of the class-model built for a category, namely sensitivity and specificity. Using them as criteria, in this paper, two different approaches to class-modelling problems are presented, approaches that differ from other usual me...

Uncertainty is inherent in all experimental determinations. Nevertheless, these measurements are used to make decisions including the performance of the own measurement systems. The link between the decision and the true implicit system that generates the data (measurement system, production process, category of samples, etc.) is a representation o...

The work presents two approaches for the construction of empirical class-models for a given category C. The attention is centred on the information provided by the sensitivity and specificity, the two usual parameters employed to qualify a class-model. In fact, not only a class-model is built for C but a set of class-models which differ in their se...

Every day millions of analytical determinations are made in thousands of laboratories all around the world. These measurements are necessary for evaluating merchandise in the commercial interchanges, supporting health care, nourishing security, quality control of water and the environment, characterization of raw materials and manufactured products...

From a statistical point of view, the regression analysis is an area of ongoing research, so an ever-growing collection of techniques makes it difficult the selection of the most adequate one for a given problem. From a chemical or biochemical point of view, instrumental calibration is an essential stage in many procedures of measurement for the q...

Due to the second-order advantage, calibration models based on parallel factor analysis (PARAFAC) decomposition of three-way data are becoming important in routine analysis. This work studies the possibility of fitting PARAFAC models with excitation-emission fluorescence data for the determination of ciprofloxacin in human urine. The finally chosen...

An experimental strategy, based on a D-optimal design, to systematically study the influence of some metaparameters that affect the behaviour of a class-modelling method is described.The class-modelling method computes class-models by using neural networks trained by an evolutionary algorithm. The key is that the neural networks are trained to find...

The statistical analysis based on the distribution of the ranks (order of the experimental values) has had an increasing development. Outcomes associated with an experiment may be numerical in nature, such as quantity in an analytical sample. The types of measurements are usually called “measurement scales” and are, from the weakest to the stronges...

This work presents a methodology to analyse the behaviour of an analytical procedure, above all when optimization of the procedure is needed. The methodology starts by the design of an experiment suitable to fit response surfaces to some analytical responses of interest in the problem being studied. Then, a pareto-optimal front is estimated that ac...

This paper deals with the selection of experimental conditions and how the signals obtained in these conditions influence the fitted Partial Least Squares calibration model. The multivariate signals come from a flow analysis system with amperometric detection when determining sulfadiazine, sulfamerazine and sulfamethazine in milk.The solution (carr...

An alternative to the use of desirability function for optimising multiple responses is proposed. Instead of defining a compromise among responses to find a region of experimental conditions by one-dimensional optimisation of the so-called desirability function, the proposal is to directly study the problem in its real nature as a vectorial optimis...

Sensitivity and specificity are two widely accepted parameters to qualify a model when working in class-modelling problems. Further, the trade-off between these two parameters is well known. In the present work the problem of building models taking into account both sensitivity and specificity is posed in its real nature, as a multi-objective optim...

The process control of the elaboration of wines as well as the final quality of the product is at present incorporating non-destructive methods for the analysis so that they can be systematically applied anywhere in the process. MIR spectroscopy is an easy, fast and reproducible technique that allows obtaining several parameters from the same spect...

The goal of present work is to analyse the effect of having non-informative variables (NIV) in a data set when applying cluster analysis and to propose a method computationally capable of detecting and removing these variables. The method proposed is based on the use of a genetic algorithm to select those variables important to make the presence of...

Analytical techniques based on soft multivariate calibrations (as those which provide first and second order analytical signals necessarily are) remain outside the field of application of the ISO norms related to capability of detection. In this work, a complete solution for the problem of applying ISO norm 11843 to soft calibration (for instance,...

This work analyses some partial least squares regression (PLSR) problems that can conceptually be improved. The result is the incorporation, in the classical PLSR algorithm, of a weighting stage giving rise to partial least squares with weighted loadings (WL-PLS) algorithm. Then some studies with real data have been done to evaluate its performance...

The present work is oriented to the description and evaluation as a nonparametric hypothesis test of Genetic Inside Neural Network (GINN) based on an artificial neural network trained with a stochastic process. In this paper, the theoretical framework is detailed, together with the convergence properties, and the way it is implemented. Finally, som...

A new methodology is proposed based on a neural network to determine the detection capability of an analytical procedure, in complex matrices, with the evaluation of the probability of false detection, α, and false nondetection, β, according to the ISO norms. This methodology is designed for first or greater order signals for which there is current...

Colour is one of the most important characteristics of a wine. To measure it, the International Organisation for Wine (OIV) proposes the use of the so-called CieLab parameters: a∗, red/green chromaticity; b∗, yellow/blue chromaticity; and L∗, clarity. However, the need for including the psychophysical parameters: C∗, chroma, H∗, tone, and S∗, satur...

In this paper, as an alternative to multivariate regression methods, quality control tasks are posed as a decision problem: a sample is acceptable (this means that it follows its way to market) or not (then, it should be carefully examined according to laboratory procedures). The parameter to control is the content of water in samples of ampicillin...

The relationship between absorption in the near-infrared (NIR) spectral region and the target analytical parameter is frequently of the non-linear type. The origin of the non-linearity can be widely varied and difficult to identify. In some cases, the relationship between absorption and the analytical parameter of interest is intrinsically non-line...

This study demonstrates that it is possible to characterise the vinegars obtained from wines with Certified Denomination of Origin Rioja (66 vinegars) and Jerez (18 vinegars) according to their chemical composition. SIMCA was used, along with cross-validation, as a modelling multivariate technique. In order to demonstrate that no better sensitivity...

Partial least squares (PLS), polynomial partial least squares (polynomial-PLS), locally weighted regression (LWR) and genetic inside neural network (GINN) algorithms were used to develop models for predicting motor octane number (MON) from non-leaded and catalytically reformed gasolines. Medium infrared (mid-infrared) spectra were obtained on liqui...

Multivariate chemometric techniques such as SIMCA (Soft Independent Modelling Class Analogy) and GINN (Genetic Inside Neural Network) were used to construct sensitive and specific models for rose and 'claretes' wines of the Certified Denomination of Origin Rioja, on the basis of data obtained from an easy espectrophotometric analysis (Cie-Lab param...

A genetic algorithm (steady state evolutionary algorithm without duplication) to train neural networks for classification problems is investigated. The algorithm is based on direct optimization of frequencies of both misclassifications and number of correct classifications with special attention to the parameters known as sensibility and specificit...

In our paper [1], the modeling capabilities of multi-layered feed-forward (MLF) and radial base function (RBF) networks were investigated on simulated data and well described experimental data from chemical industry [4]. Since both networks are based on a different concept (that is, RBF in contrast to MLF shows more local modeling behaviour) both m...

Neural networks have been used in multiple applications, but as a kind of black box for dealing with problems where there is no a priori information about the data. This means that the model is constructed based solely upon information obtained from the data themselves. This seems to be a good property but makes it difficult to validate the models...

A linear relationship between certain physicochemical measurements and sensory evaluation of the colour of young red Rioja wines has been constructed. Among these physicochemical measurements, different variable selection procedures based on genetic algorithms and decision trees, showed that it suffices to take into account the CieLab parameters. W...

The efficiency of multi-layered feed-forward networks (MLF) on classification is evaluated by applying them to simulated data. The classes are normal multivariate with three different structures for the matrix of covariance. For each of them a complete factorial design, 23, was performed, with a replicated central point in order to study the effect...

The modelling of the colour of young red wine of Denomination of Origin Rioja has become an issue of great practical importance. A UNEQ multivariate classification model for two categories (accepted wines and rejected wines), a partial least squares (PLS) model for the prediction of the value of the colour grading assigned by wine tasters and a mul...

In this paper, two popular types of neural network models (radial base function (RBF) and multi-layered feed-forward (MLF) networks) trained by the generalized delta rule, are tested on their robustness to random errors in input space. A method is proposed to estimate the sensitivity of network outputs to the amplitude of random errors in the input...