Fabricio A. Chiappini

National University of the Littoral | UNL · Department of Analytical Chemistry I

Background Across numerous investigations delved into second- and higher-order data, an undoubted finding emerges: models based on such data can effectively exploit the second-order advantage. However, whether further benefits can be achieved by modeling data of higher dimensions remains a subject of inquiry. In this regard, a prevailing question e...

The experimental data collected according to a proper statistical design constitute the input for data modeling, which represents the last step in response surface methodology (RSM). Data modeling consists in applying a set of statistical methods that enable the analyst to thoroughly study the relation between experimental factors and responses. Es...

Designing an experiment to fit a response surface model typically involves selecting a design among several candidates. There are often many competing criteria that could be considered to properly choose the final design. This chapter presents a description of the most reported designs involved in the data collection process. The basic principles a...

Chapter 2 presents an overview of the most important designs implemented for factor screening, including data analysis in pre-response surface methodology (pre-RSM). This chapter mainly focuses on practical aspects considering a group of experimental factors at different levels at the same time, with a minimum number of experiments. Then it is disc...

The present tutorial aims to review the most frequently reported criteria for the calculation of the limits of detection (LOD) and quantification (LOQ) in univariate calibration, summarizing their fundamentals, advantages, and limitations. The current criteria for estimating LOD and LOQ are based on diverse theoretical and/or empirical assumptions...

In this review, recent advances and applications using multi-way calibration protocols based on the processing of multi-dimensional chromatographic data are discussed. We first describe the various modes in which multi-way chromatographic data sets can be generated, including some important characteristics that should be taken into account for the...

Multi-way calibration based on second-order data constitutes a revolutionary milestone for analytical applications. However, most classical chemometric models assume that these data fulfil the property of low rank bilinearity, which cannot be accomplished by all instrumental methods. Indeed, various techniques are able to generate non-bilinear data...

In this investigation, the fermentation step of a standard mammalian cell‐based industrial bioprocess for the production of a therapeutic protein was studied, with particular emphasis on the evolution of cell viability. This parameter constitutes one of the critical variables for bioprocess monitoring since it can affect downstream operations and t...

The possibility of building an interference-free calibration with first-order instrumental data with multivariate curve resolution-alternating least-squares (MCR-ALS) has been a recent topic of interest. When the protocols were successful, MCR-ALS proved to be suitable for the extraction of chemically meaningful information from first-order calibra...

In the present report, an upgrade of a MATLAB graphical user interface (GUI) toolbox for implementing first-order multivariate calibration models is presented. The new freely available Multivariate Calibration 1 (MVC1_GUI) incorporates new models and features that make it a very versatile tool for data processing. In addition to the linear models,...

The use of machine learning for multivariate spectroscopic data analysis in applications related to process monitoring has become very popular, since non-linearities in the relationship be-tween signal and predicted variables are commonly observed. In this regard, the use of artificial neural networks (ANN) to develop calibration models has demonst...

A novel extraction strategy for the determination of imidacloprid, thiamethoxam and clothianidin in soy cotyledons by liquid chromatography was developed based on the implementation of an in-syringe-dispersive liquid-liquid microextraction system, optimized through successive experimental designs. First, a fractional factorial design was built to s...

In the pharmaceutical industry the need for high levels of protein expression in mammalian cells has prompted the search for new strategies, including technologies to obtain cells with improved mechanisms which enhance its transcriptional activity, folding or protein secretion. CHO cells are by far the most used host cell for therapeutic protein ex...

In the last years, regulatory agencies in biopharmaceutical industry have promoted the design and implementation of Process Analytical Technology (PAT), which aims to develop rapid and high-throughput strategies for real-time monitoring of bioprocesses key variables, in order to improve their quality control lines. In this context, spectroscopic te...

Fluorescence spectroscopy in combination with chemometrics has proved to be a powerful tool for the study of complex systems with analytical purposes. Under ideal conditions, multidimensional fluorescence data have the natural property of fulfilling the mathematical concepts of bilinearity and trilinearity, which is a key for chemometric modelling....

Fluorescence excitation-emission matrix spectroscopy coupled to multi-way analysis has proved to be a powerful tool for the study of complex systems with analytical purposes. However, scattering phenomena that are usually present in fluorescence landscapes can significantly affect the performance of the chemometric modelling or lead to misinterpret...