Chromatographic Applications in the Multi-Way Calibration Field

Abstract

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 selection of an adequate data processing model. We then discuss the different manners in which the collected instrumental data can be arranged, and the most usually applied models and algorithms for the decomposition of the data arrays. The latter activity leads to the estimation of surrogate variables (scores), useful for analyte quantitation in the presence of uncalibrated interferences, achieving the second-order advantage. Recent experimental reports based on multi-way liquid and gas chromatographic data are then reviewed. Finally, analytical figures of merit that should always accompany quantitative calibration reports are described.

Two new methods for the estimation and interpretation of the range of feasible profiles in multivariate curve resolution and their implications to analytical chemistry

“…A convenient parameter measuring this uncertainty is a root mean square error due to rotational ambiguity (RMSE RA ), which has been proposed to be given by the following range of values: 8)where δ RA is the range of feasible concentration values for the analyte, equal to the difference between the maximum and minimum areas of the analyte concentration profile, after conversion to concentration units through:…”

“…Unfortunately, the consideration of rotational ambiguity is almost absent in the analytical literature, and only a few publications include the estimation of the uncertainty brought about by the phenomenon in the estimated analyte concentrations. 8 In view of the above, it is imperative to bridge the gap between the body of theoretical work on rotational ambiguity in bilinear decomposition on one side, and experimental analytical protocols based on second-order multivariate calibration on the other. Especially useful in this regard are two recently introduced models: N-BANDS 9 ("N" stands for noise) and sensor-wise N-BANDS (SW-N-BANDS).…”

“…Multi‐component systems present a significant challenge for their deep understanding, although important advances have recently taken place, particularly in what concerns the implications for chemical analysis. Unfortunately, the consideration of rotational ambiguity is almost absent in the analytical literature, and only a few publications include the estimation of the uncertainty brought about by the phenomenon in the estimated analyte concentrations 8 …”

Development and Optimization of a New UPLC-UV/MS Method through DoE and MLR for Detecting Substandard Drug Products to Treat Tuberculosis

“…This method should be developed and optimized using the principles of quality by design (QbD), replacing old variables one at a time (OVAT). This approach makes it possible to study interactive effects between variables through the use of the design of experiments (DoE) and multiple linear regression (MLR) [ 23 , 24 , 25 ]. DoE helps to establish a cause-and-effect relationship between the factors and responses, thus reducing the time, effort, and resources required.…”