Research Article Supercritical Fluid Chromatography of Drugs: Parallel Factor Analysis for Column Testing in a Wide Range of Operational Conditions Ramia Z. Al Bakain, 1 Yahya Al-Degs, 2 Bertyl Andri, 3 Didier Thiébaut, 4 Jérôme Vial, 4 and Isabelle Rivals 5 1 Department of Chemistry, Faculty of Science, Te University of Jordan, P.O. Box 11942, Amman, Jordan 2 Chemistry Department, Te Hashemite University, P.O. Box 150459, Zarqa, Jordan 3 Laboratory of Analytical Chemistry, CIRM, University of Liege (ULg), 15 Avenue Hippocrate (B36), 4000 Liege, Belgium 4 Laboratoire Sciences Analytiques, Bioanalytiques et Miniaturisation, ESPCI Paris, PSL Research University, 75005 Paris, France 5 ´ Equipe de Statistique Appliqu´ ee, ESPCI Paris, PSL Research University, UMRS 1158, 75005 Paris, France Correspondence should be addressed to Ramia Z. Al Bakain; ramia.bakain@yahoo.com Received 17 December 2016; Revised 11 April 2017; Accepted 23 April 2017; Published 11 June 2017 Academic Editor: Hassan Y. Aboul Enein Copyright © 2017 Ramia Z. Al Bakain et al. Tis is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Retention mechanisms involved in supercritical fuid chromatography (SFC) are infuenced by interdependent parameters (temperature, pressure, chemistry of the mobile phase, and nature of the stationary phase), a complexity which makes the selection of a proper stationary phase for a given separation a challenging step. For the frst time in SFC studies, Parallel Factor Analysis (PARAFAC) was employed to evaluate the chromatographic behavior of eight diferent stationary phases in a wide range of chromatographic conditions (temperature, pressure, and gradient elution composition). Design of Experiment was used to optimize experiments involving 14 pharmaceutical compounds present in biological and/or environmental samples and with dissimilar physicochemical properties. Te results showed the superiority of PARAFAC for the analysis of the three-way (column × drug × condition) data array over unfolding the multiway array to matrices and performing several classical principal component analyses. Tanks to the PARAFAC components, similarity in columns’ function, chromatographic trend of drugs, and correlation between separation conditions could be simply depicted: columns were grouped according to their H-bonding forces, while gradient composition was dominating for condition classifcation. Also, the number of drugs could be efciently reduced for columns classifcation as some of them exhibited a similar behavior, as shown by hierarchical clustering based on PARAFAC components. 1. Introduction Supercritical fuid chromatography (SFC) becomes an appre- ciated separation technique in science due to its capacity to provide fast, robust, and efcient analysis [1]. In addition, this technique is considered as green due to its low consumption of organic solvents [2] that are toxic, expensive, and harmful to environment [3]. Terefore, SFC recently showed great success in many felds, such as the separation and detection of PAHs and petroleum related compounds [4–7], oligomers and polymers [8], food residues [9], unpermitted addition and misuse of dyes in diferent foodstufs [10], cosmetics and body care products [11], pharmaceutical separation [12], drug development and discovery [3, 13–15], impurity profling [16– 18], and drug testing [1, 19, 20]. During the last decade, many improvements were brought to SFC instrumentation to make this technique compatible with the majority of columns, including columns packed with sub-2 m particles [21, 22] since a key point for a separation method in SFC is to choose the proper stationary phase [3]. In practice, method development is ofen based on trial and error, which consumes efort, time, and materials, and limits the age of column due to the numerous runs required. Tus, it would be preferable to understand the Hindawi Journal of Analytical Methods in Chemistry Volume 2017, Article ID 5340601, 13 pages https://doi.org/10.1155/2017/5340601