New monoterpenoid by biotransformation of thymoquinone using Aspergillus niger.

Microbial transformation of thymoquinone (5-isopropyl-2-methyl-cyclohexa-2,5-diene-1,4-dione) (1) by suspended cell-cultures of the plant pathogenic fungus Aspergillus niger resulted in the production of three metabolites. These metabolites were identified as 5-isopropyl-2-methyloxepin-1-one (2), 3-hydroxy-5-isopropyl-2-methylcyclohexa-2,5-diene-1,4-dione (3), and 5-isopropyl-2-methylbenzene-1,4-diol (4) by different spectroscopic methods. Metabolite 2 was found to be a new compound. Compound 4 showed a potent antioxidant activity.

Supercritical Fluid Chromatography of Drugs: Parallel Factor Analysis for Column Testing in a Wide Range of Operational Conditions.

Retention mechanisms involved in supercritical fluid chromatography (SFC) are influenced 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 first time in SFC studies, Parallel Factor Analysis (PARAFAC) was employed to evaluate the chromatographic behavior of eight different 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. The 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. Thanks 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 classification. Also, the number of drugs could be efficiently reduced for columns classification as some of them exhibited a similar behavior, as shown by hierarchical clustering based on PARAFAC components.

Combination of partial least squares regression and design of experiments to model the retention of pharmaceutical compounds in supercritical fluid chromatography.

This work presents a first attempt to establish a model of the retention behaviour for pharmaceutical compounds in gradient mode SFC. For this purpose, multivariate statistics were applied on the basis of data gathered with the Design of Experiment (DoE) methodology. It permitted to build optimally the experiments needed, and served as a basis for providing relevant physicochemical interpretation of the effects observed. Data gathered over a broad experimental domain enabled the establishment of well-fit linear models of the retention of the individual compounds in presence of methanol as co-solvent. These models also allowed the appreciation of the impact of each experimental parameter and their factorial combinations. This approach was carried out with two organic modifiers (i.e. methanol and ethanol) and provided comparable results. Therefore, it demonstrates the feasibility to model retention in gradient mode SFC for individual compounds as a function of the experimental conditions. This approach also permitted to highlight the predominant effect of some parameters (e.g. gradient slope and pressure) on the retention of compounds. Because building of individual models of retention was possible, the next step considered the establishment of a global model of the retention to predict the behaviour of given compounds on the basis of, on the one side, the physicochemical descriptors of the compounds (e.g. Linear Solvation Energy Relationship (LSER) descriptors) and, on the other side, of the experimental conditions. This global model was established by means of partial least squares regression for the selected compounds, in an experimental domain defined by the Design of Experiment (DoE) methodology. Assessment of the model's predictive capabilities revealed satisfactory agreement between predicted and actual retention (i.e. R2=0.942, slope=1.004) of the assessed compounds, which is unprecedented in the field.

Synthesis and characterization of new derivatives of alginic acid and evaluation of their iron(III)-crosslinked beads as potential controlled release matrices.

CONTEXT: The excellent gelling and safety profiles of alginic acid combined, however, with drawbacks of its ionotropically crosslinked beads (i.e. their quick release of loaded drugs) prompted us to chemically modify alginic acid. OBJECTIVE: Alginic acid was chemically conjugated with four amines of varying hydrophilic-hydrophobic properties (i.e. tris(hydroxymethyl)methyl-, allyl-, benzyl- or pentyl-amines) in an attempt to enhance the drug release profiles from respective metal crosslinked beads. MATERIALS AND METHODS: Chemical conjugation procedures were performed using dicyclohexylcarbodiimide as a coupling agent and the resulting new derivatives were characterized using proton nuclear magnetic resonance ((1)H NMR), infrared (IR) spectroscopy and differential scanning calorimetry (DSC). These modified polymers were used to prepare iron (III)-crosslinked beads loaded with folic acid as model drug, which were tested in vitro to assess their folic acid release profiles. RESULTS AND DISCUSSION: Interestingly, the resulting beads accessed enteric release kinetics, with tris(hydroxymethyl)methyl-amide alginic conjugate producing most pronounced enteric profile. CONCLUSION: The results suggest the possibility of achieving controlled drug release from alginate-based beads via facile chemical modification of alginic acid.

Impact of the probe solutes set on orthogonality evaluation in reverse phase chromatographic systems.

Two-dimensional liquid chromatography (2DLC) is a very attractive technique for the characterization of complex samples due to its separation power obtained via the coupling of two separation modes exhibiting different mechanisms, i.e. orthogonality. In reverse phase, orthogonality is mainly governed by three factors: the pH of the mobile phase, the structure of the stationary phase and the nature of the organic modifier. In the present paper, we studied the impact of the nature of the probe solutes on orthogonality evaluation. A set of 63 compounds with various physicochemical properties was used to evaluate 32 reverse phase chromatographic systems (2 pH × 8 stationary phases × 2 organic modifiers). Principle component analysis revealed that the solutes could be split into three subsets according to their charge in the experimental conditions. The factors affecting orthogonality and the magnitude of their effect were shown to depend on the charge of the compounds. For positively charged (basic) compounds, the pH was the most important factor, followed by the nature of the stationary phase. For negatively charged (acidic) compounds, the nature of the stationary phase had the highest impact. For neutral compounds, only the nature of the stationary phase and, to a smaller extent, the organic modifier had an influence. The present study also showed that a reduced set of only 9 test compounds instead of whole set of the 63 could enable an appropriate orthogonality evaluation.

Comparison of different statistical approaches to evaluate the orthogonality of chromatographic separations: application to reverse phase systems.

Selectivity of phase system is of primary concern when designing a bidimensional chromatographic system and looking for the highest degree of orthogonality between the two separations. Several statistical or geometrical criteria can potentially be used to measure the degree of orthogonality. A comparison of eight candidate criteria has been carried out in this study. Analysis of variance (ANOVA) was used to evaluate the relevance of each criterion and its ability to reveal the significance of the influence of factors like pH, stationary phase, and organic modifier. Experimentally, a set of 32 chromatographic systems was evaluated by the same generic gradient with 63 probe solutes, likely to be present in biological and/or environmental samples and covering a wide range of physico-chemical properties: acidic, basic and neutral compounds with different pKa, molecular mass and hydrophobicity (logP). Each chromatographic system was defined by the nature of the stationary phase (8 different silica or grafting chemistries), the pH of the aqueous fraction of the mobile phase (2.5 or 7.0) and the nature of the organic modifier (acetonitrile or methanol). The orthogonality of the 496 couples of chromatographic systems was evaluated and ranked using the eight different approaches: the three correlation coefficients (Pearson, Spearman and Kendall), two geometric criteria characterizing the coverage of the 2D separation space, Slonecker's information similarity and two chi-square statistics of independence between normalized retention times. In fact, there were only seven distinct criteria, since we established the analytical equivalence between the rankings with the likelihood ratio statistics and Slonecker's information similarity. Kendall's correlation coefficient appeared to be the best measure of orthogonality since, according to ANOVA, it exhibited the highest sensitivity to all experimental factors. The chi-square measures, and hence Slonecker's information similarity, performed equally well provided the discretization of the separation space was carried out appropriately. Finally, from the compared study of the factors acting upon orthogonality carried out by ANOVA, it is possible to draw the conclusion that the pH of the mobile phases has the highest impact on the selectivity followed by the type of stationary phase and finally by the organic modifier.