Faculty of SciencesSchool of Pharmaceutical Sciences

Pharmaceutical Analytical Chemistry

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The research of this group is focused on the development and the use of methods for mathematical and statistical analysis of data produced from chemical instrumentation. The use of chemometric tools for developing analytical methods, determining optimised or robust conditions as well as for treating data with pattern recognition techniques are applied in many projects involving the Laboratory of Pharmaceutical Analytical Chemistry (LCAP), the School of Pharmaceutical Sciences or numerous collaborations.
As defined by Massart (1), chemometrics is a chemical discipline that uses mathematics, statistics and formal logic:

• to design or select optimal experimental procedures
• to provide maximum relevant chemical information by analyzing chemical data; and
• to obtain knowledge about chemical systems.

1) Massart, D.L., et al.. (1997) Data Handling in Science and Technology 20A: Handbook of Chemometrics and Qualimetrics Part A.

Design of experiments (DOE)
DOE is a powerful tool to quantify the effect of one or more variables on a set of measured responses. It provides a methodological framework for changing operating parameters simultaneously. To better develop, optimise and validate analytical methodologies, the use of multivariate approach is of utmost interest. DOE involve the smallest possible number of useful experiments which provide maximum information. The relevant results obtained in pharmaceutical analysis in DOE compared to univariate approach come from their ability to detect and quantify variable interactions and therefore considerably increase the system knowledge. Furthermore, DOE is very useful for the selection of relevant operating parameters for robustness evaluation during validation.

Method validation
Validation of the method established that performance characteristics (Figures of merits, quality parameters) were adequate for the intended use. It entailed the evaluation of a number of parameters such as selectivity, concentration-detector response relationship, trueness, precision (repeatability and intermediate fidelity), accuracy, sensitivity, determination limits and robustness. The analytical method are fully validated following the approach proposed by the "Société française des Sciences et Techniques Pharmaceutiques" (SFSTP) which includes regular guidelines recommendations.

Data mining
Hyphenated analytical platforms such as GC-MS, CE-MS or LC-MS are now commonly used in various pharmaceutical fields such as bioanalysis or metabolomic studies. The large increase of experimental data, as a direct result of the number and sophistication of the analytical instrumentation, drives the necessity to develop new data treatment techniques and general strategies of extracting scientific knowledge. PCA, HCA, OSC or PLS are examples of multivariate analysis methods to obtain an efficient interpretation of the generated data.

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