References of "Lebrun, Pierre"
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See detailTransfer of a conventional LC method for the screening of conterfeit antimalarial medicines to UHPLC
Nistor, Iolanda ULg; Lecomte, Frédéric ULg; Mbinze Kindenge, Jérémie et al

Poster (2010, September)

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See detailOptimisation and validation of a fast HPLC method for the quantitation of sulindac and its impurities
Krier, Fabrice ULg; Brion, Michaël; Debrus, Benjamin ULg et al

Poster (2010, September)

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See detailContribution to fight against counterfeit medecines applying several analytical tools
Marini Djang'Eing'A, Roland ULg; Mbinze Kindenge, Jérémie; Montes, M. L. A. et al

Poster (2010, September)

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See detailLa contrefaçon des médicaments : outils pour lutter contre ce fléau
Marini Djang'Eing'A, Roland ULg; Mbinze Kindende, Jérémie; Lecomte, Frédéric et al

Scientific conference (2010, July 31)

The increase of counterfeit drug medicines is very remarkable all over the world and particulary in developing countries where many dramatic consequences on public health and economics have been reported ... [more ▼]

The increase of counterfeit drug medicines is very remarkable all over the world and particulary in developing countries where many dramatic consequences on public health and economics have been reported. Therefore, several tools to fight against counterfeit are presented including the simple ones such as organoleptic tools that can be applied by any one and the complex ones namely the analytical tools that belongs to the competence of laboratory. [less ▲]

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See detailBayesian hierarchical linear regression for the validation of analytical methods
Lebrun, Pierre ULg; Boulanger, Bruno ULg; Rozet, Eric ULg et al

Conference (2010, May)

Analytical quantitative methods are widely used to quantify analytes of interest, for instance in pharmaceutical formulations, linking an observed response to the concentration of one compound of the ... [more ▼]

Analytical quantitative methods are widely used to quantify analytes of interest, for instance in pharmaceutical formulations, linking an observed response to the concentration of one compound of the formulation. Current methodologies to validate these analytical methods are based on one-way ANOVA random effect model in order to estimate repeatability and intermediate precision variances. This model is then applied several times at different concentration levels over a range of concentrations where the method is intended to be used, assuming independency between the levels. In this way, the capacity of the method to be able to quantify accurately is assessed at various concentration levels, and the method is said to be fitted for purpose (or valid) at the concentration level(s) where it shows trueness and precision that are fully acceptable, i.e. within predefined acceptance limits. Problem of such approach is the amount of data required and the time needed to collect them, while small sample sizes (small number of series and of replicates per series) are often preferred and practiced by laboratories. A better use of the data could then be envisaged. In this presentation, we take into account the response-concentration relationship that exists by the use of a hierarchical linear regression model. Instead of fitting a model at each concentration level that is assessed, only one model is studied. We show how the Bayesian framework is well adapted to this task. Also, as a predictive tool, we naturally derive beta-expectation and beta-gamma content tolerance intervals by means of MCMC simulations. The Bayesian modeling can also include informative prior information whenever justified, leading to reliable decisions given the domain knowledge. [less ▲]

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See detailAcetaminophen determination in low-dose pharmaceutical syrup by NIR spectroscopy
Ziemons, Eric ULg; Mantanus, Jérôme ULg; Lebrun, Pierre ULg et al

in Journal of Pharmaceutical & Biomedical Analysis (2010), 53

The aim of the present study was first to develop a robust near infrared (NIR) calibration model able to determine the acetaminophen content of a low-dose syrup formulation (2 % (w/v)). Therefore ... [more ▼]

The aim of the present study was first to develop a robust near infrared (NIR) calibration model able to determine the acetaminophen content of a low-dose syrup formulation (2 % (w/v)). Therefore, variability sources such as production campaigns, batches, API concentration, syrup basis, operators and sample temperatures were introduced in the calibration set. A prediction model was then built using Partial Least Square (PLS) regression. First derivative followed by Standard Normal Variate (SNV) were chosen as signal pre-processing. Based on the random subsets cross validation, 4 PLS factors were selected for the prediction model. The method was then validated for an API concentration ranging from 16 to 24 mg/mL (1.6-2.4 % (w/v)) using an external validation set. The 0.26 mg/mL RMSEP suggested the global accuracy of the model. The accuracy profile obtained from the validation results, based on tolerance intervals, confirmed the adequate accuracy of the results generated by the method all over the investigated API concentration range. Finally, the NIR model was used to monitor in real time the API concentration while mixing syrups containing various amounts of API, a good agreement was found between the NIR method and the theoretical concentrations. [less ▲]

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See detailCoupling of Liquid Chromatography/Tandem Mass Spectrometry and Liquid Chromatography/Solid-Phase Extraction/NMR Techniques for the Structural Identification of Metabolites following In Vitro Biotransformation of SUR1-Selective ATP-Sensitive Potassium Channel Openers
Gillotin, F.; Chiap, Patrice ULg; Frederich, Michel ULg et al

in Drug Metabolism and Disposition : The Biological Fate of Chemicals (2010), 38(2), 232-240

SUR1-selective ATP-sensitive potassium channel openers (PCOs) have been shown to be of clinical value for the treatment of several metabolic disorders, including type I and type II diabetes, obesity and ... [more ▼]

SUR1-selective ATP-sensitive potassium channel openers (PCOs) have been shown to be of clinical value for the treatment of several metabolic disorders, including type I and type II diabetes, obesity and hyperinsulinemia. Taking into account these promising therapeutic benefits, different series of 3-alkylamino-4H-1,2,4-benzothiadiazine 1,1-dioxides structurally related to diazoxide were developed. In view of the lead optimisation process of the series, knowledge of ADMET parameters, and more particularly the metabolic fate of these compounds, is a fundamental requirement. For such a purpose, two selected promising compounds (BPDZ 73 and BPDZ 157) were incubated in the presence of phenobarbital-induced rat liver microsomes to produce expected mammal in vivo phase I metabolites. The resulting major metabolites were then analysed by both MS and NMR in order to completely elucidate their chemical structures. The two compounds were also further incubated in the presence of non-treated rats and human microsomes in order to compare the metabolic profiles. In the present study, the combined use of an exact mass LC-MS/MS platform and a LC-SPE-NMR system allowed the clarification of some unresolved structural assessments in the accurate chemical structure elucidation process of the selected PCOs drugs. These results greatly help the optimization of the lead compounds. [less ▲]

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See detailActive content determination of non-coated pharmaceutical pellets by near infrared spectroscopy: Method development, validation and reliability evaluation
Mantanus, Jérôme ULg; Ziemons, Eric ULg; Lebrun, Pierre ULg et al

in Talanta (2010), 80

A robust near infrared (NIR) method able to quantify the active content of pilot non-coated pharmaceutical pellets was developed. A protocol of calibration was followed, involving 2 operators, independent ... [more ▼]

A robust near infrared (NIR) method able to quantify the active content of pilot non-coated pharmaceutical pellets was developed. A protocol of calibration was followed, involving 2 operators, independent pilot batches of non-coated pharmaceutical pellets and two different NIR acquisition temperatures. Prediction models based on Partial Least Squares (PLS) regression were then carried out. Afterwards, the NIR method was fully validated for an active content ranging from 80 to 120% of the usual active content using new independent pilot batches to evaluate the adequacy of the method to its final purpose. Conventional criteria such as the R2, the Root Mean Square Error of Calibration (RMSEC), the Root Mean Square Error of Prediction (RMSEP) and the number of PLS factors enabled the selection of models with good predictive potential. However, such criteria sometimes fail to choose the most fitted for purpose model. Therefore, a novel approach based on accuracy profiles of the validation results was used, providing a visual representation of the actual and future performances of the models. Following this approach, the prediction model using signal pre-treatment Multiplicative Scatter Correction (MSC) was chosen as it showed the best ability to quantify accurately the active content over the 80–120% active content range. The reliability of the NIR method was tested with new pilot batches of non-coated pharmaceutical pellets containing 90 and 110% of the usual active content, with blends of validation batches and industrial batches. All those batches were also analyzed by the HPLC reference method and relative errors were calculated: the results showed low relative errors in full accordance with the results obtained during the validation of the method, indicating the reliability of the NIR method and its interchangeability with the HPLC reference method. [less ▲]

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See detailInnovative development and validation of an HPLC/DAD method for the qualitative and quantitative determination of major cannabinoids in cannabis plant material
De Backer, Benjamin ULg; Debrus, Benjamin ULg; Lebrun, Pierre ULg et al

in Journal of Chromatography. B : Analytical Technologies in the Biomedical & Life Sciences (2009), 877(32), 4115-4124

GC is commonly used for the analysis of cannabis samples, e.g. in forensic chemistry. However, as this method is based on heating of the sample, acidic forms of cannabinoids are decarboxylated into their ... [more ▼]

GC is commonly used for the analysis of cannabis samples, e.g. in forensic chemistry. However, as this method is based on heating of the sample, acidic forms of cannabinoids are decarboxylated into their neutral counterparts. Conversely, HPLC permits the determination of the original composition of plant cannabinoids by direct analysis. Several HPLC methods have been described in the literature, but most of them failed to separate efficiently all the cannabinoids or were not validated according to general guidelines. By use of an innovative methodology for modelling chromatographic responses, a simple and accurate HPLC/DAD method was developed for the quantification of major neutral and acidic cannabinoids present in cannabis plant material: Δ9-tetrahydrocannabinol (THC), THC-acid (THCA), cannabidiol (CBD), CBD-acid (CBDA), cannabigerol (CBG), CBG-acid (CBGA) and cannabinol (CBN). Δ8-tetrahydrocannabinol (∆8-THC) was determined qualitatively. Following the practice of design of experiments, predictive multilinear models were developed and used in order to find optimal chromatographic analytical conditions. The method was validated following an approach using accuracy profiles based on β-expectation tolerance intervals for the total error measurement, and assessing the measurements uncertainty. This analytical method can be used for diverse applications, e.g. plant phenotype determination, evaluation of psychoactive potency and control of material quality. [less ▲]

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See detailModèles statistiques Bayésiens et méthodologies pour calculer le Design Space (OPTIMAL-DS)
Marini Djang'Eing'A, Roland ULg; Lebrun, Pierre ULg; Hubert, Philippe ULg

Report (2009)

La compréhension des procédés technologiques et industriels dans les secteurs (bio)pharmaceutiques, biotechnologiques, agroalimentaires et environnementaux doit permettre de se conformer aux lignes de ... [more ▼]

La compréhension des procédés technologiques et industriels dans les secteurs (bio)pharmaceutiques, biotechnologiques, agroalimentaires et environnementaux doit permettre de se conformer aux lignes de conduites initiées par la FDA ou d'autres organismes de contrôles. Notamment, le document ICH Q8 introduit les notions de "Process Analytical Technology", de "Quality by Design" et de "Design Space", ayant attraits à la qualité des procédés industriels, des procédés d'analyse ainsi qu'à la qualité des produits finis. Cependant, si les lignes de conduites pour ces exigences sont expliquées, aucune méthodologie pour les atteindre n'est donnée. Or, un nombre considérable de nouvelles entités chimiques sont synthétisées par les laboratoires pharmaceutiques, biotechnologiques ou agroalimentaires. Les producteurs de matières premières et/ou d’excipients (secteur chimique) ont également besoin de disposer rapidement de méthodes analytiques de contrôle qui leur permettront de s’assurer de la qualité de leurs produits. On comprend aisément la nécessité pour ces secteurs de disposer rapidement de résultats fiables puisque les activités de recherches mais aussi des investissements, souvent importants, sont orientés ou stoppés sur base de données chiffrées, produits par les méthodes analytiques. La production de résultats fiables et la démonstration de cette fiabilité sont donc économiquement fondamentales. Ce projet vise la mise au point de stratégies et de modèles génériques de développement automatisé de nouvelles méthodes analytiques séparatives, en se basant sur la modélisation des temps de rétention, la planification expérimentale, et le concept de Design Space. L’objectif connexe est d’appliquer cette méthodologie à l’optimisation de n’importe quel procédé. Le fait de pouvoir disposer d’une méthodologie de mise au point automatique de méthodes analytiques ou de tous procédés analytiques aura un impact significatif. Cette nouvelle technologie permettra de réduire de façon drastique le temps d’optimisation des méthodes et procédés, permettant une production plus efficiente de produits (pharmaceutique, cosmétique, agro-alimentaire ou biotechnologique) répondant aux spécifications du client. [less ▲]

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See detailExpected Design Space: a Bayesian perspective based on modelling, prediction and multi-criteria decision method
Lebrun, Pierre ULg; Boulanger, Bruno ULg

Conference (2009, October)

The Design Space (DS) is defined as the set of factors settings (input conditions) that provides results at least better than pre-defined acceptance limits. The proposed methodology aims at identifying a ... [more ▼]

The Design Space (DS) is defined as the set of factors settings (input conditions) that provides results at least better than pre-defined acceptance limits. The proposed methodology aims at identifying a region in the space of factors that will likely provide satisfactory results during the future use of an analytical method or process in routine, through an optimization process. First, in a Bayesian framework, DS is derived from the joint predictive posterior distribution of the responses in a multivariate multiple regression problem using non-informative as well as informative prior distribution of the parameters. The case of DS in presence of highly correlated responses will be covered. Second, a multi-criteria decision is taken with respect to the pre-defined acceptance limits, aiming to identify the DS of any analytical methods or other processes. A strong link is made between acceptance limits and objective functions to optimize, using desirability functions and index. Examples based on high-performance liquid chromatography (HPLC) methods will be given, illustrating the applicability of the methodology with highly correlated and constrained responses. [less ▲]

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