References of "Mantanus, Jérôme"
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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 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 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 detailBuilding the quality into pellet manufacturing environment - feasibility study and validation of an in-line quantitative near infrared (NIR) method
Mantanus, Jérôme ULg; Ziemons, Eric ULg; Rozet, Eric ULg et al

in Talanta (2010), 83

The present study focuses on the implementation of an in-line quantitative near infrared (NIR) spectroscopic method for determining the active content of pharmaceutical pellets. The first aim was to non ... [more ▼]

The present study focuses on the implementation of an in-line quantitative near infrared (NIR) spectroscopic method for determining the active content of pharmaceutical pellets. The first aim was to non-invasively interface a dispersive NIR spectrometer with four realistic particle streams existing in the pellets manufacturing environment. Regardless of the particle stream characteristics investigated, NIR together with principal component analysis (PCA) was able to classify the samples according to their active content. Further, one of these particle stream interfaces was non-invasively investigated with a FT-NIR spectrometer. A predictive model based on Partial Least Squares (PLS) regression was able to determine the active content of pharmaceutical pellets. The NIR method was finally validated with an external validation set for an API concentration range from 80 to 120 % of the targeted active content. The prediction error of 0.9 % (root mean standard error of prediction, RMSEP) was low, indicating the accuracy of the NIR method. The accuracy profile on the validation results, an innovative approach based on tolerance intervals, demonstrated the actual and future performance of the in-line NIR method. Accordingly, the present approach paves the way for real-time release-based quality system. [less ▲]

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See detailProduction line real time near infrared (NIR) monitoring
Mantanus, Jérôme ULg; Ziemons, Eric ULg; Streel, Bruno et al

Conference (2009, September)

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See detailMoisture content determination of pharmaceutical pellets by near infrared spectroscopy: method development and validation.
Mantanus, Jérôme ULg; Ziemons, Eric ULg; Lebrun, Pierre ULg et al

in Analytica Chimica Acta (2009), 642(1-2), 186-92

The aim of the present study was to develop and validate a near infrared method able to accurately determine a moisture content of pharmaceutical pellets ranging from 1% to 8% in order to check their ... [more ▼]

The aim of the present study was to develop and validate a near infrared method able to accurately determine a moisture content of pharmaceutical pellets ranging from 1% to 8% in order to check their moisture content conformity. A calibration and validation set were designed for the conception and evaluation of the method adequacy. An experimental protocol was then followed, involving two operators, independent production campaign batches and different temperatures for data acquisition. On the basis of this protocol, prediction models based on partial least squares (PLS) regression were then carried out. Conventional criteria such as the R(2), the root mean square errors of calibration and prediction (RMSEC and RMSEP) as well as the number of PLS factors enabled the selection of three preliminary models. However, such criteria did not clearly demonstrate the model's ability to give accurate predictions over the whole analyzed water content range. Consequently, a novel approach based on accuracy profiles which allow the selection of the most fitted model for purpose was used. According to this novel approach, the model using multiplicative scatter correction (MSC) pre-treatment was obviously the most suitable. Indeed, the resulting accuracy profile clearly showed that this model was able to determine moisture content over the range of 1-8% with a very acceptable accuracy. The present study confirmed that NIR spectroscopy could be used in the PAT concept as a non-invasive, non-destructive and fast technique for moisture content determination in pharmaceutical pellets. In addition, facing the limit of the classical and commonly used criteria, the use of accuracy profiles proved to be useful as a powerful decision tool to demonstrate the suitability of the proposed analytical method. [less ▲]

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