References of "Lebrun, Pierre"
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See detailCOMBINATION OF INDEPENDENT COMPONENT ANALYSIS, DESIGN OF EXPERIMENTS AND DESIGN SPACE FOR A NOVEL METHODOLOGY TO DEVELOP CHROMATOGRAPHIC METHODS
Rozet, Eric ULg; Debrus, Benjamin ULg; Lebrun, Pierre ULg et al

Poster (2012, February)

As defined by ICH [1] and FDA, Quality by Design (QbD) stands for “a systematic approach to development that begins with predefined objectives and emphasizes product and process understanding and process ... [more ▼]

As defined by ICH [1] and FDA, Quality by Design (QbD) stands for “a systematic approach to development that begins with predefined objectives and emphasizes product and process understanding and process control, based on sound science and quality risk management”. A risk–based QbD–compliant approach is proposed for the robust development of analytical methods. This methodology based on Design of Experiments (DoE) to study the experimental domain models the retention times at the beginning, the apex and the end of each peak corresponding to the compounds of a mixture and uses the separation criterion (S) rather than the resolution (RS) as a Critical Quality Attribute. Stepwise multiple linear regressions are used to create the models. The estimated error is propagated from the modelled responses to the separation criterion (S) using Monte Carlo simulations in order to estimate the predictive distribution of the separation criterion (S) over the whole experimental domain. This allows finding ranges of operating conditions that will guarantee a satisfactory quality of the method in its future use. These ranges define the Design Space (DS) of the method. In chromatographic terms, the chromatograms processed at operating conditions within the DS will assuredly show high quality, with well separated peaks and short run time, for instance. This Design Space can thus be defined as the subspace, necessarily encompassed in the experimental domain (i.e. the knowledge space), within which the probability for the criterion to be higher than an advisedly selected threshold is higher than a minimum quality level. Precisely, the DS is defined as “the multidimensional combination and interaction of input variables (e.g., material attributes) and process parameters that have been demonstrated to provide assurance of quality” [1]. Therefore, this DS defines a region of operating conditions that provide prediction of assurance of quality rather than only quality as obtained with traditional mean response surface optimisation strategies. For instance, in the liquid chromatography there is a great difference in e.g. predicting a resolution (RS) higher than 1.5 vs. predicting that the probability for RS to be higher than 1.5 (i.e. P(RS> 1.5)) is high. The presentation of this global methodology will be illustrated for the robust optimisation and DS definition of several liquid chromatographic methods dedicated to the separation of different mixtures: pharmaceutical formulations, API and impurities/degradation products, plant extracts, separation of enantiomers, … References [1] International Conference on Harmonisation (ICH) of Technical Requirements for Registration of Pharmaceuticals for Human Use, Topic Q8(R2): Pharmaceutical development, Geneva, 2009. [less ▲]

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See detailAPPLICATION OF DESIGN OF EXPERIMENTS AND DESIGN SPACE METHODOLOGY FOR THE HPLC-UV SEPARATION OPTIMIZATION OF APORPHINE ALKALOIDS FROM LEAVES OF Spirospermum penduliflorum THOUARS
Rafamantanana, Mamy; Debrus, Benjamin ULg; Raoelison, Guy et al

in Journal of Pharmaceutical & Biomedical Analysis (2012), 62

Spirospermum penduliflorum Thouars (Menispermaceae) is an endemic species of Madagascar traditionally used as vasorelaxant. Recently, two aporphine alkaloids known to possess antihypertensive activity ... [more ▼]

Spirospermum penduliflorum Thouars (Menispermaceae) is an endemic species of Madagascar traditionally used as vasorelaxant. Recently, two aporphine alkaloids known to possess antihypertensive activity (dicentrine and neolitsine) were isolated and identified from the leaves of this plant. In the present study, a HPLC-UV method allowing the separation of all alkaloids and the quantification of dicentrine in the alkaloidic extract of leaves was developed using design of experiments and design space methodology. Three common chromatographic parameters (i.e. the mobile phase pH, the initial proportion of methanol and the gradient slope) were selected to construct a full factorial design of 36 experimental conditions. The times at the beginning, the apex (i.e. the retention time) and the end of each peak were recorded and modelled by multiple linear equations. The corresponding residuals were normally distributed which confirmed that the models can be used for the prediction of the retention times and to optimize the separation. The optimal separation was predicted at pH 3, with a gradient starting at 32% of methanol and a gradient slope of 0.42%/min. Good agreement was obtained between predicted and experimental chromatograms. The method was also validated using total error concept. Using the accuracy profile approach, validation results gave a LOD and LOQ for dicentrine of 3 µg/ml and 10 µg/ml, respectively. A relative standard deviation for intermediate precision lower than 10% was obtained. This method was found to provide accurate results in the concentration range of 10 µg/ml to 75 µg/ml of dicentrine and is suitable for routine analysis. [less ▲]

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See detailDesign space approach in the optimization of the spray-drying process
Lebrun, Pierre ULg; Krier, Fabrice ULg; Mantanus, Jérôme ULg et al

in European Journal of Pharmaceutics & Biopharmaceutics (2012), 80(1), 226-234

From a quality by design perspective, the aim of the present study was to demonstrate the applicability of a Bayesian statistical methodology to identify the design space (DS) of a spray-drying process ... [more ▼]

From a quality by design perspective, the aim of the present study was to demonstrate the applicability of a Bayesian statistical methodology to identify the design space (DS) of a spray-drying process. Following the ICH Q8 guideline, the DS is defined as the “multidimensional combination and interaction of input variables (e.g., materials attributes) and process parameters that have been demonstrated to provide assurance of quality”. Thus, a predictive risk-based approach was set up in order to account for the uncertainties and correlations found in the process and in the derived critical quality attributes such as the yield, the moisture content, the inhalable fraction of powder, the compressibility index and the Hausner ratio. This allowed quantifying the guarantees and the risks to observe whether the process shall run according to specifications. These specifications describe satisfactory quality outputs and were defined a priori given safety, efficiency and economical reasons. Within the identified DS, validation of the optimal condition was effectuated. The optimized process was shown to perform as expected, providing a product for which the quality is built in by the design and controlled set-up of the equipment, regarding identified critical process parameters: the inlet temperature, the feed rate and the spray flow rate. [less ▲]

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See detailDesign Space ou Espace de Conception
Boulanger, B.; Lebrun, Pierre ULg; Rozet, Eric ULg et al

Scientific conference (2011, November 29)

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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 (2011)

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 detailNew Methodology for the Development of Chromatographic Methods
Rozet, Eric ULg; Debrus, Benjamin ULg; Lebrun, Pierre ULg et al

Conference (2011, September 08)

As defined by ICH [1] and FDA, Quality by Design (QbD) stands for “a systematic approach to development that begins with predefined objectives and emphasizes product and process understanding and process ... [more ▼]

As defined by ICH [1] and FDA, Quality by Design (QbD) stands for “a systematic approach to development that begins with predefined objectives and emphasizes product and process understanding and process control, based on sound science and quality risk management”. A risk–based QbD–compliant approach is proposed for the robust development of analytical methods. This methodology based on Design of Experiments (DoE) to study the experimental domain models the retention times at the beginning, the apex and the end of each peak corresponding to the compounds of a mixture and uses the separation criterion (S) rather than the resolution (RS) as a Critical Quality Attribute. Stepwise multiple linear regressions are used to create the models. The estimated error is propagated from the modelled responses to the separation criterion (S) using Monte Carlo simulations in order to estimate the predictive distribution of the separation criterion (S) over the whole experimental domain. This allows finding ranges of operating conditions that will guarantee a satisfactory quality of the method in its future use. These ranges define the Design Space (DS) of the method. In chromatographic terms, the chromatograms processed at operating conditions within the DS will assuredly show high quality, with well separated peaks and short run time, for instance. This Design Space can thus be defined as the subspace, necessarily encompassed in the experimental domain (i.e. the knowledge space), within which the probability for the criterion to be higher than an advisedly selected threshold is higher than a minimum quality level. Precisely, the DS is defined as “the multidimensional combination and interaction of input variables (e.g., material attributes) and process parameters that have been demonstrated to provide assurance of quality” [1]. Therefore, this DS defines a region of operating conditions that provide prediction of assurance of quality rather than only quality as obtained with traditional mean response surface optimisation strategies. For instance, in the liquid chromatography there is a great difference in e.g. predicting a resolution (RS) higher than 1.5 vs. predicting that the probability for RS to be higher than 1.5 (i.e. P(RS> 1.5)) is high. The presentation of this global methodology will be illustrated for the robust optimisation and DS definition of several liquid chromatographic methods dedicated to the separation of different mixtures: pharmaceutical formulations, API and impurities/degradation products, plant extracts, separation of enantiomers, … References [1] International Conference on Harmonisation (ICH) of Technical Requirements for Registration of Pharmaceuticals for Human Use, Topic Q8(R2): Pharmaceutical development, Geneva, 2009. Acknowledgements A research grant from the Belgium National Fund for Scientific Research (F.R.S-FNRS) to E. Rozet is gratefully acknowledged. [less ▲]

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See detailValidation and Routine of Ligand-Binding Assays, a Bayesian Perspective
Lebrun, Pierre ULg; Boulanger, Bruno; Hubert, Philippe ULg

Conference (2011, April 29)

The way to apply Bayesian modeling is illustrated to validate a ligand-binding assay such as ELISA. Hierarchical non-linear model and the associated predictive distribution of back-calculated responses ... [more ▼]

The way to apply Bayesian modeling is illustrated to validate a ligand-binding assay such as ELISA. Hierarchical non-linear model and the associated predictive distribution of back-calculated responses allow quantifying the total uncertainty of every future measurement with the assays, through the use of precision and risk profiles. It is also shown how the obtained posterior distribution of the parameters can be used as prior for new the calibration curves during routine. [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 (2011)

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 detailDesign Space and desirability index. A Bayesian predictive risk-based approach to flexibly achieve multi-criteria decision methods.
Lebrun, Pierre ULg; Boulanger, Bruno; Hubert, Philippe ULg et al

Conference (2011, March 02)

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

The Design Space (DS) is defined as the set of factors settings (input conditions) that will provide 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. In a Bayesian framework, the responses are modelled using a multivariate multiple regression model allowing deriving their joint predictive posterior distribution. On the basis of this consequent distribution, a multi-criteria risk-based decision is taken with respect to the pre-defined acceptance limits. This aims to identify the DS. In this context, desirability methodologies are also applied to take the risk-based decision in a more flexible way. An example based on high-performance liquid chromatography illustrates the applicability of the methodology with highly correlated and constrained responses. [less ▲]

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See detailTrial predictions vs. trial simulations in Model-based Drug Development: integrating uncertainties to evaluate the predictive probability of success.
Lebrun, Pierre ULg; Boulanger, Bruno; Jullion, Astrid

Conference (2011, March 02)

In a Model-Based Drug Development strategy, the first objective is to design studies such that the most reliable model estimates are obtained, in order to optimize the design of future studies and to take ... [more ▼]

In a Model-Based Drug Development strategy, the first objective is to design studies such that the most reliable model estimates are obtained, in order to optimize the design of future studies and to take decisions based on predictions. The objectives of the work is to present from a theoretical and practical point of view how to perform trial predictions, as opposed to trial simulations, by integrating the uncertainty of the parameters. The difference between prediction and simulation is important in early development when limited data or prior information are available. Indeed ignoring the uncertainty of parameter estimates can lead to wrong decisions. First, will be provided methodology, derived from Bayesian statistics, to perform trial predictions from the parameter estimates and their uncertainty, when obtained with conventional frequentist population methods. Second, a practical implementation in R will be shown. This generalized prediction shell can cope with any kind of structural population models: Ordinary Differential Equation, single & multiple doses, infusion, etc... The proposed shell is also flexible to allow the testing of various scenarios and study designs, and therefore evaluate the predictive probability of success of different protocols. When joint models for efficacy and safety are established, the Prediction-based Clinical Utility Index (p-CUI) and its distribution can directly be obtained for more riskless decision making. Examples will be shown to highlight in early phases the differences existing between trial prediction and trial simulation. This approach is required to permit Model-Based Drug Development strategy, and impact successfully decision in early clinical phases. [less ▲]

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See detailInnovative methodology to transfer conventional GC-MS heroin profiling to UHPLC-MS/MS
Debrus, Benjamin ULg; Broséus, Julian; Guillarme, Davy et al

in Analytical and Bioanalytical Chemistry (2011), 399(8), 2719-2730

Nowadays, in forensic laboratories, heroin profiling is frequently carried out by gas chromatography coupled with mass spectrometry (GC-MS). This analytical technique is well established, provides good ... [more ▼]

Nowadays, in forensic laboratories, heroin profiling is frequently carried out by gas chromatography coupled with mass spectrometry (GC-MS). This analytical technique is well established, provides good sensitivity and reproducibility, and allows the use of large databases. Despite those benefits, recently introduced analytical techniques, such as ultra-high-pressure liquid chromatography (UHPLC), could offer better chromatographic performance, which needs to be considered to increase the analysis throughput for heroin profiling. With the latter, chromatographic conditions were optimized through commercial modeling software and two atmospheric pressure ionization sources were evaluated. Data obtained from UHPLC–MS/MS were thus transferred, thanks to mathematical models to mimic GC-MS data. A calibration and a validation set of representative heroin samples were selected among the database to establish a transfer methodology and assess the models’ abilities to transfer using principal component analysis and hierarchical classification analysis. These abilities were evaluated by computing the frequency of successful classification of UHPLC–MS/MS data among GC-MS database. Seven mathematical models were tested to adjust UHPLC–MS/MS data to GC-MS data. A simplified mathematical model was finally selected and offered a frequency of successful transfer equal to 95%. [less ▲]

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See detailEvaluating the reliability of analytical results using a probability criterion: a Bayesian perspective
Rozet, Eric ULg; Govaerts, B.; Lebrun, Pierre ULg et al

in Analytica Chimica Acta (2011), 705

Methods validation is mandatory in order to assess the fitness of purpose of the developed analytical method. Of core importance at the end of the validation is the evaluation of the reliability of the ... [more ▼]

Methods validation is mandatory in order to assess the fitness of purpose of the developed analytical method. Of core importance at the end of the validation is the evaluation of the reliability of the individual results that will be generated during the routine application of the method. Regulatory guidelines provide a general framework to assess the validity of a method, but none address the issue of results reliability. In this study, a Bayesian approach is proposed to address this concern. Results reliability is defined here as “the probability of an analytical method to provide analytical results within predefined acceptance limits around their reference or conventional true concentration values over a defined concentration range and under given environmental and operating conditions.” By providing the minimum reliability probability needed for the subsequent routine application of the method, as well as specifications or acceptance limits , the proposed Bayesian approach provides the effective probability of obtaining reliable future analytical results over the whole concentration range investigated. This is summarized in a single graph: the reliability profile. This Bayesian reliability profile is also compared to two frequentist approaches, the first one derived from the work of Dewé et al. [Dewé W., Govaerts B., Boulanger B., Rozet E., Chiap P., Hubert Ph., Chemometr. Intell. Lab. Syst. 85 (2007) 262-268] and the second proposed by Govaerts et al. [B. Govaerts, W. Dewé, M. Maumy, B. Boulanger, Qual. Reliab. Engng. Int. 24 (2008) 667-680]. Furthermore, to illustrate the applicability of the Bayesian reliability profile, this approach is also applied here to a bioanalytical method dedicated to the determination of ketoglutaric acid (KG) and hydroxymethylfurfural (HMF) in human plasma by SPE-HPLC-UV. [less ▲]

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