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See detailFast method for the simultaneous quantification of toxic polyphenols applied to the selection of genotypes of yam bean (Pachyrhizus sp.) seeds.
Lautié, Emmanuelle; Rozet, Eric ULg; Hubert, Philippe ULg et al

in Talanta (2013), 117

The purpose of the research was to develop and validate a rapid quantification method able to screen many samples of yam bean seeds to determine the content of two toxic polyphenols, namely pachyrrhizine ... [more ▼]

The purpose of the research was to develop and validate a rapid quantification method able to screen many samples of yam bean seeds to determine the content of two toxic polyphenols, namely pachyrrhizine and rotenone. The analytical procedure described is based on the use of an internal standard (dihydrorotenone) and is divided in three steps: microwave assisted extraction, purification by solid phase extraction and assay by ultra high performance liquid chromatography (UHPLC). Each step was included in the validation protocol and the accuracy profiles methodology was used to fully validate the method. The method was fully validated between 0.25mg and 5mg pachyrrhizin per gram of seeds and between 0.58mg/g and 4mg/g for rotenone. More than one hundred samples from different accessions, locations of growth and harvest dates were screened. Pachyrrhizine concentrations ranged from 3.29mg/g to lower than 0.25mg/g while rotenone concentrations ranged from 3.53mg/g to lower than 0.58mg/g. This screening along with principal component analysis (PCA) and discriminant analysis (DA) analyses allowed the selection of the more interesting genotypes in terms of low concentrations of these two toxic polyphenols. [less ▲]

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See detailA new criterion to assess distributional homogeneity in hyperspectral images of solid pharmaceutical dosage forms
Sacre, Pierre-Yves ULg; Lebrun, Pierre ULg; Chavez, Pierre-François ULg et al

Conference (2013, September)

During galenic formulation development, homogeneity of distribution is a critical parameter to check since it may influence activity and safety of the drug. Several techniques exist to assess this ... [more ▼]

During galenic formulation development, homogeneity of distribution is a critical parameter to check since it may influence activity and safety of the drug. Several techniques exist to assess this homogeneity, the most used and recognized being HPLC. However, these techniques are destructive, time consuming and uses a lot of organic solvents. Vibrational spectroscopies are promising green chemistry techniques that may replace HPLC for several analysis tasks thanks of their rapid, non-destructive and non-pollutant characteristics. Raman hyperspectral imaging is a technique of choice for assessing the distributional homogeneity of compounds of interest. Indeed, the combination of both spectroscopic and spatial information provides a detailed knowledge of chemical composition and component distribution. When dealing with hyperspectral imaging, multivariate data analysis is necessary to extract the concentration map of the compound of interest that will be used to assess sample homogeneity. Actually, most authors assess homogeneity using parameters of the histogram of intensities (e.g. mean, skewness and kurtosis). However, this approach does not take into account spatial information and loses the main advantage of imaging. Recently, Rosas et al. proposed a homogeneity index based on the Poole index. However, it necessitates cutting the maps in non-overlapping macropixels and is therefore quickly limited with small maps. To overcome this limitation, we propose a new criterion that combines Continuous Level Moving Blocks and homogeneity curves with a randomization step to assess the distributional homogeneity. This distributional homogeneity index (DHI) enables analysis of hyperspectral maps without apriori knowledge. It has been applied on five pharmaceutical formulations with different blending conditions. The uniformity content values of the API (present at a concentration of 7% w/w) measured by HPLC ranged from RSD: 0.46% to 11.04%. Ten tablets per formulation have been mapped over a region of interest of 4 mm². After extracting pure spectra by MCR-ALS, the concentration maps of the API were computed using classical least squares analysis. DHI have been computed with a hundred simulations for the randomization step for each concentration map. Afterwards, a mean DHI and standard deviation values were computed per formulation. A linear relationship has been observed between the RSD values and the mean DHI. These results enabled us to select the formulation with the best homogeneity. Further experiments are in progress to check whether hyperspectral imaging combined with DHI could be used in routine to assess blending homogeneity of well-known formulations. [less ▲]

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See detailChemical imaging of small molecules from simple to complex matrices: Quantitative approaches based on Surface Enhanced Raman scattering
De Bleye, Charlotte ULg; Sacre, Pierre-Yves ULg; Chavez, Pierre-François ULg et al

Conference (2013, July)

Surface Enhanced Raman scattering (SERS) allows to dramatically exalt the Raman diffusion of molecules absorbed or very closed to rough metallic surfaces while keeping their structural information. SERS ... [more ▼]

Surface Enhanced Raman scattering (SERS) allows to dramatically exalt the Raman diffusion of molecules absorbed or very closed to rough metallic surfaces while keeping their structural information. SERS chemical imaging, presenting a high specificity and sensibility, allows acquiring a visual representation of samples combining spectral and spatial measurements. This technique could become a powerful tool in pharmaceutical and biological analysis enabling to identify and quantify molecules thanks to chemometric evaluation while looking at their distribution or their interactions. In this context, SERS chemical imaging is investigated in detection or quantitative determination of molecules in pharmaceutical and biological matrices. The feasibility of making quantitative measurements using SERS is evaluated on small target molecules models such as 4-aminophenol and lactate. Firstly, a SERS method to quantify 4-aminophenol which is the primary impurity of acetaminophen coming from its degradation during the storage or from its synthesis was developed on a real pharmaceutical formulation. The standard addition method was selected as calibration method in order to take into account the matrix effect coming from the different components of the latter. Despite the well-known stability and repeatability problems of SERS, the method was thoroughly validated by means of accuracy profiles as decision tool. Moreover, this validation methodology allowed to define a first estimation of the real analytical performance of the technique. Secondly, the detection of lactate, which is a critical metabolite implicated in several metabolic disorders, was successfully tested in the physiological concentration in a simple matrix. Preliminary results for the determination of this metabolic biomarker were also very promising allowing to consider more complex matrices. Based on these results, SERS chemical imaging was implemented to detect 4-aminophenol in a pharmaceutical tablet formerly pulverised by a SERS substrate. Through this imaging technique, it was not only possible to detect the presence of the impurity at the limit of specification of 0.1% (w/w) but it was also possible to differentiate tablets comprising different concentrations of the latter. These promising results represent the first step towards quantitative measurements using SERS chemical imaging. [less ▲]

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See detailA New Method for Quality by Design Robust Optimization in Liquid Chromatography
Debrus, Benjamin ULg; Lebrun, Pierre ULg; Rozet, Eric ULg et al

in LC-GC Europe (2013), -(-), -

A new method to optimize liquid chromatography (LC) methods using a Quality by Design (QbD) approach is presented. This method is based on the use of design of experiments (DOE) and independent component ... [more ▼]

A new method to optimize liquid chromatography (LC) methods using a Quality by Design (QbD) approach is presented. This method is based on the use of design of experiments (DOE) and independent component analysis (ICA) to accurately estimate the modelled responses (that is, the retention times at the beginning, the apex, and the end) of each peak, even for coeluted peaks. The modelling of these responses usesmultiple linear regressions, while the propagation of the error affecting the responses and coming from the models is carried out by Monte Carlo simulation. The design space is determined as the region of assay factors where the probability to reach baseline-resolved peaks is higher than the desired level of quality. This method was applied to the optimization of the separation of nine compounds in a mixture, yielding the design space and the demonstration of robustness of the method. Finally, the method was validated. [less ▲]

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See detailInnovative Methodology for the Definition of Design Spaces of Chromatographic Methods
Rozet, Eric ULg; Debrus, B; Lebrun, Pierre ULg et al

Conference (2013, June 06)

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, … [less ▲]

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See detailDéveloppement de méthodes de quantification en milieu complexe par chromatographie liquide microfluidique couplée à la spectrometrie de masse
Houbart, Virginie ULg; Rozet, Eric ULg; Crommen, Jacques ULg et al

Conference (2013, June)

L’hepcidine est un biomarqueur peptidique dont l’intérêt tant comme outil de diagnostic que de suivi de pathologies est de plus en plus solidement établi. Il existe donc une demande forte d’outils ... [more ▼]

L’hepcidine est un biomarqueur peptidique dont l’intérêt tant comme outil de diagnostic que de suivi de pathologies est de plus en plus solidement établi. Il existe donc une demande forte d’outils sensibles et robustes afin de la doser au sein de milieux biologiques tels que le plasma ou le sérum. Une méthode analytique a été développée à l’aide d’un système chromatographique miniaturisé (nanoLC-chip) couplé à un spectromètre de masse permettant d’assurer un dosage de l’hepcidine à la fois sensible et fiable. Lors du développement de cette méthode, il a été constaté que la composition de l’échantillon avait une influence majeure sur la réponse analytique. Or, l’utilisation de systèmes chromatographiques miniaturisés implique souvent l’injection de volumes proportionnellement très importants par rapport aux dimensions du système, ce qui amplifie encore l’impact de sa composition. C’est pourquoi il est capital d’avoir une bonne compréhension des phénomènes qui ont lieu entre l’injection de l’échantillon dans le système chromatographique et la détection par spectrométrie de masse, et particulièrement lors du développement de méthodes analytiques quantitatives. Dans cette étude, nous avons utilisé la planification expérimentale afin de mieux comprendre le comportement chromatographique des peptides, ainsi que les facteurs qui influencent la sensibilité de la méthode développée. Un mélange de peptides a été sélectionné, varié tant du point de vue du poids moléculaire que du point isoélectrique et de l’hydropathie. Un plan de criblage a permis de délimiter le domaine expérimental ainsi que les facteurs significatifs parmi la composition de la phase mobile (proportion et nature de l’agent de paire d’ions) et de l’échantillon en lui-même (nature de l’agent de paire d’ions et proportion de solvant organique). Ensuite, un plan d’expériences factoriel complet a été mis en œuvre afin d’observer plus finement le rôle de chaque facteur ainsi que les interactions éventuelles qui les lient. Certains facteurs ont montré un effet très marqué tant sur l’intensité de la réponse que sur la rétention. Entre autres, la composition de l’échantillon, facteur parfois négligé lors du développement de méthodes, a démontré son importance capitale, en particulier sur les phénomènes de rétention des peptides. Les données obtenues ont également permis de dégager des conditions optimales d’analyse en termes de rétention et de sensibilité. Enfin, une analyse en composantes principales a également été réalisée sur le grand nombre de données récoltées dans le but de mettre en évidence d’éventuels propriétés physicochimiques des peptides qui pourraient avoir un impact significatif sur les réponses étudiées. [less ▲]

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See detailA BAYESIAN PROBABILITY CRITERION TO ASSESS ANALYTICAL RESULTS RELIABILITY
Rozet, Eric ULg; Lebrun, Pierre ULg; Boulanger, B et al

Conference (2013, May 21)

In pharmaceutical and biomedical industries, quantitative analytical methods such as HPLC play a key role. Indeed, the analytical results obtained from them are used to make crucial decisions such as the ... [more ▼]

In pharmaceutical and biomedical industries, quantitative analytical methods such as HPLC play a key role. Indeed, the analytical results obtained from them are used to make crucial decisions such as the release of batches of drugs, the evaluation of safety and efficacy of new drug candidates or the monitoring of patients health. Prior to their routine use, analytical methods are submitted to a stringent validation study [1] where they have to demonstrate that they are fit for their final purpose, i.e. providing accurate results: where is the analytical result, is the theoretical unknown true concentration of analyte in the sample analyzed and a regulatory acceptance limit. Typically this demonstration is made by either providing point estimates of systematic error (bias) and random error (variance) or sometimes by providing interval estimates of these statistical parameters at several well defined concentration levels of the target analyte [2]. They are then compared to maximum acceptable levels. More recently, tolerance intervals approaches have been proposed that are evaluated in a similar way at these key concentration levels [3]. However none of these decision approaches allow knowing the probability to obtain accurate results over the whole concentration range of interest: is a vector of parameters and Pmin is a minimum reliability probability. Frequentist approximations have been proposed to estimate this probability but only at the concentration levels experimentally tested [4,5]. In this work, a linear hierarchical Bayesian approach is proposed. It takes into account the potential random characteristic of the slope and intercept observed from one analytical run to the other, but it also integrates the possible covariance between the parameters. Additionally, heteroscedasticity of the residual variance over the concentration range investigated is taken into account. A situation regularly observed in practice. Finally a reliability profile for the whole concentration range studied is obtained using MCMC sampling. This profile provides the probability (Prel) to obtain accurate results over the full concentration range investigated. This profile is then compared to a minimum reliability probability (Pmin) that will define the valid concentration range of the analytical method. The usefulness of this approach is illustrated through the validation of a bioanalytical method and also compared with one concentration level at a time frequentist approaches [4,5]. [1] International Conference on Harmonization (ICH) of Technical Requirements for registration of Pharmaceuticals for Human Use Topic Q2 (R1): Validation of Analytical Procedures: Text and Methodology, Geneva, 2005. [2] A. Bouabidi and al., J. Chromatogr. A, 1217 (2010) 3180. [3] Ph. Hubert and al., J. Pharm. Biomed. Anal., 36 (2004) 579. [4] W. Dewé and al., Chemometr. Intell. Lab. Syst. 85 (2007) 262. [5] B. Govaerts and al., Qual. Reliab. Engng. Int. 24 (2008) 667. [less ▲]

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See detailMEASURING VARIABILITY SOURCES IN NMR METABOLOMIC STUDIES
Rozet, Eric ULg; De Tullio, Pascal ULg; Hubert, Philippe ULg et al

Conference (2013, May 13)

Due to the huge amount of information available in NMR spectra obtained from the analysis of metabolomic experiments, multivariate analysis such as Principal Component Analysis (PCA) are required to ... [more ▼]

Due to the huge amount of information available in NMR spectra obtained from the analysis of metabolomic experiments, multivariate analysis such as Principal Component Analysis (PCA) are required to understand the influence of treatments over the metabolites [1]. However, many experiments in metabolomics studies have more complexes variability structures than simply comparing several treatments: they may include time effects, biological effects such as diet or hormonal status, and other blocking factors or variability sources: samples stability, age of the individuals, pH of a buffer, days of acquisition, and so on. Metabolomic data analysis needs to extract from the spectral data matrix the variations linked to a change indicated in the factor of interest. However other sources of variability may impair this objective. This stresses the importance to discover the sources of variability of the spectral metabolomic data using appropriate methodology. Classically, to analyze such data analysis of variance (ANOVA) or multivariate ANOVA (MANOVA) [2] is used. However direct application of these methodologies to NMR spectra obtained from structured metabolomics studies is inappropriate or impossible. More complex data analyses methodologies are required to understand the importance of the various factors implied in the experiments and to provide a measure of their variance components. Three related methodologies have been proposed to achieve this: ASCA [3], ANOVA-PCA [4] and AComDim [5]. The ASCA and ANOVA-PCA methodologies combine first an analysis of variance step (ANOVA) and then a PCA step. The AComDim one adds to the output of the ANOVA-PCA step a multi-block analysis. In this presentation, the usefulness and applicability of these advanced techniques to data analysis of NMR metabolomic spectra are provided to highlight the increase of knowledge gained and the estimation of main sources of variability arising in an experimental setup. Two NMR databases will be used [6]. The first one concerns human serum analyzed by 1H-NMR where three random factors are present: day of measurement (3 days), sample (2 samples per individual) and replication of analyses as well as two fixed controlled factors, time of measurement after thawing (2 times) and two protein suppression methods for the spectral pre-treatment. The second database is about the 1H-NMR analyses of rats’ urine where two different concentrations of citrate and of hippurate were deliberately added and three other sources of variability are present: urine pool diluted or not diluted, repetitions of analyses, days of analyses (three days), as well as two different spectral pre-treatment procedures. [less ▲]

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See detailNON-ANTHOCYANIN POLYPHENOLS QUANTIFICATION IN EUTERPE OLERACEA FRUITS BY A UHPLC−LTQ-ORBITRAP MS METHOD
Dias, Aecio; Rozet, Eric ULg; Chataigné, G et al

Poster (2013, May)

High antioxidant and anti-inflammatory activities have been observed from non-anthocyanin polyphenols of E. oleracea fruits [1-2]. The aim of this work was to quantify major non-anthocyanin polyphenols by ... [more ▼]

High antioxidant and anti-inflammatory activities have been observed from non-anthocyanin polyphenols of E. oleracea fruits [1-2]. The aim of this work was to quantify major non-anthocyanin polyphenols by an accurate UHPLC−LTQ-Orbitrap MS method. Fruits were harvested in Pará state (Brazil), processed to pulp and lyophilised. 0.5g of dry pulp powder was defatted by sonication with petroleum ether. The residue was then extracted five times with 5mL MeOH each time for 30 min (optimized conditions giving recovery rates > 90%). The extract was evaporated to dryness with a RapidVap® evaporator at 35°C. Solubilization of the dried extract was realised using 40% MeOH. For the UHPLC quantification, a HSS C18 column (1.8µm) was used with a gradient elution of MeOH and H2O both with 0.1% HCOOH and the ionisation source (ESI) was operated in NI mode. 26 compounds were identified, among them 7 identified for the first time in this fruit. Total error and accuracy profiles were used as validation criteria. Calibration in the matrix was found to be more accurate than calibration without matrix. Trueness, repeatability, intermediate precision, selectivity, response function, linearity and LOD/LOQ for 12 non-anthocyanin phenolic compounds were evaluated and the quantification method validated. [1] J. Kang et al., Food Chem. 122 (2010) 610–617. [2] J. Kang et al., Food Chem. 128 (2011) 152–157. [less ▲]

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See detailEnzymatic but not compensated Jaffe methods reach the desirable specifications of NKDEP at normal levels of creatinine. results of the French multicentric evaluation
Boutten, Anne; Bargnoux, Anne-Sophie; Carlier, Marie-Christine et al

in Clinica Chimica Acta (2013), 419

The French Society of Clinical Biochemistry conducted this study to compare the accuracy and performances of the best creatinine enzymatic assays and the compensated Jaffe methods from the same ... [more ▼]

The French Society of Clinical Biochemistry conducted this study to compare the accuracy and performances of the best creatinine enzymatic assays and the compensated Jaffe methods from the same manufacturers. Creatinine was measured in 3 serum pools with creatinine levels of 35.9±0.9 μmol/L, 74.4±1.4 μmol/L, and 97.9±1.7 μmol/L (IDMS determination). The performances of the assays (total error that includes the contribution of bias and imprecision) were evaluated using Monte-Carlo simulations and compared against desirable NKDEP criteria. The enzymatic assays always fell within the desirable total Error of 7.6%. By contrast, this requirement was never obtained for the compensated Jaffe methods at the critical level of 74.4±1.4 μmol/L. Only the compensated Jaffe creatinine on Olympus analyzer reached this specification at 35.9±0.9 and 97.9±1.7 μmol/L levels. This study demonstrates that, despite substantial improvement regarding traceability to the IDMS reference method and precision, compensated Jaffe creatinine methods, by contrast to enzymatic ones, do not reach the desirable specifications of NKDEP at normal levels of creatinine. [less ▲]

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See detailValidation methodologies of near infrared spectroscopy methods in pharmaceutical applications
Chavez, Pierre-François ULg; De Bleye, Charlotte ULg; Sacre, Pierre-Yves ULg et al

in European Pharmaceutical Review (2013), 18(1), 3-6

As any analytical methods, a mandatory step at the end of the development of a near infrared spectroscopy (NIRS) method is the validation. This step enables to give enough guarantees that each future ... [more ▼]

As any analytical methods, a mandatory step at the end of the development of a near infrared spectroscopy (NIRS) method is the validation. This step enables to give enough guarantees that each future results coming from the application of the method in routine will be closed enough to the true value. However, from the literature, a minority of NIRS methods are thoroughly validated despite of the guidelines published by different group and regulatory authorities to help analyst to adequately decide if his method can be considered as valid. In this context, the aim of this review is to offer a critical overview of the different validation methodologies applied to assess the validity of quantitative methods using near infrared spectroscopy used in the field of pharmacy. [less ▲]

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See detailDesign Spaces for Analytical Methods
Rozet, Eric ULg; Lebrun, Pierre ULg; Debrus, Benjamin ULg et al

in Trends in Analytical Chemistry [=TRAC] (2013), 42

Since the adoption of the ICH Q8 document concerning the development of pharmaceutical processes following a Quality by Design (QbD) approach, there have been many discussions on the opportunity for ... [more ▼]

Since the adoption of the ICH Q8 document concerning the development of pharmaceutical processes following a Quality by Design (QbD) approach, there have been many discussions on the opportunity for analytical method developments to follow a similar approach. A key component of the QbD paradigm is the definition of the Design Space of analytical methods where assurance of quality is provided. Several Design Spaces for analytical methods have been published, stressing the importance of this concept. This paper aims at explaining what is an analytical method Design Space, why it is useful for the robust development and optimization of analytical methods and how to build such a Design Space. A strong emphasis is made by distinguishing the usual mean response surface approach, overlapping mean response surfaces and the desirability function one to other probabilistic approaches as only these last ones correctly define a Design Space. In addition, recent publications assessing the Design Space of analytical methods are reviewed and discussed. [less ▲]

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See detailBlood lead, urinary lead, urinary δ-aminolevulinic acid and urinary porphyrins levels among people living in kinshasa, D.R. Congo : a pilot biomonitoring study
Mputu Malolo, Corneille-Liévin; Ndelo di Phanzu, Josaphat; Marini Djang'Eing'A, Roland ULg et al

in Acta Clinica Belgica (2013), 68(6), 475

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