Publications of Philippe Hubert
Bookmark and Share    
Full Text
See detailOptimization of a robust and reliable FITC labeling process for CE-LIF analysis of pharmaceutical compounds using design of experiments strategy
Emonts, Paul ULiege; Avohou, Tonakpon Hermane ULiege; Hubert, Philippe ULiege et al

in Journal of Pharmaceutical and Biomedical Analysis (2021), 205

Fluorescence, especially laser induced fluorescence (LIF), is a powerful detection technique thanks to its specificity and high sensitivity. The use of fluorescence detection hyphenated to separation ... [more ▼]

Fluorescence, especially laser induced fluorescence (LIF), is a powerful detection technique thanks to its specificity and high sensitivity. The use of fluorescence detection hyphenated to separation technique often requires the labeling of analytes with suitable fluorescent dye, such as FITC for the labeling of molecules presenting amino groups. Nevertheless, the labeling of analytes could be a tedious, time consuming and a non-robust step of the analytical workflow. In this context, the objective of the present work was to propose a robust and reliable FITC labeling process. Primary and secondary amino compounds (i.e. synthetic cathinones) were selected as model compounds because they are representative of a large proportion of pharmaceutical small molecules. Based on prior knowledge, DoE combined with multivariate statistical modeling was performed to optimize the process. Reaction time and pH of reaction buffer were highlighted as the most critical parameters to control the process. The study showed also the benefit of short reaction time to maximize the labeling efficiency. Indeed, optimal condition was defined as reaction time of 32 min with ratio between FITC and analytes of 40.4 and the buffer reaction pH of 9.7. In addition, variance component analysis was integrated to the DoE to estimate the variability of process and to evaluate its applicability for quantitative purpose. These chemometric approaches helped to develop an efficient labeling process able to reach high sensitivity for CE-LIF analysis (i.e. 10 nM) with good precision (i.e. intermediate precision values lower or close to 5 %). [less ▲]

Detailed reference viewed: 34 (10 ULiège)
See detailDevelopment of a sensitive MEKC-LIF method for the analysis of synthetic cathinones and amphetamines Paul Emonts
Emonts, Paul ULiege; Avohou, Tonakpon Hermane ULiege; Hubert, Philippe ULiege et al

Poster (2021, October)

Synthetic cathinones (SCs) are phenylalkylamine compounds related to natural cathinone from Catha Edulis leaves. Given their structural similarities with amphetamines, these compounds are mainly drug of ... [more ▼]

Synthetic cathinones (SCs) are phenylalkylamine compounds related to natural cathinone from Catha Edulis leaves. Given their structural similarities with amphetamines, these compounds are mainly drug of abuse. Indeed, these substances constitute the second most frequently seized group of new psychoactive substances and counted more than 130 compounds in Europe (EMCDDA 2016). In addition to be sold on the illegal market, some of them are currently available online using various brand names as “bath salts”, taking advantage of a legislative void. In this context, reliable analytical tools are required to track these substances. The main objective of the present study was to develop a capillary electrophoresis separation method with laser induced fluorescence detection (CE-LIF) to analyze most frequently observed SCs. As these stimulants are frequently used as substitutes to these drugs, and especially in ecstasy, most common amphetamines were also included in the panel of 14 target analytes. Due to their lack of native fluorescence, analytes were labeled using fluorescein isothiocyanate isomer I (FITC). Design of experiments strategy was performed to optimize the labeling process [1]. The FITC/analyte ratio, pH of reaction buffer and reaction time were selected as factors of the DoE. The objective was to maximize the peak intensity observed in CE while keeping an easy and fast protocol. Moreover, the estimation of process precision (i.e. repeatability and intermediate precision) was performed simultaneously by including triplicates of the central point during each day of DoE experiments. Regarding the CE method, various BGE composition and additives were investigated in order to optimize the separation [2]. As non-ionic surfactants showed interesting selectivity, the development of a micellar electrokinetic capillary chromatography (MEKC) method was performed. The nature and concentration of non-ionic surfactants were deeply studied. The interest of polyethylene glycol ether surfactant was clearly demonstrated for the separation of these closely related compounds. To conclude, a reliable labeling process was optimized thanks to DoE approach. Regarding the separation, the high resolving power of MEKC combined to the high sensitivity of LIF detection (pg/mL order) seemed to be an appropriate tool for the screening of both legal and illegal drugs [less ▲]

Detailed reference viewed: 20 (1 ULiège)
Full Text
See detailApplication of the analytical quality by design principles to the development of a qualitative surface-enhanced Raman scattering method: A proof of concept
Deidda, Riccardo ULiege; Avohou, Tonakpon Hermane ULiege; Dumont, Elodie et al

in Journal of Raman Spectroscopy (2021)

Analytical quality by design (AQbD) is a systematic approach that allows developing analytical methods in a more science-based way, due to the higher quality of information collected during the ... [more ▼]

Analytical quality by design (AQbD) is a systematic approach that allows developing analytical methods in a more science-based way, due to the higher quality of information collected during the development process. However, its application remains limited to the development of separation methods. (i.e., liquid chromatography and capillary electrophoresis). Its application to spectroscopic techniques remains underexplored, despite the potential benefits. The aim of this work was to demonstrate the application of the AQbD principles to surface-enhanced Raman scattering (SERS) method development, detailing each step characterizing this approach. First, crystal violet (CV) was chosen as a model compound and the analytical target profile was defined. Risk assessment was performed to individuate the critical method parameters. The intensity of the CV band at 1175 cm−1 was selected as critical method attribute to be modeled and maximized. A screening study was conducted to study 11 aggregation agents (AAs) at different concentration levels (range 0.010–1 M) and in two solvent media (aqueous and methanolic). The two AAs exhibiting the strongest signal, one for each medium, were retained. Once these parameters were fixed, an I-optimal design was applied to optimize the entire analysis process. Here, the volumes of nanoparticle suspension and AA solution added to the SERS samples were simultaneously varied. Two method operable design regions, one for each medium, were computed using a Bayesian design space approach. The latter enabled evaluating the failure risk associated to each experimental condition explored and choosing those that best fit the analytical purpose in the experimental domain. [less ▲]

Detailed reference viewed: 53 (17 ULiège)
See detailLa chromatographie en phase supercritique, une alternative aux méthodes normées ? Un voyage quantitatif de la répétabilité à la reproductibilité
Dispas, Amandine ULiege; Guillarme, Davy; Clarke, Adrian et al

Conference (2021, September)

L’intérêt de la chromatographie en phase supercritique dans le domaine pharmaceutique n’est désormais plus à démontrer. De plus, les performances quantitatives de cette technique ont été estimées lors de ... [more ▼]

L’intérêt de la chromatographie en phase supercritique dans le domaine pharmaceutique n’est désormais plus à démontrer. De plus, les performances quantitatives de cette technique ont été estimées lors de nombreuses études pour diverses applications telles que le dosage de molécules actives ou d’impuretés dans des matrices médicamenteuses ou biologiques. Cependant, pour démontrer qu’une nouvelle méthode peut être une réelle alternative à une méthode normée de la Pharmacopée, il est nécessaire de démontrer que celle-ci est transférable et applicable dans divers laboratoires de contrôle qualité. De même, l’évaluation de la reproductibilité (troisième niveau de la précision) via une étude inter-laboratoire est requise. Dans ce contexte, nous avons récemment démontré la transférabilité et la reproductibilité d’une méthode SFC-UV de dosage des impuretés du sulfate de salbutamol dans 18 laboratoires [1-2]. Les valeurs de variance de reproductibilité évaluées lors de cette étude étaient similaires voire plus faibles que celles reportées dans la littérature pour le dosage d’impuretés par HPLC. Par la suite, cette approche a été étendue pour inclure différents types d’instrumentation SFC. Cette deuxième étude a été réalisée dans 21 laboratoires utilisant des instruments Agilent®, Shimadzu® et Waters® (n = 7 pour chaque type d’instrument) [3]. Premièrement, la méthode a été transférée afin de vérifier la séparation et définir les paramètres spécifiques aux instruments Agilent® et Shimadzu®. Dans un second temps, l’étude inter-laboratoire a été réalisée dans les 21 laboratoires, elle comportait un test d’aptitude suivi de l’analyse de 3 échantillons contenant des concentrations en impuretés permettant de couvrir l’ensemble de la gamme de concentration validée. Après analyse des résultats pour vérifier la consistance des résultats (ISO 5725:2), la reproductibilité de la méthode a été estimée en tenant compte de la variance des réplicats, inter-séries et inter-laboratoires. Comme attendu, la variance de reproductibilité était plus élevée que celle mesurée lors de la première étude effectuée sur un seul type d’instruments. L’utilisation de différent types d’instruments est en effet une source de variabilité supplémentaire en SFC. Cependant, les variances de répétabilité et de reproductibilité estimées lors de cette étude sont similaires à celles décrites pour des méthodes HPLC de dosage d’impuretés pharmaceutiques (CV reproductibilité de 15%). Ces résultats mettent en évidence la robustesse et la fiabilité de la SFC dans le cadre du contrôle de qualité des médicaments. [less ▲]

Detailed reference viewed: 25 (1 ULiège)
Full Text
See detailInterlaboratory study of a supercritical fluid chromatography method for the determination of pharmaceutical impurities: Evaluation of multi-systems reproducibility
Dispas, Amandine ULiege; Clarke, Adrian; Grand-Guillaume Perrenoud, Alexandre et al

in Journal of Pharmaceutical and Biomedical Analysis (2021), 203

Modern supercritical fluid chromatography (SFC) is now a well-established technique, especially in the field of pharmaceutical analysis. We recently demonstrated the transferability and the ... [more ▼]

Modern supercritical fluid chromatography (SFC) is now a well-established technique, especially in the field of pharmaceutical analysis. We recently demonstrated the transferability and the reproducibility of a SFC-UV method for pharmaceutical impurities by means of an inter-laboratory study. However, as this study involved only one brand of SFC instrumentation (Waters®), the present study extends the purpose to multi-instrumentation evaluation. Specifically, three instrument types, namely Agilent®, Shimadzu®, and Waters®, were included through 21 laboratories (n = 7 for each instrument). First, method transfer was performed to assess the separation quality and to set up the specific instrument parameters of Agilent® and Shimadzu® instruments. Second, the inter-laboratory study was performed following a protocol defined by the sending lab. Analytical results were examined regarding consistencies within- and between-laboratories criteria. Afterwards, the method reproducibility was estimated taking into account variances in replicates, between-days and between-laboratories. Reproducibility variance was larger than that observed during the first study involving only one single type of instrumentation. Indeed, we clearly observed an ‘instrument type’ effect. Moreover, the reproducibility variance was larger when considering all instruments than each type separately which can be attributed to the variability induced by the instrument configuration. Nevertheless, repeatability and reproducibility variances were found to be similar than those described for LC methods; i.e. reproducibility as %RSD was around 15 %. These results highlighted the robustness and the power of modern analytical SFC technologies to deliver accurate results for pharmaceutical quality control analysis. [less ▲]

Detailed reference viewed: 27 (10 ULiège)
Full Text
See detailApplication of NIR handheld transmission spectroscopy and chemometrics to assess the quality of locally produced antimalarial medicines in the Democratic Republic of Congo
Ciza Hamuli, Patient ULiege; Sacre, Pierre-Yves ULiege; Kanyonyo, M.R. et al

in Talanta Open (2021), 3

In recent decades, more than 15% of the antimalarials marketed in low- and middle-income countries have been of poor quality, in which quinoline derivatives and quinine-based formulations account for 21 ... [more ▼]

In recent decades, more than 15% of the antimalarials marketed in low- and middle-income countries have been of poor quality, in which quinoline derivatives and quinine-based formulations account for 21%. Near infrared spectroscopy (NIR) was chosen for its fast and inexpensive test properties as well as the ability of using handheld devices to monitor drugs directly on the field. Data driven - soft independent modelling of class analogy (DD-SIMCA) and partial least squares (PLS) regression models were developed for qualitative and quantitative purpose, respectively. The specificity and selectivity tests were performed using the DD-SIMCA models on the placebo, the quinidine and cinchonine standard samples. Then, PLS regression methods have been developed and validated for the quality control of quinine dosage forms manufactured by a major local manufacturer in the Democratic Republic of Congo (DRC). Calibration and validation samples were prepared by dissolving quinine sulphate /quinine hydrochloride in the presence of excipients in HCl 1M. The opportunity to work with dissolved quinine with a cheap and readily available medium in low and middle income countries allowed analysis of different pharmaceutical forms (oral drops, solutions for injection and tablets) with the same regression model. DD-SIMCA models have demonstrated for both equipment perfect authentication of quinine and good discrimination of the two alkaloids close to quinine namely cinchonine and quinidine. The NIR PLS regression models were successfully validated using the total error approach with acceptance limits set at ± 10% with a risk level of 5%. The predictive performance of the methods developed was tested in terms of robustness. [less ▲]

Detailed reference viewed: 105 (31 ULiège)
Full Text
See detailDesign of experiments and design space approaches in the pharmaceutical bioprocess optimization
Kasemiire, Alice ULiege; Avohou, Tonakpon Hermane ULiege; De Bleye, Charlotte ULiege et al

in European Journal of Pharmaceutics and Biopharmaceutics (2021), 166(September), 144-154

The optimization of pharmaceutical bioprocesses suffers from several challenges like complexity, upscaling costs, regulatory approval, leading to the risk of delivering substandard drugs to patients ... [more ▼]

The optimization of pharmaceutical bioprocesses suffers from several challenges like complexity, upscaling costs, regulatory approval, leading to the risk of delivering substandard drugs to patients. Bioprocess is very complex and requires the evaluation of multiple components that need to be monitored and controlled in order to attain the desired state when the process ends. Statistical design of experiments (DoE) is a powerful tool for optimizing bioprocesses because it plays a critical role in the quality by design strategy as it is useful in exploring the experimental domain and providing statistics of interest that enable scientists to understand the impact of critical process parameters on the critical quality attributes. This review summarizes selected publications in which DoE methodology was used to optimize bioprocess. The main objective of the critical review was to clearly demonstrate potential benefits of using the DoE and design space methodologies in bioprocess optimization. [less ▲]

Detailed reference viewed: 62 (15 ULiège)
Full Text
See detailPAT Applications of NIR Spectroscopy in the Pharmaceutical Industry
Sacre, Pierre-Yves ULiege; De Bleye, Charlotte ULiege; Hubert, Philippe ULiege et al

in Crocombe, Richard A.; Leary, Pauline E.; Kammrath, Brooke W. (Eds.) Portable Spectroscopy and Spectrometry, Volume 1, Technologies and Instrumentation (2021)

Detailed reference viewed: 91 (6 ULiège)
See detailLA SFC, UNE ALTERNATIVE AUX MÉTHODES NORMÉES DE LA PHARMACOPÉE EUROPÉENNE ?
Dispas, Amandine ULiege; Guillarme, Davy; Hubert, Philippe ULiege

Scientific conference (2021, May 20)

Detailed reference viewed: 15 (1 ULiège)
Full Text
See detailNew perspective for the in-field analysis of cannabis samples using handheld near-infrared spectroscopy: A case study focusing on the determination of Δ9-tetrahydrocannabinol
Deidda, Riccardo ULiege; Coppey, Florentin; Damergi, Dhouha et al

in Journal of Pharmaceutical and Biomedical Analysis (2021)

The aim of the present study was to explore the feasibility of applying near-infrared (NIR) spectroscopy for the quantitative analysis of Δ9-tetrahydrocannabinol (THC) in cannabis products using handheld ... [more ▼]

The aim of the present study was to explore the feasibility of applying near-infrared (NIR) spectroscopy for the quantitative analysis of Δ9-tetrahydrocannabinol (THC) in cannabis products using handheld devices. A preliminary study was conducted on different physical forms (entire, ground and sieved) of cannabis inflorescences in order to evaluate the impact of sample homogeneity on THC content predictions. Since entire cannabis inflorescences represent the most common types of samples found in both the pharmaceutical and illicit markets, they have been considered priority analytical targets. Two handheld NIR spectrophotometers (a low-cost device and a mid-cost device) were used to perform the analyses and their predictive performance was compared. Six partial least square (PLS) models based on reference data obtained by UHPLC-UV were built. The importance of the technical features of the spectrophotometer for quantitative applications was highlighted. The mid-cost system outperformed the low-cost system in terms of predictive performance, especially when analyzing entire cannabis inflorescences. In contrast, for the more homogeneous forms, the results were comparable. The mid-cost system was selected as the best-suited spectrophotometer for this application. The number of cannabis inflorescence samples was augmented with new real samples, and a chemometric model based on machine learning ensemble algorithms was developed to predict the concentration of THC in those samples. Good predictive performance was obtained with a root mean squared error of prediction of 1.75% (w/w). The Bland-Altman method was then used to compare the NIR predictions to the quantitative results obtained by UHPLC-UV and to evaluate the degree of accordance between the two analytical techniques. Each result fell within the established limits of agreement, demonstrating the feasibility of this chemometric model for analytical purposes. Finally, resin samples were investigated by both NIR devices. Two PLS models were built by using a sample set of 45 samples. When the analytical performances were compared, the mid-cost spectrophotometer significantly outperformed the low-cost device for prediction accuracy and reproducibility. [less ▲]

Detailed reference viewed: 50 (12 ULiège)
Full Text
See detailPixel-based Raman hyperspectral identification of complex pharmaceutical formulations
Coic, Laureen ULiege; Sacre, Pierre-Yves ULiege; Dispas, Amandine ULiege et al

in Analytica Chimica Acta (2021), 1155

Hyperspectral imaging has been widely used for different kinds of applications and many chemometric tools have been developed to help identifying chemical compounds. However, most of those tools rely on ... [more ▼]

Hyperspectral imaging has been widely used for different kinds of applications and many chemometric tools have been developed to help identifying chemical compounds. However, most of those tools rely on factorial decomposition techniques that can be challenging for large data sets and/or in the presence of minor compounds. The present study proposes a pixel-based identification (PBI) approach that allows readily identifying spectral signatures in Raman hyperspectral imaging data. This strategy is based on the identification of essential spectral pixels (ESP), which can be found by convex hull calculation. As the corresponding set of spectra is largely reduced and encompasses the purest spectral signatures, direct database matching and identification can be reliably and rapidly performed. The efficiency of PBI was evaluated on both known and unknown samples, considering genuine and falsified pharmaceutical tablets. We showed that it is possible to analyze a wide variety of pharmaceutical formulations of increasing complexity (from 5 to 0.1% (w/w) of polymorphic impurity detection) for medium (150 x 150 pixels) and big (1000 x 1000 pixels) map sizes in less than 2 minutes. Moreover, in the case of falsified medicines, it is demonstrated that the proposed approach allows the identification of all compounds, found in very different proportions and, sometimes, in trace amounts. Furthermore, the relevant spectral signatures for which no match is found in the reference database can be identified at a later stage and the nature of the corresponding compounds further investigated. Overall, the provided results show that Raman hyperspectral imaging combined with PBI enables rapid and reliable spectral identification of complex pharmaceutical formulations. [less ▲]

Detailed reference viewed: 64 (20 ULiège)
Full Text
See detailDevelopment of a prototype device for near real-time surface-enhanced Raman scattering monitoring of biological samples
Dumont, Elodie ULiege; De Bleye, Charlotte ULiege; Rademaker, Gilles ULiege et al

in Talanta (2021), 224

With the fast growth of bioanalytical surface-enhanced Raman scattering (SERS), analytical methods have had to adapt to the complex nature of biological samples. In particular, interfering species and ... [more ▼]

With the fast growth of bioanalytical surface-enhanced Raman scattering (SERS), analytical methods have had to adapt to the complex nature of biological samples. In particular, interfering species and protein adsorption onto the SERS substrates have been addressed by sample preparation steps, such as precipitation or extraction, and by smart SERS substrate functionalisation. These additional handling steps however result in irreversible sample alteration, which in turn prevents sample monitoring over time. A new methodology, that enables near real-time, non-invasive and non-destructive SERS monitoring of biological samples, is therefore proposed. It combines solid SERS substrates, benefitting from liquid immersion resistance for extended periods of time, with an original protein filtering device and an on-field detection by means of a handheld Raman analyser. The protein removal device aims at avoiding protein surface fouling on the SERS substrate. It consists of an ultracentrifugation membrane fixed under a cell culture insert for multi-well plates. The inside of the insert is dedicated to containing biological samples. The solid SERS substrate and a simple medium, without any protein, are placed under the insert. By carefully selecting the membrane molecular weight cutoff, selective diffusion of small analytes through the device could be achieved whereas larger proteins were retained inside the insert. Non-invasive SERS spectral acquisition was then carried out through the bottom of the multi-well plate. The diffusion of a SERS probe, 2-mercaptopyridine, and of a neurotransmitter having a less intense SERS signal, serotonin, were first successfully monitored with the device. Then, the latter was applied to distinguish between subclones of cancerous cells through differences in metabolite production. This promising methodology showed a high level of versatility, together with the capability to reduce cellular stress and contamination hazards. [less ▲]

Detailed reference viewed: 65 (24 ULiège)
Full Text
See detailUsing prediction bands for near-infrared spectra for authentication and verification of drug products
Avohou, Tonakpon Hermane ULiege; Sacre, Pierre-Yves ULiege; Hubert, Philippe ULiege et al

Conference (2021, February 03)

1. Introduction Near-infrared spectroscopy (NIR) is a powerful analytical tool approved by the EU and US pharmacopeias. It can provide an accurate description of the physicochemical composition of samples ... [more ▼]

1. Introduction Near-infrared spectroscopy (NIR) is a powerful analytical tool approved by the EU and US pharmacopeias. It can provide an accurate description of the physicochemical composition of samples, and hence can be used to fingerprint a drug product. With the fast-development and miniaturization of handheld spectrophotometers, this vibrational spectroscopy technique is more and more used in a large range of research and industrial applications involving characterization, identification and quality control of drug products. These applications however require the use of accurate, robust, risk-oriented, computationally efficient decision-making tools to statistically compare high dimensional spectra to references in order to identify or control the quality of pharmaceutical products. We propose a novel and probabilistic one-class classification strategy based on newly emerging chemometric techniques of (Bayesian) functional data analysis, for the identification and quality control of medicines. The strategy uses the concept of prediction bands as acceptance region. 2. Material and methods A representative training set of spectra of a target product is sampled from several batches of that product using a MicroPhazir® (ThermoFisher Inc) reflection NIR spectrophotometer. Based on this set and using Bayesian (functional) principal component regression [1], a statistical prediction band is constructed so that it contains a high proportion, say at least 90% or 95% of future spectra of the product (see Figure 1 for illustration). The upper and lower limits of the band are used as critical trajectories or reference spectra that would enable testing the deviation from regular behavior or excursions out of the bands of any future unit from the product batch based on its spectrum, while controlling the risks of errors [2]. 3. Results and discussion The proposed one-class classification methodology has been applied to the identification of Dafalgan® 1g. Four other paracetamol-based drugs were used to evaluate the specificity. Spectra were measured with the handheld NIR device. The predicted trajectories of future Dafalgan® 1g spectra and their limiting behaviors (band limits) are illustrated on Figure 2A and B. The pattern of deviation from the band limits (acceptance region) are illustrated on Figure 2C and D for a Dafalgan® 1g spectrum and an Excedryn® spectrum respectively. The method compares favorably with existing methods like the SIMCA, with high sensitivity between 90% and 98% and similar specificity. 4. Conclusion A new one-class classification method for identification and quality control of drug products is proposed, using prediction bands for NIR spectra. Compared with existing spectral matching models, the proposed approach is fully predictive, with more intuitive interpretation of classification results. 5. References [1] J.S. Morris, Functional regression. Annual Review Statistics and its Applications 2, 2015, pp. 321-359. [2] TH Avohou, et al. A probabilistic class-modelling method based on prediction bands for functional spectral data:Methodological approach and application to near-infrared spectroscopy. Analytica Chimica Acta 1144, 2021, pp. 130-149. [less ▲]

Detailed reference viewed: 21 (3 ULiège)
See detailQuantitative structure-retention relationship modelling of small pharmaceutical compounds in reverse phase liquid chromatography
Kumari, Priyanka ULiege; Van Laethem, Thomas ULiege; Hubert, Philippe ULiege et al

Conference (2021, February 03)

1 Introduction Reverse phase liquid chromatography (RPLC) is still one of the most used analytical technique for the analysis of chemical mixtures. The development step can be very extensive given the ... [more ▼]

1 Introduction Reverse phase liquid chromatography (RPLC) is still one of the most used analytical technique for the analysis of chemical mixtures. The development step can be very extensive given the different possible stationary phases, mobile phases and other analysis parameters. A thorough screening takes a lot of time and requires many consumables even with a systematic approach using experimental planification. The development of quantitative structure-retention relationship (QSRR) models can advantageously replace this experimental screening phase with in silico chromatograms simulations. QSRR models are statistically derived relationships between chromatographic parameters and computed molecular descriptors characterizing the analytes. Several linear and nonlinear models have been used to build such models (Partial least squares (PLS), Bayesian, Ridge, Lasso, K-nearest neighbors (KNN), support vector machines (SVR), artificial neural network (ANN), etc.) [1]. Ensemble machine-learning models covering boosting, bagging and stacking have shown to generally outperform other algorithms [2]. In the presented work, QSRR models will be built for different chromatographic conditions (pH and gradient time). Subsequently, a response surface model (RSM) will be used allowing predictions of retention times in new conditions within the studied space [3, 4, 5]. 2 Material and methods Ninety-eight molecules were selected to cover a wide range in LogP values (-3.22 – 6.45), molecular weight (46 – 454 g/mol) and includes both non-charged and charged molecules (25 non-charged and 73 charged). Experimental retention times were acquired in house on three different HPLC systems (Waters Alliance) with gradients from 100% buffer to 5% buffer in 20 and 60 minutes considering five different pH levels (2.7, 3.5, 5, 6.5 and 8). These two gradients and five pH conditions represent the ten datasets that will be analyzed. Methanol was selected as the organic modifier. At first, the weighted average of the molecular descriptors of each present form of the compound are calculated. Then, four machine-learning models were fitted on the ten datasets using the 26 features selected using stepwise regression methods. RMSE and R² values were used to compare the different models. Finally, a RSM is fitted for each compound based on the predicted retention times starting from equation (1) while removing pH terms for neutral. log⁡(𝑡𝑅)=𝛽0+𝛽1×𝑝𝐻+𝛽2×𝑡𝑔𝑟𝑎𝑑+𝛽12×𝑝𝐻×𝑡𝑔𝑟𝑎𝑑+𝛽11×𝑝𝐻2+𝛽111×𝑝𝐻3 (1) 3 Results and discussion Out of the tested models, XGBoost and Lasso were the best performing ones showing R² values as high as 0.99 for the training set and R² higher than 0.95 for the prediction set shown in Figure1. Their blended prediction performed better over single model predictions. Using those predictions, RSM models were built. The different predictions of ibuprofen from the external test set can be seen on Figure2. Figure 1: Plot of observed vs. predicted retention times for best prediction model (XGBoost) Figure 2: Observed (hollow points), ML predicted (filled points) and RSM predicted (curves) retention times of ibuprofen for 20, 40 and 60 minutes gradients 4 Conclusion The RPLC retention times predicted by QSRR models followed by a RSM model were close to the experimental ones. This demonstrates that the combination of QSRR and RSM offers the possibility to replace usefully the experimental screening phase by computational methods when developing chromatographic techniques for known sets of molecules. The presented results concern a limited set of test molecules and will be further extended to new molecules and chromatographic modes. [less ▲]

Detailed reference viewed: 81 (10 ULiège)
Full Text
See detailA probabilistic class-modelling method based on prediction bands for functional spectral data: Methodological approach and application to near-infrared spectroscopy
Avohou, Tonakpon Hermane ULiege; Sacre, Pierre-Yves ULiege; Lebrun, Pierre ULiege et al

in Analytica Chimica Acta (2021), 1144

Class-modelling methods aim to predict the conformity of new unknown samples with a single target class, using statistical decision rules built exclusively with objects of that class. This article ... [more ▼]

Class-modelling methods aim to predict the conformity of new unknown samples with a single target class, using statistical decision rules built exclusively with objects of that class. This article introduces a novel class-modelling method for spectral data. The method uses the concept of beta(%)-prediction band for functional data to classify spectra. The band is defined by an upper and a lower limiting spectra which delimit critical trajectories for beta(%) of future spectra of the target class. It is constructed in three main steps: firstly, a naïve bootstrap sample of calibration spectra is projected onto a parsimonious principal component (PC) basis and their scores are estimated. The posterior predictive distribution of the scores on each PC is estimated using a Bayesian zero-mean normal model. This procedure is repeated on naïve bootstrap estimations of the PCs to obtain the predictive distribution of the scores. These enable to account for all modelling uncertainties including the random deviation of scores from their zero-mean on each PC, uncertainty in the variance of scores (eigenvalue) on each PC, and uncertainty in the PC estimations. Secondly, the predicted scores are back-transformed to the original signal scale to obtain the predictive distribution of future spectra. Thirdly, the predicted spectra are ranked to select the beta(%) most central ones as typical set, whose ranges of variation are used to construct the simultaneous limits of the band. Once the band is constructed, reconstructions of future unknown test spectra by bootstrap PC models are projected onto it, and the extent to which they overlap with it is used to decide their acceptance or rejection. The statistical properties and classification performances of the proposed prediction band are evaluated on real near-infrared datasets and compared to the well-known soft-independent modelling of class analogy (SIMCA) model. The results of the evaluation provide evidence that the proposed prediction band possesses satisfactory predictive performances. It even outperforms the SIMCA while offering attractive advantages like risk-management and straightforward physical interpretability of outlyingness patterns of tested spectra. [less ▲]

Detailed reference viewed: 50 (16 ULiège)
Full Text
See detailClassification of polymorphic forms of fluconazole in pharmaceuticals by FT-IR and FT-NIR spectroscopy.
Alaoui Mansouri, Mohammed ULiege; Ziemons, Eric ULiege; Sacre, Pierre-Yves ULiege et al

in Journal of Pharmaceutical and Biomedical Analysis (2021), 196

The main goal of this work was to test the ability of vibrational spectroscopy techniques to differentiate between different polymorphic forms of fluconazole in pharmaceutical products. These are mostly ... [more ▼]

The main goal of this work was to test the ability of vibrational spectroscopy techniques to differentiate between different polymorphic forms of fluconazole in pharmaceutical products. These are mostly manufactured with fluconazole as polymorphic form II and form III. These crystalline forms may undergo polymorphic transition during the manufacturing process or storage conditions. Therefore, it is important to have a method to monitor these changes to ensure the stability and efficacy of the drug. Each of FT-IR or FT-NIR spectra were associated to partial least squares-discriminant analysis (PLS-DA) for building classification models to distinguish between form II, form III and monohydrate form. The results has shown that combining either FT-IR or FT-NIR to PLS-DA has a high efficiency to classify various fluconazole polymorphs, with a high sensitivity and specificity. Finally, the selectivity of the PLS-DA models was tested by analyzing separately each of three following samples by FT-IR and FT-NIR: lactose monohydrate, which is an excipient mostly used for manufacturing fluconazole pharmaceutical products, itraconazole and miconazole. These two last compounds mimic potential contaminants and belong to the same class as fluconazole. Based on the plots of Hotelling’s T² vs Q residuals, pure compounds of miconazole and itraconazole, that were analyzed separately, were significantly considered outliers and rejected. Furthermore, binary mixtures consist of fluconazole form-II and monohydrate form with different ratios were used to test the suitability of each technique FT-IR and FT-NIR with PLS-DA to detect minimum contaminant or polymorphic conversion from a polymorphic form to another using also the plots of Hotelling’s T² vs Q residuals. [less ▲]

Detailed reference viewed: 71 (19 ULiège)
Full Text
See detailDevelopment of a sensitive MEKC‐LIF method for synthetic cathinones analysis
Emonts, Paul ULiege; Servais, Anne-Catherine ULiege; Ziemons, Eric ULiege et al

in Electrophoresis (2021), 0

Synthetic cathinones are phenylalkylamine compounds related to natural cathinone from Catha edulis leaves. Due to their sympathomimetic effects comparable to common illicit drugs, these substances are ... [more ▼]

Synthetic cathinones are phenylalkylamine compounds related to natural cathinone from Catha edulis leaves. Due to their sympathomimetic effects comparable to common illicit drugs, these substances are mainly drugs of abuse and constitute the secondmost frequently seized group of new psychoactive substances. In order to ensure their regulation and to promote public health, reliable analytical tools are required to track these substances. In the present study, we developed a CE hyphenated to laser-induced fluorescence detection method to demonstrate its suitability to perform fast and cost-effective synthetic cathinones analysis. Fourteen compounds including isobaric compounds and position isomers were selected to encompass the large panel of chemical structures. To separate the FITC-labeled analytes (presenting the same negative charge and close mass to charge ratios), MEKC separation mode was selected. Method selectivity was not suitable using common surfactants. In this context, alkyl polyethylene glycol ether surfactants were successfully used as neutral surfactant to overcome this analytical challenge. The effect of surfactant nature on separation performances and migration behaviors of the analytes was also studied. Optimal BGE composition included 75 mM borate buffer at pH 9.3 and 0.4 mM of C12E10 surfactant. Final MEKC separation conditions were proposed to analyze a large panel of synthetic cathinones. This method helped to reach a sensitivity with LOD from 0.1 to 0.4 nM (pg/mL order). [less ▲]

Detailed reference viewed: 26 (4 ULiège)
Full Text
See detailAcceptabilité du dépistage néonatal de la drépanocytose au cours de la pandémie au COVID-19 à Kisangani, en République Démocratique du Congo
TEBANDITE KASAI, Emmanuel; ALWORONG'A OPARA, Jean-Pierre; BATINA AGASA, Salomon et al

in Pan African Medical Journal (2020)

Introduction: the implementation of neonatal screening to identify infants with sickle cell disease during the COVID-19 pandemic is a major challenge in the Democratic Republic of the Congo (DRC). The ... [more ▼]

Introduction: the implementation of neonatal screening to identify infants with sickle cell disease during the COVID-19 pandemic is a major challenge in the Democratic Republic of the Congo (DRC). The purpose of this study is to determine whether socio-economic factors are associated with acceptability of newborn screening to identify infants with sickle cell disease during the COVID-19 pandemic in Kisangani, DRC. Methods: we conducted an observational study of mothers sensitized to neonatal screening to detect sickle cell disease in their newborns with hemotypeSCTM (HT401RUO-USA). The study was carried out at the maternity wards in Kisangani from March 21st to June 30th 2020. Collected data were parity, educational level, age, socio-economic level, occupation, awareness and the reason for the denial of screening. Results: out of 55,5% (273/492) of sensitized mothers, 107 (39,19%) accepted and 166 (60,80%) refused neonatal screening to detect sickle cell disease in their newborn. The reasons for refusal were lack of information (67,5%; 95% CI [59,8-74,5]), lack of money due to confinement (66,3%; 95% CI [58,5-73,4]), blood test to develop a vaccine for protection against COVID-19 (63,2%; 95% CI = [55,4-70,6]). Factors associated with the acceptability of screening were age > 35 years (p = 0.0009; ORa = 3.04; 95% CI = 1.57-5.87) and low socio-economic level (p = 0.0016; ORa = 2.29; 95% CI = 1.37-3.85). Conclusion: the acceptability of neonatal screening to detect sickle cell disease during COVID-19 is low in Kisangani. The government should identify effective communication channels to promote health care initiatives. [less ▲]

Detailed reference viewed: 18 (4 ULiège)