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Article ; Online: Comprehensive analysis of vitamin D

Jambo, Hugues / Dispas, Amandine / Pérez-Mayán, Leticia / Rodríguez, Isaac / Ziemons, Éric / Hubert, Philippe

2024

Abstract: ... Vitamin ... ...

Abstract	Vitamin D
Language	English
Publishing date	2024-03-14
Publishing country	England
Document type	Journal Article
ZDB-ID	2462336-2
ISSN	1942-7611 ; 1942-7603
ISSN (online)	1942-7611
ISSN	1942-7603
DOI	10.1002/dta.3670
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Article ; Online: The benefits of validation of methods for toxicity testing outweigh its costs

Gourmelon, Anne / Hubert, Philippe / Grignard, Elise / Baumann, Lisa / Munn, Sharon / Michel, Cécile

ALTEX

2024

Abstract: The 4th Annual Forum on Endocrine Disrupters organized by the European Commission brought together authors of this article around the topic: "From bench to validated test guidelines: (pre)validation of test methods". Validation activities are meant to ... ...

Abstract	The 4th Annual Forum on Endocrine Disrupters organized by the European Commission brought together authors of this article around the topic: "From bench to validated test guidelines: (pre)validation of test methods". Validation activities are meant to demonstrate the relevance and reliability of methods and approaches used in regulatory safety testing. These activities are essential to facilitate regulatory use, still they are largely underfunded and unattractive to the scientific community. In the last decade, there has been large amounts of funding invested in European research towards the development of approaches that can be used in regulatory decision-making, including for the identification of endocrine disrupters. There is a vast pool of candidate test methods for potential regulatory applications, but most of them will not be used due to the absence of consideration of their relevance and reliability outside the method developer's laboratory. The article explains the reasons why such a gap exists between the outputs of research projects and the uptake in a regulatory context. In parallel, there are also increasing expectations from the regulatory science community that validation becomes more efficient with respect to time and resources. This article shares some of the lessons learned and proposes paths forward for validation of new methods that are not intended as one-to-one replacements of animal studies. This includes submitting only mature methods for validation that were developed following good practices and good documentation, proposing a greater emphasis on well-documented transferability studies, and adopting a cost-sharing model between those who benefit from validated methods.
Language	English
Publishing date	2024-03-19
Publishing country	Germany
Document type	Journal Article
ZDB-ID	165707-0
ISSN	1868-8551 ; 1018-4562 ; 0946-7785
ISSN (online)	1868-8551
ISSN	1018-4562 ; 0946-7785
DOI	10.14573/altex.2403051
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Article ; Online: Regulatory Testing for Endocrine Disruptors; Need for Validated Methods and Integrated Approaches.

Grignard, Elise / de Jesus, Kelly / Hubert, Philippe

Frontiers in toxicology

2022 Volume 3, Page(s) 821736

Language	English
Publishing date	2022-01-19
Publishing country	Switzerland
Document type	Journal Article
ISSN	2673-3080
ISSN (online)	2673-3080
DOI	10.3389/ftox.2021.821736
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Article: Investigation of potential substandard dry powder inhalers on EU and North African markets - evaluation of the delivered and fine particle doses.

Zhang, Yue / Hubert, Philippe / Hubert, Cédric

Journal of drug assessment

2022 Volume 11, Issue 1, Page(s) 20–25

Abstract: Purpose: Discovery of falsified Symbicort 320/9 Turbohaler identified in the UK in 2013 demonstrated that falsified dry powder inhalers were also present in the European market. This work aimed to investigate the current situation of formoterol- ... ...

Abstract	Purpose: Discovery of falsified Symbicort 320/9 Turbohaler identified in the UK in 2013 demonstrated that falsified dry powder inhalers were also present in the European market. This work aimed to investigate the current situation of formoterol-containing dry powder inhalers in Europe and North Africa by assessing their aerodynamic performance profile. Methods: A total of eight registered formoterol-based dry powder inhalers over the European and North African markets were involved in this study, including the reference drug Foradil. Samples were prepared using a multistage liquid impinger (MsLI) and further analyzed by a validated HPLC-UV method to determine the delivered and the fine particle doses (FPDs). This study also examined the impact of freezing-thawing cycles on sample stability in terms of analytical purpose handling. Results: No substandard dry powder inhalers were identified among the medicinal products involved in this work. The delivered dose (DD) of assessed drugs varied from 8.33 to 9.69 µg, while the FPD was between 1.86 and 3.35 µg. As expected, this work confirmed that the capsule composition and the barrier properties of the primary packaging can affect the FPD of dry powder for inhalation use. Conclusions: The FPD of products C and B was, respectively, 17.4 and 14.2% superior to Foradil, products D and H had the closest values compared to the original drug, and product F was 34.5% inferior. Additionally, this work showed that a high FPD can be achieved using HPMC capsules and moisture-impermeable primary packaging.
Language	English
Publishing date	2022-09-28
Publishing country	England
Document type	Journal Article
ZDB-ID	2663094-1
ISSN	2155-6660
ISSN	2155-6660
DOI	10.1080/21556660.2022.2125727
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Article: Supercritical fluid chromatography for pharmaceutical quality control: Current challenges and perspectives

Jambo, Hugues / Hubert, Philippe / Dispas, Amandine

Trends in analytical chemistry. 2022 Jan., v. 146

2022

Abstract: Quality control is a fundamental and critical activity in the pharmaceutical industry that permits to guarantee the quality of medicines and consequently safeguard the health of the patients. In recent years, supercritical fluid chromatography has ... ...

Abstract	Quality control is a fundamental and critical activity in the pharmaceutical industry that permits to guarantee the quality of medicines and consequently safeguard the health of the patients. In recent years, supercritical fluid chromatography has emerged as a robust and suitable analytical technique in several fields thanks to the introduction of modern SFC instruments. The present review aims to give an overview of the recent advances of the use of SFC in pharmaceutical quality control and highlights current challenges and perspectives. SFC instrumentation is presented and published applications are discussed from an analytical method lifecycle point of view. At each step regulatory requirements and recommendations are also presented to highlight the readiness of modern SFC for pharmaceutical QC.
Keywords	analytical chemistry ; instrumentation ; pharmaceutical industry ; quality control ; supercritical fluid chromatography
Language	English
Dates of publication	2022-01
Publishing place	Elsevier B.V.
Document type	Article
ZDB-ID	2014041-1
ISSN	0165-9936
ISSN	0165-9936
DOI	10.1016/j.trac.2021.116486
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Quantitative Structure Retention-Relationship Modeling: Towards an Innovative General-Purpose Strategy.

Kumari, Priyanka / Van Laethem, Thomas / Hubert, Philippe / Fillet, Marianne / Sacré, Pierre-Yves / Hubert, Cédric

Molecules (Basel, Switzerland)

2023 Volume 28, Issue 4

Abstract: Reversed-Phase Liquid Chromatography (RPLC) is a common liquid chromatographic mode used for the control of pharmaceutical compounds during their drug life cycle. Nevertheless, determining the optimal chromatographic conditions that enable this ... ...

Abstract	Reversed-Phase Liquid Chromatography (RPLC) is a common liquid chromatographic mode used for the control of pharmaceutical compounds during their drug life cycle. Nevertheless, determining the optimal chromatographic conditions that enable this separation is time consuming and requires a lot of lab work. Quantitative Structure Retention Relationship models (QSRR) are helpful for doing this job with minimal time and cost expenditures by predicting retention times of known compounds without performing experiments. In the current work, several QSRR models were built and compared for their adequacy in predicting the retention times. The regression models were based on a combination of linear and non-linear algorithms such as Multiple Linear Regression, Support Vector Regression, Least Absolute Shrinkage and Selection Operator, Random Forest, and Gradient Boosted Regression. Models were built for five pH conditions, i.e., at pH 2.7, 3.5, 6.5, and 8.0. In the end, the model predictions were combined using stacking and the performances of all models were compared. The k-nearest neighbor-based application domain filter was established to assess the reliability of the prediction for further compound prioritization. Altogether, this study can be insightful for analytical chemists working with RPLC to begin with the computational prediction modeling such as QSRR to predict the separation of small molecules.
MeSH term(s)	Reproducibility of Results ; Quantitative Structure-Activity Relationship ; Chromatography, Liquid/methods ; Chromatography, Reverse-Phase ; Algorithms ; Chromatography, High Pressure Liquid/methods
Language	English
Publishing date	2023-02-10
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	1413402-0
ISSN	1420-3049 ; 1431-5165 ; 1420-3049
ISSN (online)	1420-3049
ISSN	1431-5165 ; 1420-3049
DOI	10.3390/molecules28041696
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Article ; Online: Interpretable One-Class Classification of Raman Spectra Using Prediction Bands Estimated by Wavelet Regression.

Avohou, T Hermane / Sacré, Pierre-Yves / Hubert, Philippe / Ziemons, Eric

Analytical chemistry

2022 Volume 94, Issue 10, Page(s) 4183–4191

Abstract: Previously, we introduced a novel one-class classification (OCC) concept for spectra. It uses as acceptance space for genuine spectra of the target chemical, a prediction band in the wavelengths' space. As a decision rule, test spectra falling ... ...

Abstract	Previously, we introduced a novel one-class classification (OCC) concept for spectra. It uses as acceptance space for genuine spectra of the target chemical, a prediction band in the wavelengths' space. As a decision rule, test spectra falling substantially outside this band are rejected as noncomplying with the target, and their deviations are documented in the wavelengths' space. This band-based OCC concept was applied to smooth signals like near-infrared (NIR) spectra. A regression model based on a smoothed principal component (PC) representation of the training spectra was used to predict unseen trajectories of future spectra. The boundaries of the most central predicted trajectories were chosen as critical trajectories. We now propose a methodology to construct a similar band-based one-class classifier for Raman spectra, which are sharper and noisier than NIR spectra. The spectra are transformed by a composition of wavelet and principal component (wPC) expansions instead of just a PC expansion in the previous methodology for NIR spectra. Wavelets can capture sharp features of Raman signals and provide a framework to efficiently denoise them. A multinormal prediction model is then used to derive predictions of future wPC scores of unseen spectra. These predicted wPC scores are then backtransformed to obtain predictions of future trajectories of unseen spectra in the wavelengths' space, whose most central region defines the acceptance band or space. This band-based one-class classifier successfully classified the first derivatives of real pharmaceutical Raman spectra, while enjoying the advantage of documenting deviations from the critical trajectories in the wavelengths' space and hence is more interpretable.
MeSH term(s)	Spectrum Analysis, Raman/methods
Language	English
Publishing date	2022-03-04
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1508-8
ISSN	1520-6882 ; 0003-2700
ISSN (online)	1520-6882
ISSN	0003-2700
DOI	10.1021/acs.analchem.1c04098
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Article ; Online: Emerging analytical techniques for pharmaceutical quality control: Where are we in 2022?

Dispas, Amandine / Sacré, Pierre-Yves / Ziemons, Eric / Hubert, Philippe

Journal of pharmaceutical and biomedical analysis

2022 Volume 221, Page(s) 115071

Abstract: Quality control is a fundamental and critical activity in the pharmaceutical industry that guarantees the quality of medicines. QC analyses are currently performed using several well-known techniques, mainly liquid and gas chromatography. However, ... ...

Abstract	Quality control is a fundamental and critical activity in the pharmaceutical industry that guarantees the quality of medicines. QC analyses are currently performed using several well-known techniques, mainly liquid and gas chromatography. However, current trends are focused on the development of new techniques to reduce analysis time and cost, to improve the performances and decrease ecological footprint. In this context, analytical scientists developed and studied emerging technologies based on spectroscopy and chromatography. The present review aims to give an overview of the recent development of vibrational spectroscopy, supercritical fluid chromatography and multi-dimensional chromatography. Selected emerging techniques are discussed using SWOT analysis and published pharmaceutical QC applications are discussed.
MeSH term(s)	Chromatography, Supercritical Fluid/methods ; Drug Industry ; Pharmaceutical Preparations ; Quality Control
Chemical Substances	Pharmaceutical Preparations
Language	English
Publishing date	2022-09-22
Publishing country	England
Document type	Journal Article ; Review
ZDB-ID	604917-5
ISSN	1873-264X ; 0731-7085
ISSN (online)	1873-264X
ISSN	0731-7085
DOI	10.1016/j.jpba.2022.115071
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Article: Interpretable One-Class Classification of Raman Spectra Using Prediction Bands Estimated by Wavelet Regression

Avohou, T. Hermane / Sacré, Pierre-Yves / Hubert, Philippe / Ziemons, Eric

Analytical chemistry. 2022 Mar. 04, v. 94, no. 10

2022

Abstract: Previously, we introduced a novel one-class classification (OCC) concept for spectra. It uses as acceptance space for genuine spectra of the target chemical, a prediction band in the wavelengths’ space. As a decision rule, test spectra falling ... ...

Abstract	Previously, we introduced a novel one-class classification (OCC) concept for spectra. It uses as acceptance space for genuine spectra of the target chemical, a prediction band in the wavelengths’ space. As a decision rule, test spectra falling substantially outside this band are rejected as noncomplying with the target, and their deviations are documented in the wavelengths’ space. This band-based OCC concept was applied to smooth signals like near-infrared (NIR) spectra. A regression model based on a smoothed principal component (PC) representation of the training spectra was used to predict unseen trajectories of future spectra. The boundaries of the most central predicted trajectories were chosen as critical trajectories. We now propose a methodology to construct a similar band-based one-class classifier for Raman spectra, which are sharper and noisier than NIR spectra. The spectra are transformed by a composition of wavelet and principal component (wPC) expansions instead of just a PC expansion in the previous methodology for NIR spectra. Wavelets can capture sharp features of Raman signals and provide a framework to efficiently denoise them. A multinormal prediction model is then used to derive predictions of future wPC scores of unseen spectra. These predicted wPC scores are then backtransformed to obtain predictions of future trajectories of unseen spectra in the wavelengths’ space, whose most central region defines the acceptance band or space. This band-based one-class classifier successfully classified the first derivatives of real pharmaceutical Raman spectra, while enjoying the advantage of documenting deviations from the critical trajectories in the wavelengths’ space and hence is more interpretable.
Keywords	analytical chemistry ; models ; prediction ; regression analysis ; wavelet
Language	English
Dates of publication	2022-0304
Size	p. 4183-4191.
Publishing place	American Chemical Society
Document type	Article
ZDB-ID	1508-8
ISSN	1520-6882 ; 0003-2700
ISSN (online)	1520-6882
ISSN	0003-2700
DOI	10.1021/acs.analchem.1c04098
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Article ; Online: A pharmaceutical-related molecules dataset for reversed-phase chromatography retention time prediction built on combining pH and gradient time conditions.

Van Laethem, Thomas / Kumari, Priyanka / Hubert, Philippe / Fillet, Marianne / Sacré, Pierre-Yves / Hubert, Cédric

Data in brief

2022 Volume 42, Page(s) 108017

Abstract: There is a rising interest in the modeling and predicting of chromatographic retention. The progress towards more complex and comprehensive models emphasized the need for broad reliable datasets. The present dataset comprises small pharmaceutical ... ...

Abstract	There is a rising interest in the modeling and predicting of chromatographic retention. The progress towards more complex and comprehensive models emphasized the need for broad reliable datasets. The present dataset comprises small pharmaceutical compounds selected to cover a wide range in terms of physicochemical properties that are known to impact the retention in reversed-phase liquid chromatography. Moreover, this dataset was analyzed at five pH with two gradient slopes. It provides a reliable dataset with a diversity of conditions and compounds to support the building of new models. To enhance the robustness of the dataset, the compounds were injected individually, and each sequence of injections included a quality control sample. This unambiguous detection of each compound as well as a systematic analysis of a quality control sample ensured the quality of the reported retention times. Moreover, three different liquid chromatographic systems were used to increase the robustness of the dataset.
Language	English
Publishing date	2022-03-04
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	2786545-9
ISSN	2352-3409 ; 2352-3409
ISSN (online)	2352-3409
ISSN	2352-3409
DOI	10.1016/j.dib.2022.108017
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