Kris De Braekeleer

Research in Drug Development (RD3)

Pharmacognosy Bioanalysis and Drug Discovery

Research activities

My research are focused on : chemometrics for multivariate analysis of data matrices obtained with hyphenated and spectroscopic techniques in different fields of life science.

Top ten recent articles

Articles dans des revues avec comité de lecture

2024

Spectroscopy and Chemometrics for Conformity Analysis of e-Liquids: Illegal Additive Detection and Nicotine Characterization

Vaping electronic cigarettes (e-cigarettes) has become a popular alternative to smoking tobacco. When an e-cigarette is activated, a liquid is vaporized by heating, producing an aerosol that users inhale. While e-cigarettes are marketed as less harmful than traditional cigarettes, there are ongoing concerns about their long-term health effects, including potential lung damage. Therefore, it is essential to closely monitor and study the composition of e-liquids. E-liquids typically consist of propylene glycol, glycerin, flavorings and nicotine, though there have been reports of non-compliant nicotine concentrations and the presence of illegal additives. This study explored spectroscopic techniques to examine the conformity of nicotine labeling and detect the presence of the not-allowed additives: the caffeine, taurine, vitamin E and cannabidiol (CBD) in e-liquids. A total of 236 e-liquid samples were carefully selected for analysis. Chemometric analysis was applied to the collected data, which included mid-infrared (MIR) and near-infrared (NIR) spectra. Supervised modeling approaches such as partial least squares-discriminant analysis (PLS-DA) and soft independent modeling of class analogy (SIMCA) were employed to classify the samples, based on the presence of nicotine and the targeted additives. This study demonstrates the efficacy of MIR and NIR spectroscopic techniques in conjunction with chemometric methods (SIMCA and PLS-DA) for detecting specific molecules in e-liquids. MIR with autoscaling data preprocessing and PLS-DA achieved 100% classification rates for CBD and vitamin E, while NIR with the same approach achieved 100% for CBD and taurine. Overall, MIR combined with PLS-DA yielded the best classification across all targeted molecules, suggesting its preference as a singular technique.

2023

Evaluation of an electrochemical sensor and comparison with spectroscopic approaches as used today in practice for harm reduction in a festival setting—A case study: Analysis of 3,4‐methylenedioxymethamphetamine samples

Abstract More and more countries and organisations emphasise the value of harm reduction measures in the context of illicit drug use and abuse. One of these measures is drug checking, a preventive action that can represent a quick win by tailored consultation on the risks of substance use upon analytical screening of a submitted sample. Unlike drop‐in centres that operate within a fixed setting, enabling drug checking in a harm reduction context at events requires portable, easy to use analytical approaches, operated by personnel with limited knowledge of analytical chemistry. In this case study, four different approaches were compared for the characterisation of 3,4‐methylenedioxymethamphetamine samples and this in the way the approaches would be applied today in an event context. The four approaches are mid‐infrared (MIR), near‐infrared, and Raman spectroscopy, which are today used in drug checking context in Belgium, as well as an electrochemical sensor approach initially developed in the context of law enforcement at ports. The MIR and the electrochemical approach came out best, with the latter allowing for a direct straightforward analysis of the percentage 3,4‐methylenedioxymethamphetamine (as base equivalent) in the samples. However, MIR has the advantage that, in a broader drug checking context, it allows to screen for several molecules and so is able to identify unexpected active components or at least the group to which such components belong. The latter is also an important advantage in the context of the growing emergence of new psychotropic substances.

Characterization of CBD oils, seized on the Belgian market, using infrared spectroscopy: Matrix identification and CBD determination, a proof of concept

Abstract The availability of cannabidiol (CBD) oil products has increased in recent years. No analytical controls are mandatory for these products leading to uncertainties about composition and quality. In this paper, a methodology was developed to identify the oil matrix and to estimate the CBD content in such samples, using mid‐infrared and near‐infrared spectroscopy. Different oils were selected based on the information labeled on products and were bought in food stores in order to create a sample set with a variety of matrices. These oils were spiked with CBD to obtain samples with CBD levels from 0% to 20%. The first part of the study was focused on the qualitative analysis of the oil matrix. A classification model, based on Soft Independent Modeling of Class Analogy, was build using the spiked oils to distinguish between the different oil matrices. For both spectroscopic techniques, the sensitivity, the specificity, the accuracy and the precision were equal to 100%. These models were applied to determine the oil matrix of seized samples. The second part of the study was focused on the quantitative estimation of CBD. After determination of CBD in seized samples using gas chromatography‐tandem mass spectrometry, partial least square regression (PLS‐R) models were built, one for each matrix in the sample set. Both techniques were able to classify unknown oily samples according to their matrix, and although only few samples were available to evaluate the PLS‐R models, the approach clearly showed promising results for the estimation of the CBD content in oil samples.

Evaluation of Multivariate Filters on Vibrational Spectroscopic Fingerprints for the PLS-DA and SIMCA Classification of Argan Oils from Four Moroccan Regions

This study aimed to develop an analytical method to determine the geographical origin of Moroccan Argan oil through near-infrared (NIR) or mid-infrared (MIR) spectroscopic fingerprints. However, the classification may be problematic due to the spectral similarity of the components in the samples. Therefore, unsupervised and supervised classification methods—including principal component analysis (PCA), Partial Least Squares-Discriminant Analysis (PLS-DA) and Soft Independent Modeling of Class Analogy (SIMCA)—were evaluated to distinguish between Argan oils from four regions. The spectra of 93 samples were acquired and preprocessed using both standard preprocessing methods and multivariate filters, such as External Parameter Orthogonalization, Generalized Least Squares Weighting and Orthogonal Signal Correction, to improve the models. Their accuracy, precision, sensitivity, and selectivity were used to evaluate the performance of the models. SIMCA and PLS-DA models generated after standard preprocessing failed to correctly classify all samples. However, successful models were produced after using multivariate filters. The NIR and MIR classification models show an equivalent accuracy. The PLS-DA models outperformed the SIMCA with 100% accuracy, specificity, sensitivity and precision. In conclusion, the studied multivariate filters are applicable on the spectroscopic fingerprints to geographically identify the Argan oils in routine monitoring, significantly reducing analysis costs and time.

Quality Control and Authentication of Argan Oils : Application of advanced Analytical Techniques

2022

Response to letter to the editor: “Comments on ‘discrepancies between validated GC‐FID and UHPLC‐DAD methods for the analysis of Δ‐9‐THC and CBD in dried hemp flowers'”

Discrepancies between validated GC‐FID and UHPLC‐DAD methods for the analysis of Δ‐9‐THC and CBD in dried hemp flowers

Relative response factors and multiple regression models in liquid chromatography to quantify low-dosed components using alternative standards—proof of concept: total Δ9-THC content in cannabis flowers using CBD as reference

Contents of amoxillin drugs dispensed in Goma, Democratic Republic of Congo

Benchtop NIR standardization on handheld spectrometers to identify paracetamol tablets

Near-infrared spectroscopy (NIRS) allows innovative applications in terms of quality control, for example, in raw materials verification, in process analytical technology (PAT), and in discrimination between genuine and falsified medicines. The development of small and cheap handheld devices is expanding in the field, while trying to keep similar performances as benchtop instruments have. Considering traceability and quality control of drug compounds, this work is intended to identify 13 different paracetamol tablets on the Belgian market by using NIRS. The performances of a Fourier-transform near-infrared spectroscopy (FT-NIR) benchtop and two handheld NIR spectrometers were investigated comparatively. All spectra were collected through the blister in the reflectance diffuse mode. NIR spectral fingerprints were pretreated and analyzed using principal component analysis (PCA) and classified with soft independent modeling of class analogy (SIMCA). The performances of the spectrometers were evaluated after standardization of the reference benchtop database to the handheld spectrometers. The instrumental response of the benchtop spectrometer was standardized towards the handheld device using the piecewise direct standardization (PDS) algorithm. These investigations permitted the advantages and limitations of NIR data standardization on predictive models to be pointed out. The SIMCA models based on the spectral data of the benchtop (B), handheld 1 (H1), and handheld 2 (H2) instruments had an accuracy of 99.2%, 97.7%, and 96.2%, respectively. The same accuracy was obtained with the models of the transferred benchtop spectra for the H1 and H2 devices. However, adding handheld spectra to the transferred benchtop spectra resulted in models with improved accuracy: from 97.7% to 98.5% for the H1 instrument and from 96.2% to 97.7% for the H2 instrument. The proposed strategy highlights the potential of using a reference database collected by NIRS for pharmaceutical analyses by handheld NIR spectrometers in terms of traceability.

2021

Determination of the quality of metronidazole formulations by near-infrared spectrophotometric analysis

Determination of the quality of metronidazole formulations by near-infrared spectrophotometric analysis

In the quality control of medicines and the fight against the phenomenon of poor quality medicines, there is an urgent need for rapid and broad spectrum methods for screening these types of medicines. In the present work, we have used near infrared spectroscopy combined with multivariate data analysis to develop chemometric models for the classification and quantification of metronidazole in Burkina Faso pharmaceutical formulations. For this purpose, drug samples were collected in drugstores located in different Burkina Faso border zones. Four product classes were defined based on the national nomenclature: 3 classes for the generic drugs (C1, C3, and C4) and one class for the reference (C2) drugs. The exploratory analysis using PCA identified two clusters of drugs within class C1. Discrimination was confirmed by the developed and optimised DD-SIMCA model, with only one target class. The quality control of the samples from product class C1 was proven to be very satisfactory with specificities and sensitivities of 100%. The quantification models developed with the PLS-R method were successfully applied for the determination of the active ingredient content in the samples, with acceptable relative bias between 0.15 and 12.7 % with respect to the dose determined by the HPLC method. The RMSEC was estimated at 13.57 (R2, 0.9937), the RMSECV at 18.07 (R2, 0.9888) and the RMSEP at 13.69 (R2, 0.9941).The models developed and the results obtained are promising for routine quality control of similar formulations of metronidazole.

2020

An infrared spectroscopic approach to characterise white powders, easily applicable in the context of drug checking, drug prevention and on‐site analysis

More and more events, such as the summer music festivals, are considering the possibilities for implementing on-site testing of psychoactive drugs in the context of prevention and harm reduction. Although the on-site identification is already implemented by plenty of drug checking services, the required rapid quantitative dosing of the composition of illicit substances is still a missing aspect for a successful harm reduction strategy at events. In this paper, an approach is presented to identify white powders as amphetamine, cocaine, ketamine or others and to estimate the purity of the amphetamine, cocaine and ketamine samples using spectroscopic techniques hyphenated with partial least squares (PLS) modelling. For identification purposes, it was observed that mid-infrared spectroscopy hyphenated with PLS-discriminant analysis allowed the distinction between amphetamine, cocaine, ketamine and other samples and this with a correct classification rate of 93.1% for an external test set. For quantitative estimation, near-infrared spectroscopy was more performant and allowed the estimation of the dosage/purity of the amphetamine, cocaine and ketamine samples with an error of more or less 10% w/w. An easily applicable, practical and cost-effective approach for on-site characterisation of the majority of the psychoactive samples encountered in Belgian nightlife settings based on IR spectroscopy was proposed.

CBD oils on the Belgian market: A validated MRM GC-MS/MS method for routine quality control using QuEChERS sample clean up

Discrimination of legal and illegal Cannabis spp . according to European legislation using near infrared spectroscopy and chemometrics

Aerial parts containing cannabidiol can be purchased in a legal way but cannabis used as recreational drug is illegal in most European countries. Δ9-tetrahydrocannabinol is one of the main cannabinoids responsible for the psychotropic effect. European Union countries and Switzerland authorize a concentration of THC of 0.2 % and 1.0 % w/w, respectively, for smoking products and industrial hemp. Public health inspectors and law enforcement officers need to check the legality of samples. Therefore there is a need for innovative approaches, allowing quality control of these products in an easy way and preferably on site. In many countries, cultivation of industrial hemp is permitted if the THC content does not exceed 0.2 % w/w. A portable equipment could be a useful measuring tool for farmers to check for the THC content at regular time. In this work, 189 samples were analysed with a benchtop and a handheld NIR device in order to create two classification methods according to European and Swiss laws. All samples were also analysed by GC-FID to determine their THC concentration. Supervised analysis was applied in order to establish the best model. For the first classification, the accuracy was 91% for the test set with the benchtop data and 93 % for the test set with the handheld data. For the second classification, the accuracies were respectively 91 % and 95 %. The obtained models, hyphenating spectroscopic techniques and chemometrics, enable to discriminate legal and illegal cannabis samples according to European and Swiss laws.

Spectroscopic techniques combined with chemometrics for fast on-site characterization of suspected illegal antimicrobials

The threats of substandard and falsified (SF) antimicrobials, posed to public health, include serious adverse drug effects, treatment failures and even development of antimicrobial resistance. Next to these issues, it has no doubt that efficient methods for on-site screening are required to avoid that SF antimicrobials reach the patient or even infiltrate the legal supply chain. This study aims to develop a fast on-site screening method for SF antimicrobials using spectroscopic techniques (mid infrared, benchtop near infrared, portable near infrared and Raman spectroscopy) combined with chemometrics. 58 real-life illegal antimicrobials (claiming 18 different antimicrobials and one beta-lactamase inhibitor) confiscated by the Belgian Federal Agency for Medicines and Health Products (FAMHP) and 14 genuine antimicrobials were analyzed and used to build and validate models.Two types of models were developed and validated using supervised chemometric tools. One was used for the identification of the active pharmaceutical ingredients (APIs) by applying partial least squares-discriminant analysis (PLS-DA) and another one was used for the detection of non-compliant (overdosed or underdosed) samples by applying PLS-DA, k-nearest neighbors (k-NN) and soft independent modelling by class analogy (SIMCA). The best model capable of identifying amoxicillin and clavulanic acid (co-amoxiclav), azithromycin, co-trimoxazole and amoxicillin was based on the mid-infrared spectra with a correct classification rate (ccr) of 100%. The optimal model capable of detecting non-compliant samples within the combined group of amoxicillin and co-amoxiclav via SIMCA showed a ccr for the test set of 88% (7/8) using mid infrared or benchtop near infrared spectroscopy. The best model for detecting non-compliant samples within the group of amoxicillin via SIMCA was obtained using mid-infrared or Raman spectra, resulting in a ccr of 80% for the test set (4/5) and a ccr for calibration of 100%. For the group of co-amoxiclav, the optimal models showed a ccr of 100% for the detection of non-compliant samples by applying mid-infrared, benchtop near infrared or portable near infrared spectroscopy. Taken together, the obtained models, hyphenating spectroscopic techniques and chemometrics, enable to easily identify suspected SF antimicrobials and to differentiate non-compliant samples from compliant ones.

A new potential anti‐cancer beta‐carboline derivative decreases the expression levels of key proteins involved in glioma aggressiveness: A proteomic investigation

Gliomas remain highly fatal due to their high resistance to current therapies. Deregulation of protein synthesis contributes to cancer onset and progression and is a source of rising interest for new drugs. CM16, a harmine derivative with predicted high blood-brain barrier penetration, exerts antiproliferative effects partly through translation inhibition. We evaluated herein how CM16 alters the proteome of glioma cells. The analysis of the gel-free LC/MS and auto-MS/MS data showed that CM16 induces time- and concentration-dependent significant changes in the total ion current chromatograms. In addition, we observed spontaneous clustering of the samples according to their treatment condition and their proper classification by unsupervised and supervised analyses, respectively. A two-dimensional gel-based approach analysis allowed us to identify that treatment with CM16 may downregulate four key proteins involved in glioma aggressiveness and associated with poor patient survival (HspB1, BTF3, PGAM1, and cofilin), while it may upregulate galectin-1 and Ebp1. Consistently with the protein synthesis inhibition properties of CM16, HspB1, Ebp1, and BTF3 exert known roles in protein synthesis. In conclusion, the downregulation of HspB1, BTF3, PGAM1 and cofilin bring new insights in CM16 antiproliferative effects, further supporting CM16 as an interesting protein synthesis inhibitor to combat glioma.

2018

Determination of three main chlorogenic acids in water extracts of coffee leaves by liquid chromatography coupled to an electrochemical detector

Coffee is a beverage widely consumed in the world. The coffee species most commercialized worldwide are Arabica (Coffea arabica) and Robusta (Coffea canephora). Roasted coffee beans are the most used, but coffee leaves are also consumed as infusion in several countries for traditional medicinal purposes. They contain several interesting phenolic antioxidant compounds mainly belonging to chlorogenic acids (CGAs). In the present work, a liquid chromatography-electrochemical detection (LC-EC) method was developed for the determination of three main chlorogenic acid isomers, namely 3-, 4-, and 5-caffeoylquinic acids (CQA), in coffee leaves aqueous extracts. Samples from eight coffee species, namely; Coffea arabica, Coffea canephora, Coffea liberica, Coffea humilis, Coffea mannii, Coffea charrieriana, Coffea anthonyi, and Coffea liberica var. liberica, were grown and collected in tropical greenhouses. Linearity of the calibration graphs was observed in the range from the limit of quantification to 1.0 × 10−5 M, with R2 equal to 99.9% in all cases. High sensitivity was achieved with a limit of detection of 1.0 × 10−8 M for 3-CQA and 5-CQA (i.e., 3.5 µg/L) and 2.0 × 10−8 M for 4-CQA (i.e., 7.1 µg/L). The chromatographic profile of the samples harvested for each Coffea species was studied comparatively. Obtained raw data were pretreated for baseline variations and shifts in retention times between the chromatographic profiles. Principal Component Analysis (PCA) was applied to the pretreated data. According to the results, three clusters of Coffea species were found. In the water sample extracts, 5-CQA appeared to be the major isomer, and some species contained a very low amount of CQAs. Fluctuations were observed depending on the Coffea species and harvesting period. Significant differences between January and July were noticed regarding CQAs content. The species with the best CQAs/caffeine ratio was identified. The LC-EC data were validated by liquid chromatography-high resolution mass spectrometry (LC-HRMS).

Electrochemical studies of ethoxyquin and its determination in salmon samples by flow injection analysis with an amperometric dual detector

Ethoxyquin (EQ) is an antioxidant widely used in the food industry. Some concerns for human health have been reported since its utilization in animal feed may lead to residues in human food such as salmon samples. This work aimed to investigate the electrochemical behavior of EQ and its major oxidation products namely a dimer of EQ (EQDM) and ethoxyquin quinone imine (EQI) by cyclic voltammetry (CV) at a carbon screen printed electrode (cSPE). The stability of these products and their reactivity against glutathione (GSH) were also studied. Oxidized products and thiol adducts were identified by a microelectrolysis of an EQ solution onto a cSPE in the absence and in the presence of GSH. The products were analyzed off-line, by liquid chromatography coupled to a mass spectrometer (LC-MS). One of the generated product (EQI) was shown to be highly reactive towards GSH. Based on the redox pattern of EQ, a flow injection analysis with a dual cSPE was developed in order to detect in a rapid manner EQ in salmon samples. Since matrix effects were observed, matrix-matched calibration curves with spiked samples were built. A linear response was obtained between 20-100 μM and a limit of detection (LOD) of 7.5 μM (8.2 mg/kg of salmon). Trueness was assessed with recovery assays at three levels of concentration. The recovery was close to 100 %. Precision was determined as RSD (%) with values lower than 6 % in all cases.

Identification of coffee leaves using FT-NIR spectroscopy and SIMCA

Abundant literature has been devoted to coffee beans (green or roasted) chemical description but relatively few studies have been devoted to coffee leaves. Given the fact that coffee leaves are used for food and medicinal consumption, it was of interest to develop a rapid screening method in order to identify coffee leaves taxa. Investigation by Fourier - Transform near infrared spectroscopy (FT-NIRS) was performed on nine Coffea taxa leaves harvested over one year in a tropical greenhouse of the Botanic Garden Meise (Belgium). The only process after leaves harvesting was an effective drying and a homogeneous leaves grinding. FT-NIRS with SIMCA analysis allowed to discriminate the spectral profiles across taxon, aging stage (mature and senescence coffee leaves) and harvest period. This study showed that it was possible (i) to classify the different taxa, (ii) to identify their aging stage and (iii) to identify the harvest period for the mature stage with a correct classification rate of 99%, 100% and 90%, respectively.

2016

Bisacodyl als laxativum in de Belgische apotheek

2012

Ethinylestradiol and levonorgestrel preparations on the Belgian market: A comparitive study

2009

Nifedipine preparations on the Belgian market: A comparitive study

2008

Lisinopril and lisinopril/hydrochlorothiazide preparations on the Belgian market: A comparitive study

Propranolol preparations on the Belgian market: A comparitive study

2006

Fluconazole preparations on the Belgian market: A comparitive study

2005

Piracetam preparations on the Belgian market: A comparitive study

Ranitidine preparations on the Belgian market: A comparitive study

2000

Determination of the end point of a chemical synthesis process using on-line measured mid-infrared spectra

Improved purity assessment of high-performance liquid chromatography diode array detection data for overcoming the presence of the non-linearity artefact

Resolution of multicomponent peaks by multicomponent projection approach, positive matrix factorization and alternating least squares

1999

Application of several modified peak purity assays to real complex multicomponent mixtures by high-performance liquid chromatography with diode-array detection

On-line application of the orthogonal projection approach (OPA) and the soft independent modelling of class analogy approach (SIMCA) for the detection of the end point of a polymorph conversion reaction, by near infrared spectroscopy (NIR)

Nested Designs in Ruggedness testing

1998

Purity assessment and resolution of tetracycline hydrochloride samples using high-performance liquid chromatography with diode array detection

Influence and correction of temperature perturbations on NIR spectra during the monitoring of a polymorph conversion process prior to self-modelling mixture analysis

1997

Evaluation of the orthogonal projection approach (OPA) and the SIMPLISMA approach on the Windig standard spectral data sets