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Simultaneous quantification of Ibuprofen and Paracetamol in combined tablet formulations by UV–VIS spectrophotometry and chemometric modelling
No full textUV–VIS spectrophotometry is a simple, fast and relatively environmentally protective instrumental technique (depending on the solvents employed), which is commonly used in pharmaceutical quantitative analyses, if an absence of signal interference between the component of interest and other matrix constituents is assured. However, chemometric modelling broadens the applicability of UV–VIS spectrophotometry to multicomponent mixtures of active pharmaceutical ingredients, even when there is a significant overlap between their spectra, achieving simultaneous selective quantification without the need for prior separation, thus simplifying sample preparation and reducing waste generation, time and cost of analysis.
The aim of this work was to develop reliable and robust chemometric models coupled with UV–VIS spectrophotometry that will be applied in routine dissolution testing of combined tablet formulations of two analgesics: Ibuprofen and Paracetamol.
Two quantitative chemometric models: Principal component regression (PCR) and Partial least squares regression (PLS) were built in concentration range 40–140 % of the declared content for both components (corresponding to 2.22 — 7.78 µg/mL for Ibuprofen and 5.56 — 19.44 µg/mL for Paracetamol). After comprehensive assessment and validation, they proved to be precise (<2 % variability) and accurate (<2 % error) for prediction of new samples. Different sources of variability, not related with concentration differences between the samples, were incorporated into the calibration data in order to obtain stable models which wouldn’t be affected from expected variations during routine use.
The similarity between model-obtained results and the results from a reference HPLC procedure confirmed the capability of chemometrics to facilitate its replacement with a more sustainable alternative</p
Food Consumption in the Brussels Capital Region and the German speaking Community
No full textThis methodology report describes the procedures used to analyse food consumption and adherence
to food-based dietary guideline in the Brussels-Capital Region and the German-speaking Community,
based on data from the 2022-2023 Food Consumption Survey.
Food consumption in the additional sample of Brussels and the German-speaking Community was
assessed using a Food Frequency Questionnaire (FFQ), completed once by each participant (see
general Methodology report of the Belgian food consumption survey, Chapter 2.2.1 and Chapter
2.2.2.3.). The report outlines the steps taken to prepare the food consumption database, including the
coding of reported frequencies and portion sizes, data cleaning procedures, and the identification of
extreme values.
The final section describes the analytical approach used to derive indicators of food group intake and to
evaluate adherence to food-based dietary guidelines.</p
Towards consensus: The need for standardised definitions in Long (post) COVID care in 34 European countries.
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Lutter contre l'invisibilité des maladies rares grâce à la nomenclature Orphanet
No full textOn February 27, 2025, Annabelle Calomme (Orphanet Belgium, Sciensano) gave a presentation entitled “Fighting against the invisibility of rare diseases thanks to the Orphanet nomenclature” to approximately 80 physicians and healthcare professionals from the Cliniques Universitaires Saint-Luc (CUSL), one of the eight Belgian Rare Disease Functions. This presentation was given during the “Midis des Maladies Rares” (lunchtime conferences on rare diseases) organised each year by the CUSL Rare Diseases Institute as part of the activities organised for Rare Disease Day.
Her intervention focused mainly on the main challenges related to rare diseases, in particular diagnostic wandering, as well as the importance of making these diseases more visible in the hospital environment, through the use of ORPHAcodes. She presented the Rare Disease Knowledge (RDK™) tool co-developed by Orphanet and Tekkare, which generated a lot of interest among the participants.</p
Broadening Arsenic Speciation: Inclusion of Small Organoarsenic Species in Standard Food Testing Methods
No full textArsenic (As) is a naturally occurring element frequently found in various foodstuffs including rice and cereals, marine organisms, algae, root vegetables, and infant formulas. [1] Chronic exposure to As has been associated with several adverse health outcomes such as cancer, skin lesions, cardiovascular disease, diabetes, and cognitive development problems in children. [2] Inorganic arsenic (comprising arsenite As(III) and arsenate As(V)) is considered as one of the most toxic arsenic species and is categorized as non-threshold Class I carcinogen (IARC, 2012). To mitigate exposure, maximum allowable levels for inorganic arsenic have been established in cereals, infant formulae and baby foods under Commission Regulation (EU) 2023/915.
The recent EFSA risk assessment on small organoarsenic species (EFSA, 2024a [3]) highlighted no immediate health concerns for monomethylarsonic acid (MMA(V)), but raised potential concerns for dimethylarsinic acid (DMA(V)), recommending the development of robust and validated analytical methods to quantify specific organoarsenic species in food. The risk assessment for complex organoarsenic species (EFSA 2024b [4]) in food concluded that arsenobetaine and glycerol arsenosugar were not associated with health risks. However, insufficient data prevented conclusions on other arsenosugars and arsenolipids.
The prevailing European standard method for determining inorganic arsenic in food (EN 16802) encompasses the quantification of other arsenic species. In response, the EN method has been adapted to enable the simultaneous detection and quantification of key small organoarsenic species across diverse food matrices. The following foodstuffs are tested for the presence of the species concerned:
- edible insects, distinguished by their chitin content;
- grain products other than rice, due to their significant contribution to dietary inorganic arsenic exposure;
- novel plant-based protein sources such as lupins and beans;
- seafood, in light of potential regulatory limits on inorganic arsenic in crustaceans, bivalves, and cephalopods.
The analytical method comprises an extraction of the arsenic species contained in the matrix by heating in an acidic and oxidising medium. The species are separated using an anion-exchange column, followed by ICP-MS detection.
The present work supports ongoing regulatory and risk assessment efforts by providing improved analytical capacity for arsenic speciation in a broad range of food products.
1 EFSA ‘Scientific Opinion on Arsenic in Food’. EFSA Journal, no. 10 (2009).
2 https://www.who.int/news-room/fact-sheets/detail/arsenic
3 EFSA Panel on Contaminants in the Food, ‘Risk Assessment of Small Organoarsenic Species in Food’. EFSA Journal 22, no. 7 (2024).
4 EFSA Panel on Contaminants in the Food, ‘Risk Assessment of Complex Organoarsenic Species in Food’. EFSA Journal 22, no. 12 (2024).</p
