IRF: Institutional Repository FHNW
Welcome to the publication and research database of the FHNW University of Applied Sciences and Arts Northwestern Switzerland.
The institutional repository contains publications, projects and student theses.
Further information can be found in the IRF manual (available in German).
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Recently added
Synthetic spectral libraries for Raman model calibration
(Springer, 08.07.2025) Hellequin, Louis; Borras, Vicent; Romann, Patrick; Vishwanathan, Nandita; Souquet, Jonathan; Villiger, Thomas
Raman spectroscopy has become increasingly popular in the process analytical technology (PAT) landscape due to its versatility and predictive capability in bioprocesses. However, model building remains a time-consuming and cost-intensive task. Building upon a fast calibration workflow based on physical pure compounds spiking in water, this work explores the novel use of in silico spiking of pure spectral fingerprints of various analytes. Through data fusion, a synthetic spectral library (SSL) is created that combines base spectra information from mammalian cell culture runs with matrix variability, as well as pure component spectra in water, aiming to greatly reduce the cost and time required for efficient model building. The findings indicate that the in silico addition of pure compounds provides spectral information comparable to physically spiked measurements. Consequently, this approach allows for the generation of an extensive number of information-rich spectra, forming a robust foundation for various regression algorithms and enhancing Raman calibration of existing spectral databases.
01A - Journal article
The quest for novel cancer biomarkers and drug targets in the alternative splicing landscape
(Schweizerische Chemische Gesellschaft, 25.06.2025) Kahraman, Abdullah
01A - Journal article
Ranking of apparent drug affinity to mesoporous silica utilizing a chromatographic screening method and a tree-based prediction model
(Elsevier, 15.09.2025) Niederquell, Andreas; Vraníková, Barbora; Kuentz, Martin
Mesoporous silica has emerged as a promising component in bio-enabling formulation strategy. However, there is currently a lack of predictive tools for assessing drug-silica interactions in a preformulation phase, when formulators only have minimal material to guide them. This study proposes a solution: a chromatographic method to rank apparent drug-silica affinity for mesoporous formulations. Using a dataset of 52 drugs, a hydrophilic liquid interaction chromatography (HILIC) screening method was developed, with a stationary silica phase to simulate the drug carrier. Molecular descriptors were calculated for various compounds to analyze HILIC retention times using a tree-based machine learning algorithm. For silica affinity, the distribution coefficient (LogD), the molecular shape descriptor Kappa1, and the number of conjugated bonds (NCB) were identified as possible critical parameters. Additionally, an amine-modified HILIC column was evaluated to simulate a surface-modified silica carrier. The classification tree analysis revealed that Abraham's hydrogen bonding acidity, the NCB and the pKa were determinants for a qualitative assessment of drug affinity to the modified silica. The classification into low, moderate, and high affinity to the stationary phase appeared to be useful in understanding drug release from mesoporous silica formulations, highlighting its potential for future research.
01A - Journal article
Vom Aneignungshandeln zum Schreiben von unsichtbaren Bewältigungskarten – aktueller sozialräumlicher Fokus in der Kinder- und Jugendarbeit
(Ernst Reinhardt, 2002) Reutlinger, Christian
01A - Journal article