Through leveraging our combined computational and biological knowledge, we have proven expertise supporting clients in: (1) Evaluating and validating the potential for predictive modeling within your projects, (2) Developing and applying machine learning techniques and other AI-based

Last updated on: 11-03-2024 - 13:31

Contact: Cannot be disclosed
Organisation: BioLizard
Status: History of use, Internally validated, Validated by an external party (e.g. OECD, EURL ECVAM,…)
Through leveraging our combined computational and biological knowledge, we have proven expertise supporting clients in: (1) Developing and applying a range of statistical methods tailored to specific problem settings in both clinical and non-clinical datasets, (2) Integrating multi-omics

Last updated on: 11-03-2024 - 13:30

Contact: Cannot be disclosed
Organisation: BioLizard
Status: History of use, Internally validated, Published in peer reviewed journal, Validated by an external party (e.g. OECD, EURL ECVAM,…)
For the risk assessment of compounds migrating from food contact materials (FCM), information on the exposure to the migrant as well as its possible hazards is needed. To support the evaluation of both starting products and NIAS from plastic FCM, the VERMEER FCM tool has been developed within the

Last updated on: 29-11-2022 - 14:46

Organisation: Sciensano
Status: Internally validated
DARTpaths is an an integrative app to support the prioritisation of chemicals. The Open Source R shiny application allows for the prediction of compound-induced molecular mechanisms of action. The tool integrates phenotypic endpoints of different species induced by compounds and genetic variants, in

Last updated on: 13-06-2022 - 16:04

Contact: Vera van Noort
Organisation: Katholieke Universiteit Leuven (KUL)
Partners: Open Analytics, Hogeschool Utrecht , Vivaltes
Status: Internally validated
In silico tools are computer-assisted methodologies with a high-throughput that allow to predict the toxic potential of compounds without experimental testing. Consequently, in silico tools are time-, cost- and animal-saving in nature. The most commonly used methods are (quantitative) structure

Last updated on: 24-03-2022 - 11:25

Contact: Birgit Mertens
Organisation: Sciensano
Status: Published in peer reviewed journal
Quantitative Structure Activity Relationship modeling is generally used to construct models in which molecular descriptors of chemical compounds are used to predict endpoints/activities of interest. Commercial packages are available that can be implemented, but new models can be constructed if

Last updated on: 16-03-2022 - 13:49

Contact: Geert Verheyen
Organisation: Thomas More University of Applied Sciences
Status: Still in development, History of use, Published in peer reviewed journal
This is a mathematical compartmental formulation of dose-effect synergy modelling for multiple therapies in Non Small Cell Lung Cancer (NSCLC): antiangiogenic, immuno- and radiotherapy. The model formulates the dose-effect relationship in a unified context, with tumor proliferating rates and

Last updated on: 01-02-2021 - 14:32

Organisation: Ghent University (UGent)
Status: Published in peer reviewed journal
Performing biopredictive dissolution tests in in vitro models that are frequently used in pharmaceutical and academic institutions and using these in vitro dissolution data as input for PBPK models to predict the systemic exposure of the drug in humans/patients.

Last updated on: 08-04-2020 - 17:29

Contact: Bart Hens
Organisation: Katholieke Universiteit Leuven (KUL)
Status: Published in peer reviewed journal