ZeptoWard is a Machine Learning solution (AI) which identifies the ADMET properties of compounds. It can accurately predict over 80 properties related to absorption, distribution, metabolism, excretion, and toxicity properties, how a specific compound or combination of compounds will perform. It can

Last updated on: 29-08-2022 - 10:03

Contact: Segolene Martin
Organisation: Kantify
Status: Published in peer reviewed journal
ZeptoHit is a technology based on Artificial Intelligence (AI) which accelerates hit discovery. With only a protein sequence as information, ZeptoHit can quickly and efficiently recommend promising hits, without any limitations. Its search for promising compounds goes much beyond chemical structures

Last updated on: 29-08-2022 - 09:57

Contact: Segolene Martin
Organisation: Kantify
Status: Internally validated, Published in peer reviewed journal
An artificial dog with real skeleton to excercise positioning for radiographic examination and palpation.

Last updated on: 25-07-2022 - 09:53

Organisation: Ghent University (UGent)
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
Prototyping and replication (small series production) of microfluidic or optofluidic devices, in thermoplastic polymers or in glass. 3D nanoprinting is also available to produce microscaffolds, possibly within microfluidic channels.

Last updated on: 16-03-2022 - 14:25

Contact: Jürgen Van Erps
Organisation: Vrije Universiteit Brussel (VUB)
Status: Internally validated, 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
We developed a cellular automata model of oncolytic virotherapy with an application to pancreatic cancer. The fundamental biomedical processes (like cell proliferation, mutation, apoptosis) are modelled by the use of probabilistic principles. The migration of injected viruses (as therapy) is

Last updated on: 07-01-2021 - 21:34

Contact: Fred Vermolen
Organisation: University of Hasselt (UHasselt), Delft University of Technology
Partners: Delft University of Technology, Technion
Status: Published in peer reviewed journal
Computational Fluid Dynamics (CFD) is being applied to characterize the fluid flow in different applications. CFD has obtained significant interest in both the medical and engineering community because of its non-invasive character. It can predict the fluid flow characteristics when one or multiple

Last updated on: 10-04-2020 - 09:22

Organisation: Ghent University (UGent)
Status: Still in development, Published in peer reviewed journal