We developed a biventricular statistical shape model (SSM) from high-resolution cardiac CT scans from 271 healthy individuals. Leveraging the diversity captured by our biventricular SSM, we created a synthetic cohort of anatomically detailed, high-resolution, biventricular meshes. The geometries in
Last updated on: 16-07-2025 - 10:01
Contact: Lore Van Santvliet
Organisation: Katholieke Universiteit Leuven (KUL)
Status: Published in peer reviewed journal
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: 27-06-2025 - 09:57
Identifying drug-target interactions is a crucial step in drug repositioning, the process of suggesting new indications for known drugs. There are about 9000 FDA-approved and experimental small molecule drugs and more than 500.000 protein records available. Performing in vitro experiments would be
Last updated on: 28-01-2025 - 16:41
Contact: Daniele Parisi
Organisation: Katholieke Universiteit Leuven (KUL)
Partners: Biotech/TU-Dresden, Max-Planck-Institut für Informatik Saarbrucken
Status: Still in development
Digital twins of the cardiovascular and pulmonary systems, allowing the virtual simulation of various invasive or non-invasive measurements (cardiac output, ballistocardiography signal, blood pressure, pulse wave velocity, FeNO, DLNO, FEV1, etc.) on healthy or pathological subjects, of variable size
Last updated on: 24-04-2024 - 12:16
Contact: Benoit Haut
Organisation: Université Libre de Bruxelles (ULB)
Status: History of use, Internally validated, Published in peer reviewed journal
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,…)
Drug-induced intrahepatic cholestasis (DIC) is a main type of hepatic toxicity that is challenging to predict in early drug development stages. Preclinical animal studies often fail to detect DIC in humans. In vitro toxicogenomics assays using human liver cells have become a practical approach to
Last updated on: 15-02-2024 - 11:59
Contact: Cannot be disclosed
Organisation: Vrije Universiteit Brussel (VUB)
Status: Internally validated, Published in peer reviewed journal
Severely burned skin can exhibit serious contractions that may negatively impact the mobility of joints of patients. The method deals with post-burn evolution of skin, in which one considers the balance of momentum, cells, collagen and chemokines. The balances are represented in terms of partial
Last updated on: 05-09-2023 - 11:43
Contact: Fred Vermolen
Organisation: University of Hasselt (UHasselt)
Status: Still in development, Internally validated, Published in peer reviewed journal
NMTox is an R-software package and a Shiny app that can be used to explore and subset large datasets and can identify and test for monotonic dose responses. The package was developed within the NanoInformaTIX project where a platform is developed that aims to predict nanomaterial toxicity.
Last updated on: 22-08-2023 - 10:43
Contact: Geert Verheyen
Organisation: Thomas More University of Applied Sciences, University of Hasselt (UHasselt)
Status: Internally validated
An empirical model linking physico-chemical biomaterial characteristics to intra-oral bone formation
This empirical model is used to assess the weighted value of driving biomaterials properties in the intra-oral bone regeneration process. We used partial least square regression (PLSR) to construct empirical models that relate combinations of (quantified) biomaterial characteristics to intra-oral
Last updated on: 08-06-2023 - 14:26
Contact: Ehsan Sadeghian
Organisation: University of Liège (ULiège)
Partners: Katholieke Universiteit Leuven (KUL), University of Liège (ULiège), Université Catholique de Louvain (UCL)
Status: Internally validated
