Projects
Statistical methods for the estimation of age- and time-dependent epidemiological malaria parameters and the analysis of social network data as a novel approach to design malaria elimination strategies. University of Antwerp
Survival of coronaviruses in aquatic environment Flanders Marine Institute
Avoiding a local wildlife reservoir of SARS‐CoV‐2 in Belgium. University of Antwerp
Characterization of a contemporary Respiratory Syncytial Virus isolate for use in pre-clinical and clinical research (ReSVistrain). University of Antwerp
Enabling antibody prophylaxis of the elderly and vulnerable using yeast-based biotechnology. Ghent University
Vaccines against respiratory viral infections are likely to lack full efficacy in the most vulnerable aged population group. In this project we develop a yeast-based, cost-effective and highly scalable prototyping-and manufacturing technology for highly potent virus-neutralizing VHH-Fc anitbodies with
engineered prolonged halflife. Such passive immunization strategy complements vaccination-based approaches during peak periods of ...
Single domain antibodies that neutralize SARS-CoV-2 Ghent University
The aim of this project is to isolate single domain antibodies that are directed against the receptor-binding domain that is part of the spike protein of SARS-CoV-2. Those single-domain antibodies, separately and combined, will be evaluated for their capacity to neutralize SARS-CoV-2.
Development of fast assays for the identification of SARS-CoV-2-infected/immune humans/animals and potential human-animal-human transmissions Ghent University
SARS-CoV-2 is causing a pandemic in humans. Transmission towards animals is experimentally demonstrated but in the field animal infections are rare. With the proposed project, assays will be developed to diagnose Covid-19 in humans/animals and to assess their immune status. In addition, reverse zoonotic and zoonotic aspects will be examined in vitro.
Investigation of the interaction between the Leishmania dynamin-1 like protein and compound X, a promising lead for the development of novel antileishmanial drugs. University of Antwerp
Identification of adaptive mechanisms leading to reduced antibiotic susceptibility in bacterial biofilms using experimental evolution and machine learning approaches Ghent University
Because many mechanisms of reduced sensitivity in bacterial biofilms are still unknown, it is impossible to predict resistance. In this project we will allow bacteria to evolve in vitro in the presence of antibiotics, in order to map all mutations, differences in gene expression and relevant phenotypic characteristics. This will allow to develop a prediction algorithm using machine learning.