Personalized medicine can be achieved through the use of state-of-the-art and high-performance analytical techniques together with advanced computational methods.
Clinical metabolomics typically involves large-cohort studies with multiple patient samples or in-vitro/ex-vivo cellular models. High-quality data can only be gathered only by using cutting-edge and standardized analytical approaches. This will allow for the pinpointing of metabolic differences and the deciphering of novel biomolecular pathways or biomarkers candidates.
Our research focuses on the development of high-performance metabolomics platforms aiming for high-throughput analysis and large metabolite coverage. This will provide the most complete information on the metabolome in less time and with less costs. We are implementing standardized analytical workflows for the analysis of 3D cell culture models, enabling for highly-sensitive analysis of volume-limited samples and that aim to extract the intracellular and extracellular metabolic information from the smallest amount of cells.
Our ambition is to use these state-of-the-art and standardized technologies to unravel the biomolecular mechanisms involved in major diseases, notably cardiovascular diseases and neurological disorders. Using systems pharmacology-based approaches, we not only aim for a better diagnosis of such diseases, but also an individual prediction of the physiological response to a specific treatment.
- Development of Comprehensive and High-throughput metabolomics techniques
- Highly sensitive analysis using 3D cell culture model
- Clinical applications of (pharmaco)metabolomics