Laurence is a researcher with an interdisciplinary background in Data Science, Artificial Intelligence, and Systems Biology. He earned his bachelor’s degree in Data Science and Artificial Intelligence and completed his master’s in Systems Biology and Bioinformatics, both at Maastricht University.

During his master’s thesis internship at MERLN, he developed a physiologically based pharmacokinetic (PBPK) model to study drug–toxin interactions in chronic kidney disease. By restructuring the model into a two-compartment framework and incorporating competitive inhibition mechanisms, he provided new mechanistic insights into how toxins such as indoxyl sulfate alter drug clearance. This work combined advanced computational modeling with a strong focus on biological realism, reflecting his interest in bridging data-driven methods with systems-level understanding of human health.

Currently, Laurence is pursuing his doctoral research as part of the ERC-funded AUTOMATHIC project at the MERLN Institute for Technology-Inspired Regenerative Medicine. His work focuses on automating ODE model construction and evaluation, with the broader aim of enabling faster, more reliable discovery of complex biological network dynamics.