As basic science advances, one of the major challenges in Tissue Engineering is the translation of the increasing biological knowledge on complex cell and tissue behavior into a predictive and robust engineering process. Mastering this complexity is an essential step towards clinical applications of TE. Computational modeling allows to study the biological complexity in a more integrative and quantitative way. Specifically, in silico and in vitro tools such as those developed in our group can help in quantifying and optimizing the TE product and process but also in assessing the influence of the in vivo environment on the behavior of the TE products after implantation.
We develop computational models related to all aspects of the TE product development cycle: cells, carriers, culture conditions and clinics. Depending on the specific question that needs to be answered, the optimal model systems can vary from a single length/time scale to a multiscale approach. Furthermore, depending on the available information, model systems can be purely data-driven or more hypothesis-driven in nature. Recently, we have started to apply these same tools to study the process of lymphangiogenesis in the context of tumor development and treatment.
To bring the above discussed models to the clinics and/or the market, various collaborations have been set up with clinicians and companies, in Belgium and Europe. An important boundary condition to this translation is the acceptance of the use of in silico tools in biomedical research and in (pre)clinical dossiers presented to EMA and FDA. Through our involvement in the Virtual Physiological Human institute and the Avicenna Alliance, we are involved in interactions with a variety of stakeholders, including the European Council and Parliament, the USA-FDA and EMA to establish proper regulation and harmonized guidelines for the inclusion of digital evidence obtained from computer modeling is admissible in the context of product development and regulatory approval.
Overview presentations of our work: