How to Optimize Maturation in a Bioreactor for Vascular Tissue Engineering: Focus on a Decision Algorithm for Experimental Planning

Mon article "How to Optimize Maturation in a Bioreactor for Vascular Tissue Engineering: Focus on a Decision Algorithm for Experimental Planning" a été accepté dans la revue Annals of Biomedical Engineering. Vous pouvez le télécharger à cette adresse si vous êtes abonnés, par exemple via votre université ou bibliothèque ou ici sur pubmed.

Voici le résumé de l'article :

"Bioreactors may become essential tools for developing tissue-engineered organs from cells, with or without scaffolds. Cells seeded in these devices are expected to grow and form a tissue. Up to now, one of the main challenges to successfully develop functional organs is the structural organization of the cells into the scaffold during maturation in the bioreactor. The maturation step is affected by a set of highly interlinked dynamical variables (flow, stress, pH, temperature, and growth factors) in such a way that fixing the optimal environmental conditions becomes very complex. This work focuses on how the experimental parameters in the bioreactor can be optimized through numerical modeling to maximize tissue growth. Genetic programming (GP) and Markov decision processes (MDPs) were used in synergy to generate and take full advantage of a model of the vascular construct growth. The approach consists in formulating a model through GP to explain the growth of the construct and using MDPs to come up with a strategy to yield the best results in the experimental runs. Construct growth was improved, and the regeneration process was better understood in numerical simulations that relied on this control system. Therefore, an advanced numerical controller of this type could become an effective and inexpensive tool for planning experimental work in tissue engineering."

Essentiellement, je montre que l'on peut calculer les meilleures conditions de culture dans un bioréacteur pour le génie tissulaire en utilisant quelques méthodes mathématiques (1) pour planifier les expériences afin d'étudier le système et (2) prendre des décisions séquentielles concernant les conditions de culture. Ce que cela apporte à mon domaine, c'est l'idée de calculer mathématiquement plutôt que de poser arbitrairement les paramètres pour faire grandir les tissus en laboratoire. Finalement, je montre par des simulations numériques qu'en utilisant cette approche on obtient bel et bien une croissance plus rapide.

Publié par : Frédéric Couet