3D Bio-Based mRNA-Enriched Materials for Bone Regeneration: Optimizing Osteogenic Differentiation Using AI-Based Methods

This PhD project aims to develop bioresorbable scaffolds functionalized with mRNA using a polycation, poly(L-lysine), and hyaluronic acid, arranged in different structural architectures.
The originality of this approach lies in two key aspects. First, these biomaterials will incorporate mRNA sequences encapsulated within nanoparticles, encoding proteins that play a crucial role in bone regeneration, such as VEGF (Vascular Endothelial Growth Factor) and BMP (Bone Morphogenetic Proteins). Second, the project will investigate how the three-dimensional organization of the polymer network influences the biological performance of the scaffold.
The overall objective is to transform cells located at the injury site into localized therapeutic protein factories through in situ transfection, enabling sustained, localized production of the therapeutic proteins at physiological concentrations.
Artificial intelligence (AI) approaches will be used as computer-aided design tools to analyze and exploit the experimental data. These methods will guide the optimization of scaffold design—including composition, architecture, and mRNA loading—to maximize osteogenic differentiation while reducing the number of experimental iterations required.
This work is part of an interdisciplinary and collaborative research project. The PhD candidate will also contribute to data analysis, the writing of scientific publications, and the dissemination of research findings at national and international conferences.