Tissue Engineering

In the context of tissue engineering, the ATOMS Lab is pursuing ground-breaking work in the production of airway and cardiac tissues. Our research foci and specific projects, detailed below, are informed by our close collaboration with Dr. Thomas Waddell and Dr. Shaf Keshavjee, Latner Thoracic Research Laboratories, and Dr. Michael Laflamme, McEwen Stem Cell Institute, University Health Network.

The mechanical, biological and chemical environments play a critical role in the successful development of tissues, and several research groups are working towards developing devices and experimental protocols to characterize, predict and control these environments. However, the pace of progress is hindered by the costly, time-consuming nature of the required in vitro, ex vivo and in vivo experiments. Computer simulations, referred to as in silico experiments in the bioengineering and biomedical literature, have been identified as key for accelerated discovery across many bioengineering/biomedical domains. Yet, a comprehensive, experimentally validated modelling/simulation methodology, accounting for how the most important cell biology behaviours (deposition, attachment, expansion, differentiation, death) are modulated by the mechano-bio-chemical environment, is still unavailable.

Our main research trust in this area is the development and experimental validation of efficient computer simulation models for cell deposition, attachment, proliferation and differentiation in both perfusion-based and static in vitro processes. We have developed a comprehensive methodology to formulate, select, calibrate, validate and analyze these in silico models (figure below). These simulation models combine traditional Computational Fluid Dynamics (CFD) methods for advection-diffusion-reaction systems, as well as cell population models based on system of ordinary differential equations. Using these models, we can inform the design of bioreactors for decellularization and recellularization of tissue scaffolds, and for de novo production of cells, micro-tissues, organoids and artificial organs. Furthermore, since our models consider both mechanical and biochemical cues and their effect on cell population, we can leverage these models to optimize the associated experimental protocols (e.g., frequency of media replenishment, required mixing levels) to maximize cell yield, minimize production costs, and minimize variability.