Osteoarthritis is a debilitating and irreversible disease afflicting the synovial joints. It is characterized by pain and hindered mobility. Given that osteoarthritis has no cure, current treatments focus on pain management. Ultimately, however, a patient’s pain and immobility necessitates joint replacement surgery. An attractive alternative to this treatment paradigm, tissue engineering is a promising strategy for resurfacing the osteoarthritis-afflicted cartilage surface with a biochemically and biomechanically similar tissue to the healthy native cartilage tissue. The most successful cartilage tissue engineered systems to date can repeatably grow constructs ≈4 mm in diameter with native proteoglycan and compressive mechanical properties. Unfortunately, as symptomatic cartilage typically presents only once lesions span large regions of the joint (≈25 mm in diameter), these small construct are of limited use in clinical practice.

Numerous attempts to simply grow a construct large enough to span the size of an osteoarthritic lesion have shown that the growth of large engineered tissues develop heterogeneous properties, emphasizing the need for culture protocols to enhance tissue homogeneity and robustness. In particular, as nutrient limitations drive heterogeneous growth in engineered cartilage, developing strategies to improve nutrition throughout the construct are critical for clinical translation of the technology. To this end, our lab has successfully supplemented nutrient channels within large engineered cartilage constructs to improve the functional properties of developing tissue. However, it is unknown what the optimal nutrient channel spacing is for growing large cartilage constructs of anatomical scale. Additionally, the fundamental factors and mechanisms which drive tissue heterogeneity have not been implicated, making the results of channel-spacing optimizations difficult to translate across different systems.

Computational models of growth, faithful to the physics and biology of engineered tissue growth, may serve as an insightful and efficient tool for optimally designing culture protocols and construct geometries to ensure homogeneous matrix deposition. Such computational tools, however, are not presently available, owing to the unresolved mechanical and biological growth phenomena within developing engineered cartilage. This dissertation seeks to develop and implement computational models for predicting the biochemical and biomechanical growth of engineered tissues and apply these models to optimizing tissue culture strategies. These models are developed in two stages:​ 1) based on our recent characterization of the nutrient demands of engineered cartilage, models are developed to simulate the spatial biochemical deposition of matrix within tissue constructs and, subsequently, 2) based on models of biochemical matrix deposition we develop models for simulating the mechanical growth of tissue constructs.

To accomplish these tasks, we first develop models simulating glucose availability within large tissue constructs using system-specific modeling based on our recent characterization of the glucose demands of engineered cartilage. These models led to early insight that we had to enhance the supply of glucose within large tissue constructs to ensure maximal matrix synthesis throughout culture. Experimental validations confirmed that increasing glucose supply enhanced matrix deposition and growth in large tissue constructs.

However, even despite the increased glucose supply, increasing the size of constructs demonstrated that severe matrix heterogeneities were still present. Subsequent nutrient characterization led to the finding that TGF-β transport was significantly hindered within large tissue constructs. Incorporating the influence of glucose and TGF-β into the computational model growth kinetics. Using both nutrients, models recreated the heterogeneous matrix deposition evident in our earlier work and could account for the role of cell seeding density and construct geometry on tissue growth. The insights gathered from this modeling analysis led to important changes in our culture protocols:​ we could reduce the dose of TGF-β from 10 ng mL⁻¹ to 1 ng mL⁻¹ for constructs cultured with channels, saving considerable expense while still maintaining a high level of matrix synthesis throughout the construct.

In the presence of sufficient nutrition, we witnessed an unprecedented level of matrix deposition and physical growth of the constructs. In fact, by using developmentally physiologic cell seeding densities (120 million cells mL⁻¹) and providing adequate nutrition, constructs physically grew to 9-times their originally cast size. Despite such encouraging growth, tissue function properties plateaued at sub-physiologic levels. For insight into the connection between matrix deposition and tissue mechanics, we extended the computational growth models to consider the mechanisms underlying physical growth. Interestingly, we found that a large matrix synthesis mismatch between proteoglycans and collagen gave rise to the excessive tissue swelling. Computational models of this matrix synthesis mismatch predicted the high tissue swelling displayed experimentally only when a damage-able collagen fiber material was implemented. Together, the experimental and modeling evidence suggested a new mechanism of cartilage growth:​ the high proteoglycan deposition creates a swelling pressure within the nascent tissue which outcompetes the restraining force of newly deposited collagens;​ this rapid tissue swelling disrupts a functional collagen network from forming. Subsequent analysis suggested that the disruption of the collagen network prevented the formation of collagen crosslinks, stymieing the development of native functional properties.

Based on this insight into the mechanisms of cartilage growth, we developed a culture systems to improve tissue functional properties. Modeling analysis indicated two novel routes for improving tissue mechanics:​ either through 1) reducing the swelling response (synthesis and deposition) of proteoglycans or 2) enhancing and reinforcing the newly synthesized collagen to prevent disruptions brought on by tissue swelling. We developed a cage culture system for resisting the swelling pressure of deposited proteoglycans and reenforcing the deposition of new collagens. Using this cage system, we grew tissue constructs with enhanced functional properties using two separate scaffold systems – agarose and a cartilage-derived matrix hydrogel – suggesting this mechanism of growth is fundamental to engineered cartilage development.

This work has generated a novel paradigm towards engineering cartilage constructs using biomimetic strategies. Performing simulations with the validated, computational growth models allowed anatomically-sized cartilage constructs to grow into the largest, homogeneous cartilage constructs grown to date. Models presented a new level of insight into the nutrient demands of developing tissues, allowing for the first time the successful development of large tissue constructs grown with developmentally physiologic cell seeding densities. In this way, tissue constructs growth followed a biomimetic approach, based on the high cell densities and cartilage canals and vasculature present during fetal cartilage development. Adequate nutrition led to high levels of tissue growth not previously experienced in vitro, a result of adequately nourishing primary chondrocytes, a cell type which preferentially deposits proteoglycans over collagen. We therefore developed a cage-based growth system to resist the proteoglycan-induced tissue swelling in a manner similar to the fetal development of cartilage where the resident cells synthesize more collagens than proteoglycans. Together, the use of nutrient growth models, high cell seeding densities, and culture systems to strengthen the collagen-framework of de novo cartilage proved beneficial for engineering anatomically-sized cartilage constructs. The fundamental mechanisms identified here are likely to be universal across a number of engineered cartilage systems and will be adapted to more clinicallyrelevant cell sources in future our work.