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Modeling the Dynamic Composition of Engineered Cartilage

Experimental studies indicate that culturing chondrocytes on biodegradable polymeric scaffolds may yield“engineered" cartilage for the replacement of tissue lost to injury or diseases such as osteoarthritis. A method of estimating the outcome of cell-polymer cultures would aid in the design and evaluation of engineered tissue for therapeutic use. The goals of this project were to develop, validate, and apply first-generation mathematical models that describe the kinetics of extracellular matrix (ECM) deposition and scaffold degradation in cell-polymer constructs cultured in vitro. The ECM deposition model is based on a product-inhibition mechanism and predicts an asymptotic, exponential increase in the concentration of ECM molecules found in cartilage, including collagen and glycosaminoglycans (GAG). The scaffold degradation model uses first-order kinetics to describe the hydrolysis of biodegradable polyesters in systems not limited by diffusion. Each model was fit to published data describing the accumulation of GAG and collagen, as well as the degradation of poly glycolic acid (PGA) and poly lactic acid (PLA), respectively. As experimental validation, cell-polymer constructs (n = 24) and unseeded scaffolds (n = 24) were cultured in vitro, and biochemical assays for GAG and collagen content, as well as scaffold mass measurements, were performed at 1, 2, 4, 6, 8, or 10 weeks of culture (n = 8 per time point). The mathematical models demonstrate a moderate to strong goodness of fit with the previously published data and our experimental results (R2=0.75-0.99). These models were also combined to predict the temporal evolution of total construct mass with reasonable accuracy (30% RMS deviation). In ongoing work, estimates of biochemical composition derived from these models are being proposed to predict the mechanical properties and functionality of the constructs. This modeling scheme may be useful in elucidating more specific mechanisms governing ECM accumulation. Given their potential predictive power, these models may also reduce the cost of performing long-term culture experiments.

Identiferoai:union.ndltd.org:wpi.edu/oai:digitalcommons.wpi.edu:etd-theses-1181
Date26 March 2002
CreatorsWilson, Christopher G
ContributorsLawrence J. Bonassar, Advisor, Jill Rulfs, Committee Member, Christopher H. Sotak, Committee Member, Sean S. Kohles, Advisor
PublisherDigital WPI
Source SetsWorcester Polytechnic Institute
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceMasters Theses (All Theses, All Years)

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