(52b) Predicting Enzymatic Degradation of Silk Scaffolds through Reaction-Diffusion Analytical Modeling
- Conference: AIChE Annual Meeting
- Year: 2020
- Proceeding: 2020 Virtual AIChE Annual Meeting
- Group: Materials Engineering and Sciences Division
- Time: Monday, November 16, 2020 - 8:15am-8:30am
To achieve the first steps in this process, degradation rates of silk materials were measured in vitro using common protein-degrading enzymes such as Proteinase K and Protease XIV. The concentration of the enzyme in solution was varied (1 U/mL, 0.1 U/mL) along with one silk sponge formulation parameter: the level of crystallinity within the samples (6 vs. 12 hours of water annealing). We held the silk concentration, polymer chain length and scaffold pore size constant as an initial set of experimental data for model development and validation. Preliminary experimental results suggest the enzyme itself and enzyme concentration within the system are the major components dictating silk sponge degradation. To build a model represent our data and enable future predictions of intermediate parameter values, a partial differential equation including reaction terms to account for the breakdown of the silk protein and diffusion terms to account for the diffusion of the silk protein peptides into the bulk enzyme solution was developed. Currently, the partial differential model uses a modified Michaelis-Menten term to approximate silk peptide generation due to enzymatic degradation of the silk sponge and diffusion of the generated silk peptides or âsilk bitsâ in a spherical geometry to obtain enzyme effects on the biodegradation of silk in biological media. The model was solved analytically to provide information about the relevant variables and parametric functions that relate material mass loss, time, and enzyme composition. We assumed, in our in vitro experiments, that enzyme diffusion into the bulk of the scaffold was negligible and therefore enzyme concentration was uniform throughout the scaffold system. We recognize that in vivo, this assumption will not hold and future experiments and alterations to the model will be needed. However, the next step in this process is to determine how and if experimental parameters such as enzyme concentration, enzyme activity, and scaffold formulation variables can be incorporated into the constants in the mathematical model. Future work will look at understanding how the constants in these terms relate to the acquired experimental data to determine the influence of silk sponge formation variables on the resulting degradation fits. These results will guide biomaterial design to achieve semi-predicable biomaterial performance for the large array of tissue engineering applications a priori, leading to better clinical outcomes following implantation.
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