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Biomaterials

Biomaterials - Poster Session A

Poster B8 - Agent-Based Model for Optimizing Vascularized Spheroid Culture in Granular Hydrogel Scaffold

Thursday, October 24, 2024
10:00 AM – 11:00 AM EST
Location: Exhibit Hall E, F & G

Introduction:  Biomaterial design traditionally necessitates time-consuming and expensive experimentation to optimize various material compositions, porosities, degradation rates, and mechanical properties. As synthetic biomaterials become increasingly complex in their structure and biomedical applications, there is a pressing need for innovative computational modeling tools that guide optimization. Granular hydrogels, comprised of packed microparticles, exemplify the complexities of next-generation biomaterials. These hydrogels are being evaluated for their capacity to induce and support vascularization; however, they pose additional complexity when designing them for specific biomedical applications. We propose the use of a comprehensive, material-informed Agent-Based Model (ABM) to optimize granular hydrogel constructs for vascularized spheroid culture.

Agent-based modeling provides a powerful methodology for simulating multi-cell interactions at the tissue scale through literature-defined rules and user-defined assumptions. ABMs are commonly used to model complex biological processes such as angiogenesis, lung fibrosis, cancer metastasis, and muscle regeneration[1]. Despite their extensive deployment in biomedical applications, the potential of ABMs as a tool to inform biomaterials design and fabrication remains largely unexplored[2], [3].

In this study, we present a novel ABM for designing granular hydrogels for vascularized spheroid culture. Specifically, our ABM simulates a porous granular hydrogel scaffold that promotes cellular infiltration. We simulate this hydrogel in NetLogo (version 6.4.0) and quantify how variations in granular hydrogel composition and degradability influence endothelial cell infiltration from a centrally-implanted spheroid[4].

Materials and

Methods:  Our ABM simulated each cell and granular hydrogel particle as an agent and represented a total area of 314mm2. Cell agents included endothelial tip cells and stalk cells. Granular hydrogel agents consisted of a mixture with defined ratios of gelatin particles and norbornene-modified hyaluronic acid (norHA) particles. Gelatin particles served as a sacrificial particle to enhance porosity, and the ratio of gelatin to norHA particles was adjusted to control pore size and density. A representative image of a biological spheroid embedded within a porous granular hydrogel after 4 days is shown in Figure 1A. ABM simulations replicating sprouting from the spheroid are displayed in Figure 1B.

Simulated cell behaviors were dictated by literature-derived rules. For example, endothelial tip cells infiltrated the scaffold in the direction of increasing growth factor concentration, and stalk cells could become tip cells in response to increasing growth factor concentration[2]. To simulate porosity, the concentrations of gelatin and norHA particles were adjusted by creating models with 25%, 50%, and 75% norHA scaffolds. Porosity was assumed to be inversely proportional to norHA concentration. To simulate different degrees of particle degradation, the concentration of degradable norHA particles was simulated at concentrations of 25%, 50%, and 75%. Nine total trials were conducted testing the respective degradability concentrations for each scaffold. Final vessel densities were quantified with ten replicates. Branch points and mean vessel tortuosity were quantified from three replicate simulations of 0% degradable norHA using REAVER, an open-source software developed by our team to quantify angiogenic vessel network morphologies[5].

Results, Conclusions, and Discussions: In trials with 0% degradable particles, our model predicted that lower percentages of norHA particles supported increased vessel density. More porous scaffolds facilitated the formation of longer, more complex angiogenic networks. There was a non-linear relationship between porosity, branchpoints, and mean tortuosity. The number of branch points dramatically decreased from the 25% norHA scaffold to the 50% scaffold, and only slightly decreased between the 50% norHA scaffold and the 75% scaffold. Interestingly, mean tortuosity increased in the 50% norHA scaffold compared to the 0% scaffold (Table 1).

Additionally, increased degradation was associated with elevated vessel densities in the 25% and 50% norHA scaffolds (Figure 1B, C). In the 75% norHA scaffold, vessel density decreased when 25% of particles were degradable (Figure 1B, C), but increased otherwise. A consistent result across simulations was that increased degradability increased capillary network complexity and length, and there was a non-linear relationship between degradability and vessel density. As norHA particle percentages increased, the number of degradable particles became a less significant determinant of vessel density (Figure 1B, C). However, all simulations with 75% degradable particles had the highest vessel density for their respective norHA compositions. These results suggest there may be an optimal porosity-dependent concentration of degradable particles to maximize angiogenic network formation.

Our results confirm that ABMs can be used as a predictive tool for designing and optimizing biomaterials for spheroid culture. We show how ABMs can model different material compositions, porosities, and degradation and how these parameters affect in vitro vasculature. REAVER quantified micro-architectures of computationally-derived angiogenic network and confirmed porosity as a key determinant of network patterning and explored the impact of degradability on vessel infiltration. Our ABM also analyzed previously untested granular hydrogel designs more quickly and in a more cost-effective way than exhaustive laboratory experimentation. Future work will explore wider variations in porosity, degradability, and other material properties of granular hydrogels, such as stiffness and bulk modulus. By pairing computational and in vitro models, hydrogel designs can be more efficiently optimized for regenerative medicine and tissue engineering purposes, and future work will explore this combined approach for in vivo applications.

Acknowledgements (Optional):  Harrison Undergraduate Research Award, and NIH R01 HL155143 and NIH R01 GM140008 to S.M.P.

References
[1]   H. Mehdizadeh, A. Artel, E. M. Brey, and A. Cinar, “Multi-Agent Systems for Biomedical Simulation: Modeling Vascularization of Porous Scaffolds,” in Agents in principle, agents in practice, vol. 7047, D. Kinny, J. Y. Hsu, G. Governatori, and A. K. Ghose, Eds. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011, pp. 113–128.
[2]   L. J. Pruett, A. L. Taing, N. S. Singh, S. M. Peirce, and D. R. Griffin, “In silico optimization of heparin microislands in microporous annealed particle hydrogel for endothelial cell migration.,” Acta Biomater., vol. 148, pp. 171–180, Aug. 2022, doi: 10.1016/j.actbio.2022.05.049.
[3]   H. Mehdizadeh, S. Sumo, E. S. Bayrak, E. M. Brey, and A. Cinar, “Three-dimensional modeling of angiogenesis in porous biomaterial scaffolds.,” Biomaterials, vol. 34, no. 12, pp. 2875–2887, Apr. 2013, doi: 10.1016/j.biomaterials.2012.12.047.
[4]   “NetLogo.” https://ccl.northwestern.edu/netlogo-ccl.shtml (accessed Jul. 05, 2024).
[5]   B. A. Corliss, R. W. Doty, C. Mathews, P. A. Yates, T. Zhang, and S. M. Peirce, “REAVER: A program for improved analysis of high-resolution vascular network images.,” Microcirculation, vol. 27, no. 5, p. e12618, Jul. 2020, doi: 10.1111/micc.12618.