Success of Autologous Chondrocyte Implantation (ACI) for treating damaged cartilage in the knee has been marginal and limited to young, healthy, and active patients. With the advent of second generation ACI referred to as Matrix-Assisted ACI (MACI), a new opportunity arises. We hypothesize that if the design of the matrix is patient-specific (i.e., specific to the tissue synthesis capabilities of the cell), it will be possible to not only improve the effectiveness of ACI long-term, but expand its indication to a wider patient population regardless of age or health. Thus, the overarching goal of this research project is to personalize MACI. Our innovative approach to personalizing MACI combines the following two highly interconnected themes: (a) A new class of highly tunable hydrogels with spatiotemporal control over degradation (to enable patient-matched tissue synthesis capabilities), high moduli capabilities (to restore function), and matrix-retention capabilities (to minimize tissue loss). (b) The introduction of a universal computational tool based on a well-established theoretical framework, which will analyze data related to the response of a patient-specific cell and, based on this information, predict the corresponding hydrogel structure and degradation that enables tissue growth and sustained mechanical integrity in a dynamic loading environment (such as that in the knee). To accomplish our overall research goals, the specific aims are as follows.
We aim to determine model constants that enable the design of personalized hydrogels, first in the absence of mechanical loading (Aim 1) then in the presence of mechanical loading (Aim 2). We will accomplish this through an integrated experimental and simulation campaign combined with the use of a self-learning algorithm. This will lead to the construction of the data- driven predictive computational model. Once developed, we will test the predictive capability of the mathematical model in personalized MACI using a large animal model, specifically to treat a chondral lesion in the knee of a swine (Aim 3). At the completion of this five year research project, we expect to have developed a predictive computational tool and established a novel and highly tunable hydrogel platform for personalizing MACI. The universal nature of the computational predictive tool enables it to be broadly applied in future research to other scaffolds and cells, including osteoarthritic chondrocytes and stem cells.
This research aims to develop a personalized approach to Matrix Assisted Autologous Chondrocyte Implantation by developing i) a new hydrogel platform with high modulus, spatiotemporal control over degradation and matrix retaining capabilities and ii) a computational tool that can predict the best hydrogel formulation that is specific to the patient. !
|Chu, Stanley; Sridhar, Shankar Lalitha; Akalp, Umut et al. (2017) * Understanding the Spatiotemporal Degradation Behavior of Aggrecanase-Sensitive Poly(ethylene glycol) Hydrogels for Use in Cartilage Tissue Engineering. Tissue Eng Part A 23:795-810|
|Brighenti, Roberto; Vernerey, Franck J (2017) A simple statistical approach to model the time-dependent response of polymers with reversible cross-links. Compos B Eng 115:257-265|
|Schneider, Margaret C; Barnes, Christopher A; Bryant, Stephanie J (2017) Characterization of the chondrocyte secretome in photoclickable poly(ethylene glycol) hydrogels. Biotechnol Bioeng 114:2096-2108|
|Lalitha Sridhar, Shankar; Schneider, Margaret C; Chu, Stanley et al. (2017) Heterogeneity is key to hydrogel-based cartilage tissue regeneration. Soft Matter 13:4841-4855|
|Akalp, Umut; Schnatwinkel, Carsten; Stoykovich, Mark P et al. (2017) Structural Modeling of Mechanosensitivity in Non-Muscle Cells: Multiscale Approach to Understand Cell Sensing. ACS Biomater Sci Eng 3:2934-2942|
|Shen, Tong; Vernerey, Franck (2017) Phoretic motion of soft vesicles and droplets: an XFEM/particle-based numerical solution. Comput Mech 60:143-161|
|Neumann, Alexander J; Quinn, Timothy; Bryant, Stephanie J (2016) Nondestructive evaluation of a new hydrolytically degradable and photo-clickable PEG hydrogel for cartilage tissue engineering. Acta Biomater 39:1-11|
|Akalp, Umut; Bryant, Stephanie J; Vernerey, Franck J (2016) Tuning tissue growth with scaffold degradation in enzyme-sensitive hydrogels: a mathematical model. Soft Matter 12:7505-20|
|Benet, Eduard; Vernerey, Franck J (2016) Mechanics and stability of vesicles and droplets in confined spaces. Phys Rev E 94:062613|
|Aisenbrey, E A; Bryant, S J (2016) Mechanical loading inhibits hypertrophy in chondrogenically differentiating hMSCs within a biomimetic hydrogel. J Mater Chem B 4:3562-3574|
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