Optimizing Soluble Cues for Salivary Gland Tissue Mimetics Using a Design of Experiments (DoE) Approach

Abstract

The development of therapies to prevent or treat salivary gland dysfunction has been limited by a lack of functional in vitro models. Specifically, critical markers of salivary gland secretory phenotype downregulate rapidly ex vivo. Here, we utilize a salivary gland tissue chip model to conduct a design of experiments (DoE) approach to test combinations of seven soluble cues that were previously shown to maintain or improve salivary gland cell function. This approach uses statistical techniques to improve efficiency and accuracy of combinations of factors. The DoE-designed culture conditions improve markers of salivary gland function. Data show that the EGFR inhibitor, EKI-785, maintains relative mRNA expression of Mist1, a key acinar cell transcription factor, while FGF10 and neurturin promote mRNA expression of Aqp5 and Tmem16a, channel proteins involved in secretion. Mist1 mRNA expression correlates with increased secretory function, including calcium signaling and mucin (PAS-AB) staining. Overall, this study demonstrates that media conditions can be efficiently optimized to support secretory function in vitro using a DoE approach.

Optimizing phenol-modified hyaluronic acid for designing shape-maintaining biofabricated hydrogel scaffolds in soft tissue engineering

“…Light-mediated crosslinking of HA-Tyr and GelMA further increased crosslinking density (1.1 mol/m3) and formed strong covalent bonds, resulting in a stable hydrogel with high structural integrity. A contractual gel to liquid transitionflow point understood as loss of the structural integrity of the material (as the viscus behavior starts to dominate over the elastic one), and the start of flow can be observed from shear strain tests, which characterize the material's response to a specific deformation under shear stress [16,17]. In our study, we used shear strain tests to investigate the material's behavior under shear stress and found that the flow point is shifted when crosslinking steps are applied, making the material less prone to integrity loss, and inducing flow at higher shear stress values.…”

“…DoE can facilitate the efficient development of biomaterial formulations for 3D printing through systematic manipulation of variables [16] to enhance efficiency and improve prediction of outcomes. DoE allows multiple factors to be varied simultaneously, significantly reducing the number of experiment while still permitting analysis of the parameters of individual effects to be separated using statistical analysis revealing the key dependencies of different variables for particular responses [16][17][18]. Despite numerous advantages, DoE was rarely applied to optimize ink formulation for 3D printing [16,19,20].…”