A Rapid Screening Platform for Simultaneous Evaluation of Biodegradation and Therapeutic Release of an Ocular Hydrogel

Abstract

This study attempts to address the challenge of accurately measuring the degradation of biodegradable hydrogels, which are frequently employed in drug delivery for controlled and sustained release. The traditional method utilizes a mass-loss approach, which is cumbersome and time consuming. The aim of this study was to develop an innovative screening platform using a millifluidic device coupled with automated image analysis to measure the degradation of Gelatin methacrylate (GelMA) and the subsequent release of an entrapped wetting agent, polyvinyl alcohol (PVA). Gel samples were placed within circular wells on a custom millifluidic chip and stained with a red dye for enhanced visualization. A camera module captured time-lapse images of the gels throughout their degradation. An image-analysis algorithm was used to translate the image data into degradation rates. Simultaneously, the eluate from the chip was collected to quantify the amount of GelMA degraded and PVA released at various time points. The visual method was validated by comparing it with the mass-loss approach (R = 0.91), as well as the amount of GelMA eluted (R = 0.97). The degradation of the GelMA gels was also facilitated with matrix metalloproteinases 9. Notably, as the gels degraded, there was an increase in the amount of PVA released. Overall, these results support the use of the screening platform to assess hydrogel degradation and the subsequent release of entrapped therapeutic compounds.

Keywords: biodegradation; hydrogels; image analysis; millifluidics; ocular drug delivery.

Figure 1

Setup of the millifluidic system for analyzing the biodegradation of GelMA hydrogels. A schematic diagram and photograph from a top-down view of the millifluidic system used in this study. The bottom photograph of the setup was acquired from the same fixed camera module used for all image-based biodegradation experiments. The depicted photo is thus representative of the quality (color accuracy and image resolution) of all time-lapse images in all biodegradation experiments.

Figure 2

Time-lapse millifluidic imaging system with computational image-analysis capture kinetics of MMP9-dependent GelMA degradation. (a) Schematic diagram of the experimental approach to visually observe GelMA biodegradation. (b) Overview of the computational pipeline applied to all images acquired in the time-lapse experiments. (c) Representative images of stained GelMA discs within the millifluidic chamber over the course of 650 min of 100 μg/mL MMP9 treatment acquired via time-lapse imaging. Quantification of the change in GelMA disc size over time for discs with or without 100 μg/mL MMP9 in PBS (light and dark orange, and blue line traces, respectively, n = 2). (d) Percent of initial GelMA disc weight is plotted over time after exposure to the indicated concentrations of MMP9 in PBS. (e) Side view of a GelMA ocular disc after treatment with 100 μg/mL MMP9 in the millifluidic device. (f) Representative images (both top-down and side views) of GelMA ocular disc before and after treatment with 100 μg/mL MMP9 in a static vial.

Figure 3

Computational image-analysis pipeline detects differences in GelMA biodegradation, which correlates well with conventional weight-based measurements of hydrogel biodegradation. (a) Representative images of GelMA inserts in custom-designed 8-chamber millifluidic devices during treatment with MMP9 over the course of 20 h. (b) Application of our automated custom image-analysis pipeline. Yellow indicates areas detected as stained GelMA inserts, and purple denotes areas not labeled as GelMA. (c) Quantification of two biological replicates (each with three technical replicates) of MMP9-dependent degradation of GelMA discs using our automated image pipeline. (d) Representative images of GelMA hydrogels undergoing irregular degradation or rapid disintegration during treatment with 200 μg/mL MMP9. White dotted outline indicates the location of the hydrogel, and black arrows indicate the location of GelMA biomaterial debris. (e) Pseudorates of GelMA biodegradation were calculated and plotted against MMP9 concentration (n = 3). Statistical significance determined by one-way ANOVA with Tukey multiple comparisons test: * p < 0.05, ** p < 0.005 (f) Linear correlation between the size of the GelMA discs and the weight of the same discs after being removed from the millifluidic device. Red dashed line represents the line of best fit with the Pearson correlation coefficient indicated (R).

Figure 4

Simultaneous measurements of hydrogel degradation and concentrations of released compounds in device eluates. Computational quantification of the biodegradation of (a) GelMA and GelMA-PVA discs MMP9 at 0, 50 and 100 μg/mL. (b) Quantification of soluble PVA released from GelMA-PVA discs (top) and detection of degraded GelMA polymer (bottom) at the indicated times following MMP9 treatment. Error bars represent standard error of the mean. (c) Correlation between detected GelMA in the eluates and the size of the GelMA-PVA disc in the millifluidic device. Red dashed line represents the line of best fit with the Pearson correlation coefficient indicated (R).