# Competitive Inhibition as a Tool to Modulate and Predict Dynamic Hydrogel Mechanics

## TL;DR

Researchers developed a framework using competitive inhibition to predict and control the mechanical properties of dynamic hydrogels, enabling practical applications like injectable gels.

## Contribution

A predictive model based on competitive inhibition is introduced to modulate hydrogel mechanics across different dynamic chemistries.

## Key findings

- The model predicts hydrogel modulus with less than 10% error using boronate ester networks and diol competitors.
- The approach is validated for hydrazone-cross-linked gels, showing broad applicability.
- Competitor addition transformed non-extrudable gels into injectable materials.

## Abstract

Dynamic hydrogels are powerful biomaterials whose performance
in
drug delivery, tissue engineering, and related applications depends
on mechanical properties that remain difficult to predict. We introduce
a simple, quantitative framework for tuning hydrogel mechanics through
competitive inhibition, where small-molecule competitors reversibly
disrupt cross-linking. Inspired by Michaelis–Menten kinetics,
the model defines an apparent cross-link association constant, K
a,app, that decreases as a function of competitor
concentration and binding affinity. Incorporating K
a,app into traditional network theory enabled quantitative
prediction of modulus. When using boronate ester networks and small-molecule
competitors bearing diol motifs spanning 4 orders of magnitude in
affinity, the predicted and measured moduli agreed within 10% relative
error. A Langmuir-type decay function further captured stress-relaxation
behavior by accounting for changes in effective cross-link density.
Extending the approach to hydrazone-cross-linked gels confirmed its
generality across distinct dynamic chemistries and exchange mechanisms.
Finally, we demonstrate practical relevance by transforming a nonextrudable
gel into a hand-injectable material through competitor addition. This
framework establishes competitive inhibition as a universal and predictive
strategy for designing adaptive soft materials.