Factorial Data-Driven Inverse Design of Granular Hydrogels for Targeted Therapeutic Release

Grandular hydrogels enmeshed with therapeutic particles offer an exciting modular platform for the delivery of targeted therapeutics, but this modularity also complicates the optimization of the design. Here, we present a programmable therapeutic release simulation for this material platform. Using factorial experimental design, we efficiently validate simulation parameters and identify a practical design space that supports precision medicine through the inverse design of unique and customizable drug release profiles, including tunable cumulative release profiles through random packing and tunable instantaneous release profiles through layered packing.