Hettiaratchi Lab

Current Projects

Directed Evolution for Controlled Protein Delivery

Current strategies for controlling protein delivery from biomaterials rely on natural protein-material interactions with limited tunability or the expression of challenging fusion proteins. Yeast/phage display platforms offer a means of generating specific affinity binding partners for proteins of interest, such that their local presentation and effect on different stages of tissue healing may be tuned with precision and flexibility. We are generating libraries of highly specific binding partners for therapeutic proteins with tunable affinities that will enable the delivery of multiple therapeutics from a single biomaterial delivery vehicle.

Cell-Instructive Biomaterials for Bone Repair

Stem cell transplantation can stimulate tissue repair through the secretion of pro-regenerative paracrine factors. Harnessing the regenerative and immunomodulatory potential of stem cells through their secretome represents a recent paradigm shift in the field of tissue engineering. We are creating biomaterial delivery vehicles that facilitate both paracrine- and cell-based tissue repair strategies by (1) presenting biochemical cues that promote cell viability and encourage paracine factor secretion of stem cells, and (2) selectively sequestering paracrine factors in the injury micro-environment using protein binding partners. We aim to prolong local presentation of secreted proteins beyond the initial period of transplanted cell survival and create a pro-regenerative environment within injury sites.

Predictive Bio-transport Modeling

A major challenge in developing biomaterials for sustained protein delivery is the difficulty of recapitulating the dynamic cellular and molecular makeup of the injury environment in the lab. Many biomaterials that provide sustained delivery in vitro exhibit rapid protein release in vivo due to cellular uptake, competitive protein binding, and changes in tissue diffusivity. We are developing computational models that better capture the dynamic healing environment and can more accurately predict protein release in vivo, allowing us to design better biomaterials for in vivo protein delivery.