Science Drivers (Next Gen)
Synthetic Biology-Enabled Biomaterials
Marian Hettiaratchi - mhettiar@uoregon.edu
Beyond traditional chemistry-based efforts to design biomaterials, an approach that shows great promise is using synthetic biology to incorporate active and dynamic materials in the biological system or integrate the active synthetic materials more seamlessly with biological components. These can include protein- and DNA-based biomaterials that leverage unique protein-protein, protein-nucleotide, and other macromolecular interactions. These cell-free systems control complex biological processes within biomaterials, and advances in bioconjugation that enable precise additions of proteins and other biomolecules to biomaterials.
Smart/Responsive Biomaterials
Mike Pluth - pluth@uoregon.edu
As the field has moved away from biomaterials that passively interact with their surroundings towards biomaterials that actively integrate with and instruct their environments, the need for smart, responsive biomaterials that can fulfill this role has increased. The ability to program numerous functions using biomaterials has widened the capabilities of the field. These include biomaterials that trigger temporal immune response activation, present, or shield specific protein or cell signals with spatiotemporal control, provide on-demand/triggered drug delivery, and biomaterials that respond to environmental or externally applied stimuli by changing physicochemical properties, releasing cargo, and/or triggering a cascade of cell signaling events.
Biofabrication and Biointerfaces
Ramesh Jasti - rjasti@uoregon.edu
Traditional implants have been developed to be space-filling with minimal ability to actively regenerate lost tissue and respond to host biological and mechanical inputs. However, more recently developed biomaterials that actively integrate with their surroundings have enormous potential to fill tissue defects and facilitate the eventual remodeling of the biomaterials into healthy, functional tissue. Research in volumetric 3D printing, bioprinting, tissue-material interactions, and biointerfaces is necessary to develop biomaterials taht can fulfill the roles of engineered tissues.
Data-Driven Methods for Biomaterials Design
Danielle Benoit - dbenoit@uoregon.edu
Considering this multi-faceted approach with tremendous design space available for exploration, the use of data-driven methods, including artificial intelligence (AI), machine learning (ML), and statistical modeling techniques become invaluable in the experimental cycle to focus efforts on the most impactful combinations of variables at the experimenter's disposal. Using data-driven strategies and large libraries of materials, the process of reaching fundamental understanding is expedited, and the biomaterial can be rapidly optimized and fast-tracked to application-driven stages of development. This methodical experimental exploration is also key to hastening clinical translation and regulatory processes, as the number of new variables is reduced, and iterative design becomes simplified.