Injectable hydrogels are attractive candidates for minimally invasive tissue engineering therapies for complex craniofacial bone defects. In contrast to current treatments such as autograft bone, this versatile class of materials provides a highly hydrated matrix formulated as an aqueous solution that can be injected into large craniofacial defects, crosslinked in situto fill complex configurations, locally deliver stem cells and therapeutic agents, and remodeled into native bone. Our laboratory has developed two novel injectable hydrogel systems for craniofacial tissue engineering based on poly(N-isopropylacryamide), a thermosensitive polymer that undergoes a sol-gel phase transition to form physically gelling three-dimensional scaffolds. Dual physically and chemically gelling networks were synthesized through the copolymerization of N-isopropylacryamide with epoxy pendant groups that can react with a diamine-functionalized polyamidoamine crosslinker, or pendant phosphate groups allowing for post-polymerization attachment of crosslinkable methacrylate groups. Controlled degradation of the hydrogel networks was achieved through hydrolysis-or enzyme-dependent lower critical solution temperature modulation above physiological temperature. In vitro and in vivo results suggest that the development of injectable, dual-gelling hydrogels provides a promising method for minimally invasive and localized delivery of stem cells for craniofacial bone regeneration.

BIOSKETCH

Antonios G. Mikos is the Louis Calder Professor of Bioengineering and Chemical and Biomolecular Engineering at Rice University. His research focuses on the synthesis, processing, and evaluation of new biomaterials for use as scaffolds for tissue engineering, as carriers for controlled drug delivery, and as non-viral vectors for gene therapy. He is the author of over 530 publications and 27 patents. He has been cited over 48,000 times and has an h-index of 118.Mikos is a Member of the National Academy of Engineering, a Member of the Institute of Medicine of the National Academies, and a Member of the Academy of Medicine, Engineering and Science of Texas. He is a Founding Fellow of the Tissue Engineering and Regenerative Medicine International Society, a Fellow of the American Association for the Advancement of Science, a Fellow of the American Institute of Chemical Engineers, a Fellow of the American Institute for Medical and Biological Engineering, a Fellow of the Biomedical Engineering Society, a Fellow of the Controlled Release Society, a Fellow of the International Union of Societies for Biomaterials Science and Engineering, and a Fellow of the National Academy of Inventors.Mikos is a founding editor and editor-in-chief of the journals Tissue Engineering Part A, Tissue Engineering Part B: Reviews, and Tissue Engineering Part C: Methods.

2. Computational Prediction of Receptor-Ligand Interactions
as an Enabling Technology for Tissue Engineering

Systems biology is providing researchers with genomic, proteomic, signaling, and metabolomic information at unprecedented rates. Tissue engineering has yet to benefit from the repositories, analysis tools, and enabling technologies that are becoming available. A central goal is the computational modeling of receptor-mediated interactions where the functional epitope is well understood, typically from experiments. A novel approach will be presented that uses substructure matching methods to identify the given epitope in proteins deposited in the Protein DataBank. Such data mining is of primary importance now that high-throughput methods for structure determination have greatly increased the number of proteins with known structure in the Protein DataBank. Proteins that locally match the epitope, or a small variant of the epitope, can be efficiently isolated and studied. Identification of proteins of previously uncharacterized function can aid the design of new therapeutics. Furthermore, a nuanced and detailed understanding of protein function can also provide insight into the roles proteins play in signaling networks with yet unexplored implications for tissue engineering.

BIOSKETCH

Lydia E. Kavraki is the Noah Harding Professor of Computer Science and Bioengineering at Rice University. Kavraki received her B.A. in Computer Science from the University of Crete in Greece and her Ph.D. in Computer Science from Stanford University. Her research contributions are in physical algorithms and their applications in computational structural biology and biomedicine. Kavraki has authored more than 200 peer-reviewed journal and conference publications. She is an associate editor of several journals including ACM/IEEE Transactions in Bioinformatics and Computational Biology, PeerJ in Computer Science, Frontiers in Molecular Biosciences, and Annual Reviews. Kavraki is a Fellow of the Association of Computing Machinery, a Fellow of the Institute of Electrical and Electronics Engineers, a Fellow of the Association for the Advancement of Artificial Intelligence, a Fellow of the American Institute for Medical and Biological Engineering, a Fellow of the American Association for the Advancement of Science, and an elected member of the Institute of Medicine of the National Academies of the United States of America.