Thursday, 5 September at 1:00pm
Biochemistry Seminar Room BIG13
Prof John P. Fisher, Fischell Department of Bioengineering, University of Maryland
3D Printing to Engineer Gynecological Tissues
Generating complex tissues has been an increasing focus in tissue engineering and regenerative medicine. With recent advances in bioprinting technology, our laboratory has focused on developing platforms for treating and understanding clinically relevant problems ranging from congenital heart disease to orthopedic trauma. In this presentation, we focus on engineering gynecological tissues, particularly a nipple-areolar complex (NAC), as well as a model of the human placenta. We utilize digital light processing (DLP)-based and extrusion-based additive manufacturing to generate engineered tissues. Both approaches begin with CAD models that are then transferred to printing platforms. Prints use a variety of inks, including synthetic (PEG) and natural (GelMA, ECM) materials. Evaluation of printed constructs assesses critical criteria, including print fidelity, material properties (immediately after printing and at longer time points), cell viability, and cell functionality. Tissue function is assessed both in vitro and in vivo. Our initial studies have generated a portfolio of NAC implant designs via Solidworks, allowing for the rapid development of personalized implants. CAD designs explore the impact of nipple projection height, nipple diameter, areola diameter, and NAC infill patterning upon the implant’s properties, particularly on the shape retention over time. NAC physical and biological properties (shape, mechanics, cell seeding efficiency, cell viability / proliferation, matrix production) have been assessed. NAC vascularization strategies have been developed. We have also developed a 3D printed bioengineered placenta model (BPM) to better understand placental biology. Our multicellular, multiphase construct models the role of the placental matrix upon both the barrier functionality of the tissue and the cellular remodeling throughout pregnancy. We are now using the model to better assess the impact of intrinsic and extrinsic factors on placental functionality.
