5E: Computational and Machine Learning Approaches for Biomaterial Design & Evaluation
Time: 8:00 AM to 10:00 AM
Description
Computational modeling and machine learning can enhance our ability to design and evaluate biomaterials for a variety of applications, and have greatly improved patient care worldwide. This session will explore computational approaches and tools for designing biomaterials for tissue engineering and other applications, evaluating complex data from in vitro and in vivo studies, and predicting biomaterial performance in different microenvironments. Examples of these may include fluid mechanics and bio-transport models of drug/protein delivery, models of protein-protein and protein-material interactions, statistical modeling for biomaterial optimization, machine learning for biomaterial design and analysis, and bioinformatics-based platforms for analyzing complex data, including RNA sequencing and other -omics approaches. Progress and challenges in applying computational approaches in developing biomaterials and in patient care may be discussed.
Moderators:
Adam Gormley, Rutgers University
Bingyun Li, West Virginia University
Objectives
8:00 AM. 213. Automation and Machine Learning for Antibody Formulation in High Concentration Regimes.David Radford, PhD1, Matthew Tamasi, PhD1, Elena Di Mare1, Adam Gormley, PhD1 1Rutgers University
8:15 AM. 214. 3D Multi-Scale Simulations of Electrospun Mesh Mechanical Responses from nanoCT images.Evan He, BS1, Shruti Motiwale, PhD2, Elizabeth Cosgriff-Hernandez, PhD2, Michael sacks, PhD2 1Unversity of Texas at Austin, 2University of Texas at Austin
8:30 AM. 215. Computational Modeling of the Effects of Implant Metallic Composition on the Electrochemical Changes upon Cathodic Stimulation of Total Knee Replacements.Priyanshu Vishnoi, PhD1, Elise Martin, PhD1, Mary Canty, PhD1, Mark Ehrensberger, PhD1 1University at Buffalo
8:45 AM. 216. Data-driven design of novel polymer excipients for pharmaceutical amorphous solid dispersions.Elena Di Mare1, Ashish Punia, PhD2, Matthew Lamm, PhD2, Timothy Rhodes, PhD2, Adam Gormley, PhD1 1Rutgers University, 2Merck & Co., Inc.
9:00 AM. 217. Demonstrating the Impact of L- and D-Peptide Isomer Mixtures on Hydrogel Self-Assembly via Molecular Dynamics.Justin Kim1, Rachel Letteri, PhD1, Phillip Taylor, PhD1, Kyle Lampe, PhD1 1University of Virginia
9:15 AM. 218. 3D pore shape is predictable in randomly packed granular systems.Yasha Saxena1, Lindsay Riley1, Wendy Wu1, Shihab Kabir1, Amanda Randles1, Tatiana Segura, PhD1 1Duke University
9:30 AM. 219. Machine Learning-Based Morphometric and Biomarker Analysis To Guide Elastic Matrix Regenerative Repair in Abdominal Aortic Aneurysms.Francesca Morrell1, Joseph Amitrano2, Anand Ramamurthi, PhD, FAHA2, Dhruv Seshadri2 1Lehigh Univeristy, 2Lehigh University
9:45 AM. 220. Building Predictive Models of Stem Cell Fate from Curvature-Induced Cytoskeletal Changes.Elizabeth Byers1, Justin Brown1 1The Pennsylvania State University