Drug Delivery
Effective therapeutic design requires optimizing potency, toxicity, availability, and dosage schemes for treatment. Delivery of effective therapies that are able to transport across restrictive endothelial barriers (e.g. blood-brain barrier and HEV-lymph node barrier) remains a central challenge to the treatment of several diseases and cancers. Additionally, gaining access to the lymph node paracortex can unlock improved vaccines and new therapies for autoimmune disorders. We are working on drug delivery strategies for enhanced therapeutic delivery to the lymph node and brain. These projects are in tight collaboration with the Zurakowski and Kwee Laboratories.
Lung Development
Morphogenesis, the process of organ assembly, relies on complex interactions - physical, chemical, and electrical - between multicellular populations of cells. Dysregulation of this process leads to a variety of congenital birth defects that can lead to mortality or life long complications. Much of the work to date has focused on genetic and molecular signals that drive these processes; however, we seek to understand how mechanical forces interact with cellular signaling networks to sculpt the physical process of morphogenesis. Studying developing tissues is incredibly difficult due their 3D nature and the need to visualize these dynamic mechanical environments over time. In our lab, we are building systems that allow us to visualize and perturb the cellular mechanical environments to understand the role of these forces in creating tissues. Specifically we are investigating the role of the extracellular matrix (ECM), tissue strains, tissue stiffness, and the role of fluid flows in driving cellular behaviors and organ formation to inform clinical treatment.
Complex Cellular Self Assembly
Developing engineered tissues for tissue replacement has had limited translation as much of the focus is on recreating native tissue architecture. The challenge in this approach is that these approaches don’t account for cellular remodeling. We think differently about this problem. We use our knowledge of development of the embryo (the original tissue engineer) to apply similar mechanical, chemical, and electrical gradients to 3D organotypic tissues and assist them to develop into functional tissue architectures. We have done this in epithelial and vascular tissues. Most recently, we have harnessed endothelial cells’ innate ability to form vascular networks to fabricate large scale vascularized constructs of arbitrary geometries. This allows for a wide range of bulk shapes and sizes, thus making this process ideal for various types of grafts or constructs. Once the vascular plexus has formed, the network goes through phases of strengthening and pruning in response to fluid flows. We are using graph theory to computationally model the network as a series of nodes and edges to predict how different fluid regimes dictate the structure of the resulting network of arteries, veins, and capillaries. We are working in parallel to generate a hierarchical in vitro vascular network with perfusable ports, allowing for the introduction of flow, which is a critical component of the physiological microenvironment. We have developed an injectable, self-healing hydrogel to support the development of modular, perfusable, hierarchical vascular networks that incorporate stromal cell populations.
Maternal-Fetal Health
Maternal-fetal health is an area of research that has often been overlooked. Many times the problems pregnant women face can be hard to study due to lack of knowledge of an intricate process. The connection between the maternal and fetal systems and the development baby are continually changing and make-up a complex system. The health of the mother during pregnancy not only has consequences on her but also the developing baby. Our lab studies many different facets of the maternal-fetal health space. From understanding placental development, to developing therapeutics to treat pregnant women without harming the developing baby, to understanding lung development in premature babies. In order to study these areas we have developed many tools and platforms to probe information.
Machine Learning
Machine learning opens the door to model complex biochemical relationships through instruction with data. We apply various modern techniques to accomplish high-throughput and robust processing of biological data in two main categories:
Computer Vision
Convolutional neural networks allow for the segmentation and classification of biomedical images. We take this a step further, by reconstructing high-resolution anatomically relevant 3D meshes from image Z-stacks. This allows for the analysis of dense tissues and vasculature with fine precision; informing pharmacokinetic models and biological pathways.
Natural Language Processing
Advancements in transformer neural networks and attentive models allow for an understanding of chemical systems through the augmentation of string datatypes. Through masked language modeling on large corpora of chemical datasets, transformers learn the “semantic laws” of chemical systems, allowing for downstream applications. Primarily, we focus on amino acid datasets to understand the complex interactions of immune cells. Additionally, we conduct novel function and interaction prediction to elucidate fundamental biology.