EAGER/Collaborative Research: Experimentally Validated Modeling of the Dynamics of Carbon Dioxide Removal from the Bloodstream via Peritoneal Perfluorocarbon Circulation

点击翻译按钮获取中文摘要

This EArly-concept Grant for Exploratory Research (EAGER) project brings together a multidisciplinary team of control engineers, biomedical engineers, medical researchers, and clinicians to explore a novel pulmonary-independent method for supplementing gas exchange in an animal. Specifically, the research team will study whether the circulation of oxygenated perfluorocarbon (PFC) through the abdomen (the peritoneal cavity) of a large animal, can serve as a pathway for clearing carbon dioxide (CO2) from the animal’s bloodstream; and what are the governing dynamics of this CO2 clearing process. The peritoneal cavity essentially acts as a “third lung” in this scenario, providing critical life support for patients whose compromised lung function has exceeded the support achievable through mechanical ventilation. There is currently a critical need for this treatment, within the context of the COVID-19 pandemic, but this system also has potential to emerge as a standard modality in the critical care of hundreds of thousands of patients in pulmonary failure. Furthermore, the medical community will benefit from the deep fundamental understanding of the CO2 removal capabilities of peritoneal oxygenated PFC circulation, which will be an essential element in bringing this technology into future clinical trials.This project addresses the challenge of building an experimentally validated model of the dynamics of carbon dioxide transport from the bloodstream of a large animal into oxygenated perfluorocarbon perfused through the animal’s abdominal (peritoneal) cavity. Using the experimental data obtained as part of this project, the team will develop and parameterize a control-oriented, multi-compartment model of the transport dynamics governing CO2 removal. While previous experiments on peritoneal oxygenated PFC circulation have predominantly examined quasi-steady conditions, the research team will ensure the richness of its data by deliberately designing the underlying experiments to maximize the identifiability of the CO2 removal dynamics. The result will be a dataset better suited for the modeling and estimation of underlying system dynamics than the quasi-steady datasets. The system dynamics and control community will benefit from the opportunity to apply its scientific tools and methods to the dynamic modeling of a novel ventilation technology. Particularly important is the degree to which such modeling can help broaden the interdisciplinary impact of the dynamic systems and controls discipline to a new health-related application technology. Addressing this research challenge urgently, but rigorously, has the potential to provide critical assistance to the medical research community, particularly considering the COVID-19 crisis.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.