Dr. Amor Menezes, Dr. Damon Ghetmiri, and Alessia Venturi of the SYBORGS Lab at UF MAE, along with Dr. Mitchell Cohen of the University of Colorado Anschutz Medical Campus, authored a paper on their breakthrough research that was published in Nature Communications this month.
The paper centers on models the group developed that can assess the coagulation ability of blood in much faster and more efficient ways than what is commonly used. Current procedures for measuring the clot strength of blood are quite time-consuming and impractical for urgent care or automated coagulation control. The models created by the group, however, can predict thromboelastography (TEG) curve outputs based on blood protein concentrations, which can be measured in about five minutes. Using blood protein concentrations like this facilitates treatment decisions, which can be based on the TEG curves predicted by these fast and personalized models.
“Because protein concentrations in a blood sample can be measured in about five minutes, we develop personalized, phenomenological, quick, control-oriented models that predict TEG curve outputs from input blood protein concentrations, to facilitate treatment decisions based on TEG curves,” Ghetmiri explained. “Here, we accurately predict, experimentally validate, and mechanistically justify curves and parameters for common TEG assays.”
The real-world applications of this innovation are vast. Clot strength measurements are used to identify patients at risk for thromboembolic events, when blood clots can block vessels. These measurements are also often used to guide treatments for a variety of conditions, including liver cirrhosis, COVID-19, sepsis, obstetrics-related conditions, diabetes, hemophilia, cardiovascular conditions, and fracture surgeries, among others. In all of those examples, blood viscoelastic measurements provide clinical insight relating to the delivery of blood products such as transfusions, blood protein concentrates, pharmacological agents, and anticoagulant treatments.
According to Ghetmiri, physical trauma is the leading cause of death for people between the ages of 1 and 44, with the majority of deaths and essentially all morbidity driven by coagulation and inflammation biology. This illustrates just how crucially impactful it will be to have the ability to measure clot strength, and make medical decisions based on that, so much more efficiently.
“Collaborating with Dr. Mitchell Cohen, we got the front-row seat to learn about the benefits and pitfalls of coagulation assays, learn about how they are used at the point of care, and this made us think how we can make improvements and increase accessibility,” Ghetmiri said.
Before this project, they had done other modeling of biological systems, but this was a step forward to a more complicated system. They first sought to establish the phenomenological model that can describe the process of coagulation cascade, which is a chain reaction of blood protein concentration that culminates in clot formation. After developing a simplified model, they identified what blood protein concentrations are fundamental for each process, and each section of the model, and leveraged those to establish the prediction model. Once they had this sophisticated model, they trained it using several different datasets of blood samples from healthy individuals and from trauma patients.
“Looking back at this paper, I always feel proud that the results of our tireless efforts can make a real positive impact on patient care and saving lives,” Ghetmiri said. “This would have not been possible without the excellent collaboration of the team, and great leadership of Dr. Amor Menezes.”
Ghetmiri is now a senior system performance engineer at ASML, while Venturi graduated from UF with her bachelor’s in mechanical engineering last semester.
For more information on their research visit https://www.nature.com/articles/s41467-023-44231-w