That same flexibility also enables to model to be run for individual patients who may have more or less severe versions of the disorder. The model allows users to input parameters specific to the organ they’re hoping to simulate. For example, because oxygen plays a key role in the process, sickling unfolds very differently in oxygen-rich areas like the lungs compared to more oxygen-poor areas like the kidneys. To validate the model, the researchers showed that it could reproduce the outcomes of prior experiments in the lab and in people.īecause the dynamics of the sickling process can vary depending upon where in the body it’s happening, researchers designed the model to simulate sickling process in different organs. Using information gleaned from the detailed supercomputer models, the researchers were able to build a simplified version that captures all the important dynamics of the sickling process, yet can be run on a laptop. This new model combines and simplifies the previous models to create a single kinetic model of the entire sickling process. Most recently, he’s worked with Lu and He Li, a research professor at Brown, to create detailed biophysical models of each stage of the sickling process, including a model of red blood cell function called OpenRBC and a supercomputer model of sickle cell fiber formation. George Karniadakis, a professor of applied mathematics at Brown and senior author of the new research, has worked for years to better understand the disorder. The clumps then form long polymer fibers that push against the cell wall, stiffening the cells and forcing them out of shape.
When oxygen-deprived, sickle cell hemoglobin clumps together inside the cell. The irregularly shaped cells get stuck in blood vessels, causing pain, swelling, strokes and other complications.Īt the cellular level, sickle cell disease affects hemoglobin, a protein in red blood cells responsible for transporting oxygen. The disorder causes red blood cells, which are normally soft and round, to become stiff, sticky and sickle-shaped (a bit like a crescent moon). Sickle cell disease is a genetic disorder that affects millions of people worldwide. “We wanted to build a model that considers the entire sickling process and could be used to quickly and inexpensively pre-screen new drug candidates.” student in the Division of Applied Mathematics at Brown and the study’s co-lead author. “There are currently only two drugs approved by the FDA for treating sickle cell disease, and they don’t work for everyone,” said Lu Lu, a Ph.D. The model, described in a paper published in Science Advances, could be useful in the preclinical evaluation of drugs aimed at preventing the sickling process. A team of Brown University researchers has developed a new computer model that simulates the way red blood cells become misshapen by sickle cell disease.
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