"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. student in the Division of Applied Mathematics at Brown and the study's co-lead author. "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."
Sickle cell disease is a genetic disorder that affects millions of people worldwide. 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). The irregularly shaped cells get stuck in blood vessels, causing pain, swelling, strokes and other complications.
Level - Sickle - Cell - Disease - Hemoglobin
At the cellular level, sickle cell disease affects hemoglobin, a protein in red blood cells responsible for transporting oxygen. When oxygen-deprived, sickle cell hemoglobin clumps together inside the cell. The clumps then form long polymer fibers that push against the cell wall, stiffening the cells and forcing them out of shape.
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. 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.
Model - Combines - Models - Model - Sickling
This new model combines and simplifies the previous models to create a single kinetic model of the entire sickling process. 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.
To validate the model, the researchers showed that it could reproduce the outcomes...
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