red blood cell

A team of researchers at Brown University has engineered an advanced computer model that determines the way regular cells are misshapen by sickle cell diseases. The model could prove to be useful in the evaluation of drugs aimed at preventing such diseases.

Sickle cell disease, a genetic disorder, affects millions of people across the world. The disease turns soft and round blood cells into tough, sticky and crescent moon shaped, like a sickle. The deformity causes the cells to get stuck in blood vessels, causing strokes, pain, swelling, and other complications. Sickle cell diseases affect the hemoglobin negatively, a protein in blood cells responsible for transporting oxygen.

There are only two drugs approved by the FDA for treating sickle cell diseases. The team wanted to build a model that could prevent the entire sickling process and be used quickly and effectively to screen new drug candidates.

The new model takes cues from the previous models, combines and simplifies its principals to come up with a better version and creates a single kinetic model for the entire process of sickling. With the help of information gained from the detailed supercomputer models, the researchers were able to develop a simple model, that could be run on a laptop.

Test and results.

The researchers showed that the new model can deliver the outcomes of previous experiments in laboratories and patients to validate the functioning of the device. The dynamics of sickling depend upon the area where the process is taking place. Therefore, the researchers designed a model to imitate the sickling process in different organs of the body. Oxygen plays an important role in the process, that is why the process happened in more oxygenated areas such as lungs and not in less oxygenated areas like the kidneys. The model provides the users to input specific parameters to the organ they are trying to simulate. The same feature of the model enables it to run for patients who have a severe version of the disorder.

To test the effectiveness of the drugs, the model enables the users to input the action by which the drug is presumed to work. The information is often collected during preliminary lab studies. For instance, if the patient wants the medicine to boost the amount of hemoglobin in the healthy red blood cells, the model could determine the effect on a larger population of organ-specific red blood cells.

According to the lead authors of the study, sometimes a drug can be designed to work on one parameter and has different effects on other parameters. The model is efficient in telling which effects are synergistic and whether they can negate each other. Hence, the model provides a full overview of the effects of the drug

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Cassandra is a freelance writer who believes in writing informative, plagiarism-free content for websites. She is a keen observer of the technological advancements and business trends. She wishes to write her own book one day.

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