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Access to patient-specific information is key to delivering more personalized treatment. A team of biomedical engineers and hematologists at the University of Pennsylvania has conducted large-scale, patient-specific simulations of blood function under the flow conditions found in blood vessels, using robots to run hundreds of tests on human platelets responding to combinations of activating agents that cause clotting. Normally, clots prevent bleeding, but they can also cause heart attacks when they form in plaque-laden coronary arteries. Generating patient-specific information on how platelets form blood clots could be a vital part of care.

Using microfluidic devices, the researchers ran scores of blood tests with each blood sample at venous and arterial flow conditions using different drugs. The multi-scale computer simulation for each donor predicted the drug responses very accurately, and even predicted one person who was resistant to aspirin.

Graduate student and lead author Matt Flamm developed a powerful multi-scale computer model that populates a simulation of blood flowing over a site of vessel damage with thousands of platelets whose behaviors derive from the neural network model developed for each patient.

“This is the first time that it has been possible to predict blood clotting under flow using patient-specific platelets,” Flamm said. “We were able to predict the ranked potency of several drugs.”

The development of equations and algorithms to model reactive blood flow could be very helpful in predicting clinical risks, drug responses, and new disease mechanisms, and in designing biomedical devices.

“Fields like weather prediction and airplane design simulate the flow of air,” said Scott Diamond, professor of chemical and biomolecular engineering and senior author of the study. “In cardiovascular medicine, we encounter the individually unique and complex fluid of human blood. Research areas involving traumatic bleeding, stroke and deep vein thrombosis may benefit advanced simulations of blood function.”

Read more about this development here.