Biological systems are inherently complex. Identifying patterns in biological systems is a daunting, time consuming endeavor. Biomedical engineers at Duke University have created a novel artificial intelligence (AI) machine learning methodology that can predict behaviors of biological circuits in orders of magnitude faster than standard computational methods, and published their findings in Nature Communications on September 25, 2019. In scientific research for pharmaceuticals, disease treatments, and biomedicine, mathematical modeling is used to understand the processes for the particular biological system. Different systems require a separate approach.

Researchers at the Duke University, Durham, North Carolina, claim they have made an artificial human heart muscle that's big enough to be used to solve damage seen in heart attack victims. The team said that this development takes us closer towards the aim of repairing dead heart muscles in patients. The study called "Cardiopatch Platform Enables Maturation and Scale-Up of Human Pluripotent Stem Cell-Derived Engineered Heart Tissues" published on Nov. 28, 2017, appeared on Nature Communications. "Right now, virtually all existing therapies are aimed at reducing the symptoms from the damage that's already been done to the heart, but no approaches have been able to replace the muscle that's lost, because once it's dead, it does not grow back on its own," said Ilya Shadrin -- the first author of the study who is also a biomedical engineering doctoral student at Duke University. "This is a way that we could replace lost muscle with tissue made outside the body."