Unknown side effects of drugs taken by pregnant women can cause various birth defects in newborns and can be very difficult to test for.
A recent UW-Madison discovery could provide a cheaper, faster and more reliable way to test for these potential side effects and help avoid neurodevelopmental disorders like autism, according to a university release.
Michael Schwartz, an assistant scientist in biomedical engineering at UW-Madison, co-authored the study with Zhonggang Hou of the Morgridge Institute, who is now a researcher at Harvard.
The research team used stem cells to build parts of the brain that are usually targeted by toxic chemicals or drugs. These brain-imitating tissues are called “organoids” and were used in various drug tests to make models to test other chemical compounds.
The organoids provided surprisingly consistent results, even across diverse cells within the model tissue, including neurons, glial cells, interconnected vascular networks and microglia. The tissues constructed were the first to incorporate all these components of the brain, creating a more complete 3-D model of brain development.
Not only is the new testing method easier and more accurate for researchers, it also could lessen reliance on animal testing.
"These model neural tissues capture a lot more of the complexity than you would find in a monolayer of cells," Schwartz said in the statement. "They also mimic human physiology, and should be more relevant for predicting toxicity than animal models. The fact that we could apply a machine learning model to achieve 90 percent accuracy this early in the process is fantastic."
The project required collaborative efforts from the regenerative biology team at the Morgridge Institute and UW-Madison experts in tissue engineering and machine learning. The data generated could also lead to future collaborations, according to the release.
Beyond drug testing, the new methods could also benefit future studies in helping to understand effects of environmental chemicals and identify toxic profiles or fingerprints in general.
"These datasets provide valuable information about changes in gene expression that researchers can mine to better understand mechanisms that might be disrupted during human brain development," Schwartz said in the release.
