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Machine learning helps grow artificial organs

July 7, 2020
Graphic with stylized molecules

Image credit: MIPT Press Office

Researchers from the Moscow Institute of Physics and Technology, Ivannikov Institute for System Programming, and the Harvard Medical School-affiliated Schepens Eye Research Institute have developed a neural network capable of recognizing retinal tissues during the process of their differentiation in a dish. Unlike humans, the algorithm achieves this without the need to modify cells, making the method suitable for growing retinal tissue for developing cell replacement therapies to treat blindness and conducting research into new drugs. The study was published in Frontiers in Cellular Neuroscience.

“This approach does not require images of a very high quality, fluorescent reporters, or dyes, making it relatively easy to implement,” said first author Evgenii Kegeles of the MIPT Laboratory for Orphan Disease Therapy and the Schepens Eye Research Institute. “It takes us one step closer to developing cellular therapies for the retinal diseases such as glaucoma and macular degeneration, which today invariably lead to blindness. Besides that, the approach can be transferred not just to other cell lines, but also to other human artificial organs.”