AI and robotics combine to identify new cellular hallmarks of Parkinson’s Disease.

Researchers at the NYSCF Research Institute collaborated with Google Research to create a new platform for uncovering the hidden cellular signposts of Parkinson’s Disease. The automated cell culture platform utilizes AI along with robotic systems to conduct image analysis of a patient’s cells. This method is expected to enhance drug discovery for the disease, especially as current methods are plagued by high rates of failure. (Inside Big Data)

“The robotic technology NYSCF has built allows us to generate vast amounts of data from large populations of patients, and discover new signatures of disease as an entirely new basis for discovering drugs that actually work,” said NYSCF CEO Susan L. Solomon, JD.

How it works

Using the NYSCF Global Stem Cell Array, a state-of-the-art robotic system, and NYSCF’s massive database of patient cells, the project profiled the images of skin cells from 91 Parkinson’s patients and also healthy patients. The scientists isolated and expanded these cells and thereafter labelled them using a method called Cell Painting.

As a result, the sysem created thousands of high-content optical microscopy images that could be fed into an AI system for image analysis, pinpointing those features (“signatures”) in the images that were peculiar to Parkinsons sufferers and distinct from the images from healthy patients.

These disease signatures now have the potential for use in better guiding drug discovery for Parkinson’s.

“This is the first tool to successfully identify disease features with this much precision and sensitivity,” said NYSCF Senior Vice President of Discovery and Platform Development Daniel Paull, PhD. “Its power for identifying patient subgroups has important implications for precision medicine and drug development across many intractable diseases.”

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