Drug Discovery

NYSCF Discovery Platform

Automated high content screening in patient-derived cells for target identification, hit-to-lead, and patient stratification

In 2017, we set out to answer a simple question: can we reliably tell the difference between patients and healthy individuals just by imaging their cells?

To answer this question, we began taking advantage of everything that makes NYSCF unique – the vastness of our biobank and the ability to interrogate biology at scale using automation.

We published a landmark study in Nature Communications demonstrating proof of concept, remarkably, using primary human fibroblasts from a large cohort of Parkinson’s disease patients.

Read the paper: Integrating deep learning and unbiased automated high-content screening to identify complex disease signatures in human fibroblasts

NYSCF has since harnessed this platform, which combines our advantages in scale achieved through automation with cell painting and AI-powered image analysis, to extend these findings in other therapeutic areas and in iPSC-derived cell types. We have further screened libraries, demonstrated the ability to shift disease phenotypes, and are layering in additional readouts.

NYSCF is now actively exploring partnerships to test various therapeutic modalities on large cohorts of patient cell lines and controls.

Read about our announced initiative with big pharma: The New York Stem Cell Foundation Research Institute Enters Agreement to Accelerate Precision Drug Discovery for Neurodegenerative Disease.