Deepcell

Spun out of Stanford University in 2017, Deepcell offers a cell classification platform that leverages AI, microfluidics, and high-resolution optics to morphologically isolate cells. The platform is reportedly different from other such platforms in its ability to isolate whole cells and keep them unchanged throughout examinations. 

The REM-I platform is also capable of dealing with any cell population, thus enabling a wide array of applications including translational research, diagnostic testing, and drug development. It supports researchers by facilitating tissue profiling (classifying cells according to specific tissue compositions, drilling down to the cell level), cell enrichment (removing or filtering out morphologically different cells away from a specific desired cell population), and specifically capturing rare cells in populations as small as one in a billion. 

Deepcell has built a database of over one billion cell images via its platform, to assist researchers and drug developers in analyzing and generating insights based on cell mechanisms and behavior. 

Key customers and partnerships

In August 2021, the beta version of the platform was used by 10 organizations including the University of Zurich and Translational Genomic Research Institute, both of which were studying melanoma cells using the platform. Further, in March 2024 , the company launched beta programs for the REM-I platform, including Newcastle University, the European Molecular Biology Laboratory (EMBL) in Heidelberg, and a third US-based academic health science center.

In January 2024 , the company collaborated with NVIDIA to advance GenAI adoption in single-cell research. 

Funding and financials

In its latest Series B funding round led by Koch Disruptive Technologies, Deepcell raised USD 73 million. The funds were earmarked to develop and commercialize its platform.