Deepcell Closes $20 Million Series A Round to Develop AI-Powered Capture of Cells for Precision Medicine
Spun out of Stanford University in 2017, Deepcell is using deep learning and big data to classify and isolate individual cells from a sample. The technology combines advances in AI, cell capture, and single-cell analysis to sort cells based on detailed visual features, delivering novel insights through an unprecedented view of cell biology. The Deepcell platform maintains cell viability for downstream single-cell analysis and can be used to isolate virtually any type of cell — even those occurring at frequencies as low as one in a billion — to offer access to rare cells and atypical cell states that will help advance precision medicine research.
“From its early days in my lab to its launch as a startup, the Deepcell technology has offered the exciting potential of characterizing, identifying, and sorting cells without perturbation,” said Euan Ashley, Professor at Stanford and co-founder of Deepcell. “Identifying and isolating cells on a spectrum, all the way down to ultra rare, harbors unprecedented potential for understanding single-cell biology and for advancing precision medicine.”
With its AI-powered approach, Deepcell’s technology is able to differentiate among cell types with greater accuracy than traditional cell isolation techniques that rely on antibody staining or similar methods. The company’s AI identifies cells based on infinitesimal morphological differences that may not be visible to the human eye, and continually improves through a closed-loop process in which results from each analysis are fed back into the AI to hone its performance.
Unlike other approaches, Deepcell’s technology was developed to isolate and collect label-free cells of any type, keeping the cell intact for downstream biological characterization. By targeting whole cells instead of cell-free DNA, the Deepcell technology gives users access to cell-specific information — a view of the cell’s full DNA, RNA, epigenetics, and protein contents — and the ability to understand cellular heterogeneity in rich detail.
“By taking cell morphology into the digital age, Deepcell has the potential to revolutionize the field, in a similar way that high-performance computing enabled dramatic advances in genomics and transcriptomics,” said Vijay Pande, General Partner at Andreessen Horowitz.
Maddison Masaeli, co-founder and CEO of Deepcell, commented: “Cell morphology is a phenotype with a long history in clinical application that has to date been based on the eyes of a human expert. Deepcell is bringing this phenotype into modern use by adding scale, interpretability, and actionability, thanks to our innovations in AI, microfluidics, and multiomics.”
Other investors in the funding round include 50Y, DCVC, Stanford University, and angel investors, including Google’s head of AI Jeff Dean. For more information about Deepcell, please go to www.deepcellbio.com.
Deepcell is helping to advance precision medicine by combining advances in AI, cell classification and capture, and single-cell analysis to deliver novel insights through an unprecedented view of cell biology. Spun out of Stanford University in 2017, the company has created unique, microfluidics-based technology that uses continuously learning AI to classify cells based on detailed visual features and sort them without inherent bias. The Deepcell platform maintains cell viability for downstream single-cell analysis and can be used to isolate virtually any type of cell, even those occurring at frequencies as low as one in a billion. The technology will initially be available as a service for use in translational research as well as diagnostics and therapeutic development. Deepcell is privately held and based in Mountain View, CA. For more information, please visit deepcellbio.com.