TGen and Deepcell Collaborate to Use AI-Based Technology to Classify and Isolate Diseased Cells

The Translational Genomics Research Institute (TGen), a subsidiary of City of Hope, is partnering with a Silicon Valley company to become one of the first research institutes in the world to use new imaging and sorting technology based on artificial intelligence to classify and isolate individual diseased cells.

TGen’s Science Technology Assessment (START) Research Team is partnering with Menlo Park-based Deepcell, which has developed a novel imaging platform that uses AI to analyze individual living cells in real time.

TGen is the first of a handful of institutions to join Deepcell’s Technology Access Program.

Technology uses cell imaging and AI to analyze single cell morphology -; basically what it looks like -; in the context of the other cells in the sample. This allows users looking for new ways to understand cell biology to characterize and isolate cells from tiny visual features. Its resolution is powerful enough to see many components of each cell, including the cell’s nucleus, which contains its DNA and other genomic information.

Deepcell’s technology will allow our TGen researchers to focus on the most critical parts of a cell to better understand what is causing disease,” said


Stephanie Pond, Ph.D., TGen Vice President of Emerging Technologies and Head of START

First focus: melanoma

While Deepcell’s technology can be used in the assessment of any disease, the TGen-Deepcell partnership will begin with a pilot study to characterize melanoma, one of the most dangerous types of skin cancer. Deepcell previously announced a partnership to study melanoma with the University of Zurich, Switzerland, one of the few institutions in the world, along with TGen, to have access to Deepcell technology.

Dr. Jeffrey Trent, President and Chief Research Officer of TGen, leads TGen’s scientific efforts in melanoma. This partnership benefits from decades of genomic research and cellular models of pre-malignant and highly metastatic melanoma.

“Major advances in medicine come from the introduction of sharper tools and cutting-edge methods that can open up new avenues of research,” Dr Trent said. “Deepcell’s technology undoubtedly opens up new avenues for us to explore.”

Deepcell provides advanced analytics

“Our unique AI-powered technology transforms cell morphology into a high-throughput quantitative marker for use in research,” said Maddison Masaeli, Co-Founder and CEO of Deepcell. “With our technology, scientists can now characterize, identify and isolate viable cells without labeling, and use the AI-derived high-dimensional markers and sorted cells to complement existing molecular workflows as well as a new autonomous method.

Dr Pond said that because Deepcell sorting keeps cells intact, it will work hand-in-hand with TGen’s established single-cell sequencing technology to provide the best possible understanding of how each cell might contribute to disease, especially cancers.

“Understanding a complete picture of the tumor microenvironment should provide clues as to how best to treat each patient, particularly focusing on the type of immune cells that might be present and coexisting with cancer cells,” said Dr. Pond.

TGen’s new START program

TGen’s START program is a new technology evaluation facility, dedicated to evaluating pre-commercial technologies for use in TGen’s research programs. TGen excels in applying new technologies to the toughest clinical problems. Over the past decade, for example, TGen has received the world’s first access to multiple technologies that are transforming the field of genomics. These include: rapid whole genome sequencing, PepSeq (protein) immunoscanning, single cell sequencing and high-throughput CRISPR genome editing.

START explores, embarks, tests, then transmits new technologies to TGen and the large company City of Hope. This process brings new technologies that fuel innovative research programs, which in turn fuel TGen’s new commercialization efforts.

Source:

The Institute for Translational Research in Genomics

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