Parse Launches GigaLab to Scale Single Cell Sequencing to Billions of Cells Annually

Demonstrates capabilities with 10 million cells and 1,000+ samples in a single run

Parse Launches GigaLab to Scale Single Cell Sequencing to Billions of Cells Annually

Shev Rush, SRPR
shev@shevrushpr.com | 213.503.4828

Parse Biosciences, a leading provider of accessible and scalable single cell sequencing solutions, today announced the launch of the Parse GigaLab™ to scale single cell sequencing to billions of cells per year. The GigaLab leverages Parse’s Evercode™ single cell technology with a scaled up workflow and expanded automation to enable discoveries never before deemed possible with current single cell approaches.

The GigaLab was built specifically for researchers scaling to projects of 10 million cells and much larger. The current capacity enables profiling of 2.5 billion cells per year and will continue to rapidly grow over time. Several early projects running at the GigaLab are already set to exceed the total number of cells available in all public single cell datasets to date. These new capabilities will be particularly enabling for researchers focused on large-scale drug and perturbation screens, dataset generation for generative AI models, and atlasing for population studies.

As an initial demonstration in partnership with Ultima Genomics, the developer of a revolutionary new ultra-high throughput next-generation sequencing (NGS) platform, Parse ran the first 10 million cell experiment with 1,092 samples in a single run, with all barcoding and library preparation taking just 3 days. This first of its kind study measured 90 cytokine perturbations across 18 immune cell types in 12 PBMC donors, resulting in over 19,000 observed perturbations. In addition to their partnership with Ultima, the Parse team collaborated with Professor Fabian Theis from Helmholtz Munich, whose lab developed the single cell computational biology tool, Scanpy. Theis and his lab are analyzing this 10 million cell dataset and leveraging it to train new AI models.

“Large-scale single cell perturbation datasets are exactly what the field needs to build and train models to help us better predict outcomes in both health and disease,” said Dr. Theis. He adds, “The speed and scale by which Parse is able to deliver these datasets is truly amazing and will accelerate the pace of discovery.”

“With Parse’s existing kits, researchers are now routinely profiling 1 million cells or nuclei in a single experiment,” states Charlie Roco, PhD, chief technology officer and co-founder of Parse Biosciences. He adds, “We still haven’t found a limit to the Evercode technology, and now with the GigaLab, we will usher in a new era of single cell analysis and redefine what’s possible to improve biological discovery and human health.”

Parse team members will be unveiling additional details about the GigaLab capabilities at the upcoming American Society of Human Genetics (ASHG) conference in a CoLab Theater talk (Theater 1) on November 6 at 2:30 PM local time and throughout the remainder of the conference in booth #703.

About Parse Biosciences

Parse Biosciences is a global life sciences company whose mission is to accelerate progress in human health and scientific research. Empowering researchers to perform single cell sequencing with unprecedented scale and ease, its pioneering approach has enabled groundbreaking discoveries in cancer treatment, tissue repair, stem cell therapy, kidney and liver disease, brain development, and the immune system.

With technology developed at the University of Washington by co-founders Alex Rosenberg and Charles Roco, Parse has raised over $100 million in capital and is now used by over 2,000 customers across the world. Its growing portfolio of products includes Evercode™ Whole Transcriptome, Evercode™ TCR, Evercode™ BCR, Gene Select, and a solution for data analysis, Trailmaker™.

Parse Biosciences is based in Seattle’s vibrant South Lake Union district, where it recently expanded into a new headquarters and state-of-the-art laboratory. To learn more, please visit https://www.parsebiosciences.com/.