Seeing the Previously Unseen

Unmatched Cellular Understanding

Cells are the fundamental building blocks of the human body, and cell identities, states, and interactions between them define how we function in health and what goes wrong in disease. Single-cell genomics allows us to observe individual cells and better understand key differences in diseased tissues and between responders and non-responders to therapy, which helps us identify drug targets and develop the right therapeutics for the right patients. This is the essence of precision medicine.

Real Human Disease Biology

While analysis of model systems is informative, fully understanding human disease requires studying biology using actual patient tissue. We have built an extensively curated collection of human tissue samples in inflammatory disease, and are using single-cell RNA sequencing to generate meaningful insights that facilitate precision drug development.

The collection consists of newly collected and archival samples from around the globe. We have developed preparation and shipping methods that require minimal manipulation at the clinical site and standardized processing methods in order to ensure high quality and consistent data.

Rapid, Scaled Interrogation

Single-cell RNA sequencing is often bespoke and labor-intensive. We have industrialized this process to allow us to analyze large numbers of samples, in parallel, with high throughput. Our automated, machine learning-enabled platform allows us to rapidly analyze and interpret the millions of cells and billions of gene expression data points that result from the single-cell analysis. We have sequenced five million cells and generated more than 100 billion gene expression data points to date, and our dataset continues to grow.

Precision Insight

By comparing cell populations in a large number of tissue samples, we can identify cell types, cell states and gene expression programs that are associated with treatment resistance and disease progression, which we can then mine for new therapeutic targets. Because certain cell populations may be present in some patients and absent in others, our approach provides us with a novel path to identifying patient subsets. The resulting level of insight into inflammation is unprecedented.