When discovery begins with patients, progress gains momentum

We are harnessing the power of single-cell RNA sequencing to markedly improve human health. Our objective is to understand how small cell populations and dynamics drive disease in order to develop breakthrough therapies for patients with difficult-to-treat diseases.

Our approach not only has deep implications for treatments but also helps identify the best choices for drug combinations and how to match effective medicines with the right patients.

Our product engine is built on a rigorous multi-step approach:

 
  • 1.

    Disease-specific experimental design

    Robust experimental design to define the right patient samples for analysis

    2.

    Industrialized sample processing

    Robust methods for sample acquisition and tissue processing

  • 3.

    Insight

    Advanced data analysis combining massive datasets with complex machine learning algorithms

    4.

    Target validation through Perturb-seq

    Fast credentialing of promising targets through cycles of perturbation

  • 5.

    New therapies for new targets

    Discovery engine leveraging newly generated insights to rapidly discover and develop novel therapeutics

    6.

    Celsius Dx

    Biomarker development to identify the patients who will respond best to our treatments

Disease-specific experimental design

Robust experimental design to define the right patient samples for analysis

We define new protocols to determine which patient samples should be collected and at what time. These precise samples and downstream screens allow Celsius to gain a deeper understanding of the disease biology and better interrogate our pipeline.

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Industrialized sample processing

Robust methods for sample acquisition and tissue processing

Our robust expertise in tissue handling and processing, single-cell RNA sequencing and innovative, proprietary computational techniques allows for a deep characterization of primary patient tissues that delivers insights into the mechanism of diseases. By measuring individual cells in the context of their ecosystem, we are able to attain a level of resolution that was previously impossible.

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Insight

Advanced data analysis combining massive datasets with complex machine learning algorithms

We use the single-cell RNA sequencing data to model the cellular ecosystem of disease and generate new insights. By measuring changes in the quantity, types and states of each cell within each patient sample, we can compare each sample on an individual cell basis with other healthy and diseased samples, thus moving beyond classically defined disease descriptions. This clarity identifies cell “states,” including subtypes of cell populations that can drive disease. Our scientists are constantly interrogating new samples within and across diseases to identify new therapeutic targets.

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Target validation through Perturb-seq

Fast credentialing of promising targets through cycles of perturbation

Insights from the modeling of cell interactions and cell states within healthy and diseased tissue will lead to candidate targets at therapeutic nodes. These candidate targets are rapidly credentialed and validated in a semi-high throughput fashion using techniques that combine both the advantages of single-cell sequencing and advanced functional screens to ensure a high confidence in the platform output.

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New therapies for new targets

Discovery engine leveraging newly generated insights to rapidly discover and develop novel therapeutics

Validated targets will have a seamless transition into early drug discovery. Our strong team is composed of experienced drug hunters who drive these programs through development. We focus on making the right drug for the right target, agnostic to modality.

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Celsius Dx

Biomarker development to identify the patients who will respond best to our treatments

As our drug discovery programs advance, we focus on translating our single-cell insights into a strategy to properly identify and stratify patients so we may provide the right medicine to the right patient. By understanding the mechanism of disease from patient samples and bringing the newly developed therapies back to these stratified patient subsets, we believe early and late drug discovery will be significantly more effective.

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Our product engine includes sophisticated data-driven tools and computational methods that allow us to prioritize which cells and genes matter in complex diseases.