What is spatial omics?

Spatial omics is a broad term that refers to spatially resolved molecular technologies designed for the analysis of biological molecules in their native location within a tissue. These technologies are unique in their ability to maintain the spatial context.

Spatial transcriptomics, for example, analyses the genes that are expressed at different locations within a patient’s tissue. We can use this information as a way to identify the different cells of the tumor microenvironment, including tumor and non-tumor cells, and how they interact with each other.

What is unique about spatial omics?

The ability of spatial omics to preserve the architecture of the tissue coming from patient samples allows researchers to gain a new understanding of cancer in its native spatial context.

When integrated with data from other modalities like imaging, genomics and proteomics, spatial omics provides a deep, multimodal understanding of disease mechanisms.

For these reasons spatial omics is poised to generate major breakthroughs in cancer research in the coming years.

How will MOSAIC translate spatial omics into benefits for cancer patients?

To translate spatial omics data into healthcare benefits there is a need for high-quality patient data and access to thousands of samples. We believe that the convergence of AI and spatial omics combined with patient data will spark new cutting-edge research and discoveries in cancer.

The MOSAIC initiative unites top cancer centers globally, together with Owkin’s AI expertise to create the world’s largest spatial, multiomics dataset in oncology.

This initiative will paint a picture of the dynamics between cells within the tumor microenvironment, and highlight key biological networks to enable personalized medicine via the discovery of new disease biology, more specific patient subtypes, and new biomarkers and drug targets for those patients.

In more detail

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How will spatial omics decode the complexity and heterogeneity of cancer?

What is the role of AI in MOSAIC?

MOSAIC will generate a very large dataset, with data from multiple research institutions, disease indications, and new cutting-edge modalities. The only way we can integrate such data, and analyze it to unlock scientific breakthroughs is by using purpose-built AI models: this is Owkin’s strength.

In spatial omics we use forms of AI for the analysis of tissue images, for cell segmentation, and to integrate information from across thousands of samples. We also use AI to connect spatial biology with aspects of the patients' profile, such as response to treatment.

AI is central to the success of MOSAIC, which is why Owkin is well positioned to lead this initiative.