Our capabilities across data modalities

Supporting the analysis of a wide range of digital health data modalities to generate novel insights
Patient and MD

Our capabilities across data modalities

Supporting the analysis of a wide range of digital health data modalities to generate novel insights

SOPHiA DDM™ for Genomics


The SOPHiA DDM™ platform streamlines genomic data analysis, interpretation and reporting. Its advanced analytical performance and data visualization supports informed decisions based on genomic alterations.

Biological samples (including fresh frozen tissue, formalin-fixed paraffin-embedded and liquid circulating tumor DNA) can be processed through the SOPHiA DDM™ platform, yielding the confident identification of genomic alterations. The results detail single nucleotide variants (SNVs), insertions and deletions (Indels), copy number variations (CNVs) and gene fusions, as well as more complex mutational signatures such as microsatellite instability (MSI), tumor mutational burden (TMB), homologous recombination deficiency (HRD) or minimal residual disease (MRD).

Plus, the AI-powered SOPHiA DDM™ platform accurately detects and identifies challenging genomic alterations, such as mutations in CEBPA or FLT3-ITD, MET exon14 skipping mutations or rare gene fusions.
A universal health data analytics platform for a decentralized approach to healthcare
Data pooling and knowledge sharing

SOPHiA DDM™ for Radiomics


AI-powered image segmentation and radiomics features extraction turn existing 3D medical images into novel data points.

The SOPHiA DDM™ platform can process and analyze data from any type of three-dimensional medical imaging technology, including computed tomography (CT), positron emission tomography (PET), magnetic resonance imaging (MRI) and single-photon emission computed tomography (SPECT) scanners.

We have developed AI-powered segmentation algorithms that detect tumors in the scans, then segment and reconstruct them in three dimensions, covering a wide range of major tumor types including lung, breast, liver, kidney and brain cancer.

Radiomics features extraction is conducted on segmented tumors, generating data points across volumetric, morphological, first-order (i.e., heterogeneity), second-order (i.e., texture) and deep-learning generated features.

The SOPHiA DDM™ platform has radiomics capabilities for disease detection, discrimination of disease histological subtypes, prediction of tumor evolution and prediction of disease progression.

SOPHiA DDM™ for multimodal data analytics


Combining high-quality data at the individual level to generate multimodal insights, SOPHiA GENETICS harnesses the power of advanced AI and machine learning models.

Today, the SOPHiA DDM™ platform enables the analysis of clinical, biological, genomics and radiomics data. In the future, we intend to support additional data modalities such as digital pathology, proteomics and metabolomics.

The SOPHiA DDM™ platform's predictive modeling capabilities include disease screening, disease early detection, disease diagnosis and subtype discrimination, prediction of disease evolution, prediction of response to therapy, therapy selection and monitoring.
A universal health data analytics platform for a decentralized approach to healthcare
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