SOPHiA DDM™ for Blood Cancers

Science evolves, our solutions adapt
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Hematological tumors represent the fourth most frequent cancer type in the developed world.1

In addition to the continuously evolving clinical guidelines2, reproducible harnessing of all the available information when investigating hematological disorders into meaningful insights can be outdated, inaccurate, costly, and time-consuming. This ultimately risks limiting researchers' productivity, thus leading to potential delayed or inaccurate diagnoses.
Molecular profiling by next-generation sequencing has introduced a paradigm shift in investigating the pathogenic variants causing different blood cancer disorders.

The seamless SOPHiA DDM™ for Blood Cancers portfolio offers researchers competitive advantages that can positively impact disease management. All our solutions enable in-house identification of hematological disorders’ variants and offer valuable insights, allowing you to streamline your decision-making in record time. Our portfolio comprises a range of ready-to-use solutions, targeting relevant DNA variants and RNA fusion genes that drive different blood cancers, in the same panel.
A universal health data analytics platform for a decentralized approach to healthcare
Fig 1. Illustrative representation of the workspace used for hematological cancers interpretation.

Save effort and time with our comprehensive, accurate, and future-proof end-to-end solutions

The SOPHiA DDM™ for Blood Cancers portfolio allows detection and characterization of complex genomic variants, while adhering to most up-to-date international guidelines.

Using these solutions, you can rely on:

  • Comprehensive biomarker coverage, including challenging targets such as CALR, CEBPA, ASXL1, FLT3, FLT3-ITDs and 119 RNA-based fusions

  • Accurate detection of SNVs, Indels, CNVs and gene fusion events

  • Quick and easy customization of the existing panel to fit your laboratory’s need

  • Streamlined workflow – from sample to report – in approximately 2 days

  • Rapid variant interpretation, relying on the analytical performance and advanced features of the SOPHiA DDM™ platform.

1 accessed on May 19th, 2021.
2 Arber, D. A. et al., The 2016 revision to the World Health Organization classification of myeloid neoplasms and acute leukemia. Blood (2016) 127 (20): 2391–2405.
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