New evaluation data shows the clinical utility of SOPHiA DDM Dx HRD Solution

SOPHiA GENETICS, a cloud-native software company in the healthcare space, debuted new data at the European Society of Gynaecological Oncology (ESGO) Congress as part of a poster (#PA-065) presented by Prof. Alexandre Harlé of the Institut de Cancérologie de Lorraine, France. The results show an evaluation of Homologous Recombination (HRD) detection supported by a deep learning algorithm in a clinical cohort of ovarian cancer patients treated with a PARP inhibitor. The new evaluation data show the clinical utility of the SOPHiA DDM™ Dx HRD Solution for accurate HRD testing.

The deep learning-based solution expands identification possibilities for HRD-positive ovarian cancer patients that could potentially benefit from first-line maintenance therapy with PARP inhibitors. In a single workflow, the SOPHiA DDM™ Dx HRD Solution can evaluate the causes and the consequences of HRD, which is a complex biomarker with predictive value in ovarian cancer. Approximately half of all newly diagnosed patients with advanced ovarian cancer have HRD-positive tumors.

The clinical relevance of the SOPHiA DDM™ Dx HRD Solution presented at ESGO was evaluated in a multicenter study using a sub-set of ovarian cancer samples. The results demonstrate that median progression-free survival (PFS) was improved in PARPi-treated patients with HRD-positive status as detected by the SOPHiA DDMTM Dx HRD Solution. The information presented at ESGO can be found at this page.

The SOPHiA DDM™ Dx HRD Solution is CE-IVD certified, enabling it to inform diagnostic purposes in the European Union and other markets recognizing this certification.

SOPHiA GENETICS empowers medical institutions to implement a decentralized testing approach for ovarian cancer management. Rather than having to send tests to larger laboratories, they can simplify and expedite the process in-house, allowing them to retain ownership of the data analyzed, in a cost-effective, timely and reliable manner to potentially allow for better therapy decisions.


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