In This Article:
Research presented will include the applications of new diagnostic tools and machine learning multimodal signatures in clinical trials
BOSTON and ROLLE, Switzerland, Sept. 12, 2024 /PRNewswire/ -- SOPHiA GENETICS (Nasdaq: SOPH), a cloud-native healthcare technology company and a global leader in data-driven medicine, will be presenting multiple posters at the European Society for Medical Oncology (ESMO) Congress 2024 being held in Barcelona, Spain September 13-17, 2024. The ESMO Congress is a globally influential oncology platform for clinicians, researchers, patient advocates, journalists and healthcare industry representatives from all over the world.
The details of the presentations are as follows:
Title: Analytical validation of an NGS panel-based ecDNA detection device for use as a clinical trial assay for the POTENTIATE clinical study of the novel CHK1 inhibitor, BBI-355
Poster Session: New Diagnostic Tools, Poster #1198
Date/Time: Sunday, September 15, 2024, 17h20 CEST
Presenting Author: Julien Pontis, Technical Product Manager and Lead Data Scientist, SOPHiA GENETICS
This poster presentation will focus on the analytical validation of a next-generation sequencing (NGS) panel-based extrachromosomal DNA (ecDNA) detection device. This innovative device has been developed as a clinical trial assay for Boundless Bio's ongoing, first-in-human POTENTIATE Phase 1/2 clinical study of its lead ecDNA-directed therapy (ecDTx), BBI-355.
"ecDNA-enabled cancers have a unique biology, with a growing body of research showing these tumors rapidly evolve and typically fail to respond to targeted therapies, leading to worse patient prognoses, including poor time to progression and overall survival. We have developed and validated a proprietary algorithm to detect ecDNA from the outputs of NGS panels routinely used to detect alterations in patient tumors that can be used to select patients for clinical trials," said Julien Pontis, Technical Product Manager and Lead Data Scientist at SOPHiA GENETICS.
Title: TRIDENT: Machine learning (ML) multimodal signatures to identify patients that would benefit most from tremelimumab (T) addition to durvalumab (D) + chemotherapy (CT) with data from the POSEIDON trial
Poster Session: NSCLC, Metastatic, Poster #1325
Date/Time: Saturday, September 14, 2024, 12h00 CEST
Presenting Author: Ferdinandos Skoulidis, Department of Thoracic Medical Oncology, University of Texas MD Anderson Cancer Center
This poster will feature the TRIDENT study, which leverages machine learning to develop multimodal signatures that can identify patients who would benefit most from the addition of tremelimumab to the durvalumab and chemotherapy regimen in the context of first-line treatment of stage IV non-small cell lung cancer. Dr. Ferdinandos Skoulidis from the University of Texas MD Anderson Cancer Center will present the findings, which are based on a retrospective multimodal analysis of the POSEIDON Phase 3 trial.