BostonGene and Sarah Cannon Research Institute (SCRI) have announced a collaboration to integrate advanced molecular testing and informatics platforms into clinical decision-making processes at SCRI phase 1 clinics. The partnership aims to validate novel biomarkers using BostonGene’s AI-powered multiomics platform in real-world cancer populations.
Integrating Molecular Profiling into Clinical Workflows
The collaboration will establish data connectivity between BostonGene and SCRI’s precision medicine platform, Genospace. By integrating BostonGene’s advanced testing platform into clinical workflows at community oncology clinics, the effects of molecular profiling on clinical trial enrollment frequency will be examined, including the impact of human leukocyte antigens (HLA) genotyping on pre-screening patients.
Expert Perspectives
"By integrating BostonGene’s advanced molecular profiling into our phase 1 clinical workflows, physicians are poised to significantly enhance our ability to make precise, data-driven treatment decisions. We look forward to the impact we can make in advancing personalized oncology care through our strategic collaboration," said Andrew McKenzie, PhD, Vice President of Personalized Medicine at SCRI and Scientific Director at Genospace.
Nathan Fowler, MD, Chief Medical Officer at BostonGene, stated, "We are thrilled to collaborate with SCRI, integrating our AI-driven multi-omics platform into select community oncology practices. This collaboration will enable us to personalize cancer treatment more effectively and expedite biomarker discovery and validation, ultimately shifting the standard of care and improving patient outcomes."
Comprehensive Data Analysis
BostonGene will provide its CLIA-certified, CAP-accredited Tumor PortraitTM tests to clinicians at SCRI’s phase 1 sites. Comprehensive data analyses by Genospace and SCRI will focus on HLA typing, microenvironment profiles, RNA expression levels, gene alterations, trial enrollment, treatment outcomes, therapy duration and other clinically relevant metrics.
