BostonGene Showcases AI-Powered Multiomics Platform at the 22nd Annual Meeting of Japanese Society of Digital Pathology in 2024
BostonGene, a leading provider of AI-driven molecular and immune profiling solutions, today announced that two abstracts have been accepted for the 22nd Annual Meeting of the Japanese Society of Digital Pathology in 2024, scheduled to take place August 29 - 31, 2024, at Meio University in Nago, Japan.
At the meeting, Jochen “ Joe” Lennerz, MD, PhD, Chief Scientific Officer at BostonGene will deliver a talk titled “Regulatory Horizons: Shaping the Future of Digital Pathology and AI” on Thursday, August 29 at 3:00 PM.
The talk will delve into the integration of AI, molecular diagnostics and advanced data services, highlighting how these innovations are shaping the diagnostic technology landscape. Joe Lennerz will use the example of ‘AI-powered multiomics platforms’ to illustrate, the complexities of modern diagnostics and how to navigate these challenges using regulatory tools and approaches. Key aspects will include the solutions’ ability to ensure interoperability, conduct safety and effectiveness analyses and enhance diagnostic quality management. Leveraging multiomics holds the promise of driving improvements in patient care and maintaining relevance in the evolving landscape of value-based healthcare.
Details about the abstracts selected for presentation can be found below:
Capturing Tumor Microenvironment Heterogeneity with an AI-Powered Clinical Multiplex Immunofluorescence Pipeline
Date: Friday, August 30
Speaker: Joe Lennerz, MD, PhD, Chief Scientific Officer, BostonGene
The study introduces an AI-powered multiplex immunofluorescence pipeline to assess tissue heterogeneity within the tumor microenvironment, crucial for understanding immunotherapy responses. Utilizing advanced cell segmentation and typing techniques, the method outperforms traditional imaging and other segmentation models, achieving high accuracy. The pipeline successfully identifies cell subpopulations and their interactions, demonstrating consistent detection of malignant epithelial and immune cells across various cancer types. This innovative approach, validated against manual annotations, is poised to enhance clinical studies and biomarker development in oncology.
Machine Learning Techniques for Automated Image Analysis of Tertiary Lymphoid Structures in Lung Cancer
Date: Friday August 30
Speaker: Joe Lennerz, MD, PhD, Chief Scientific Officer, BostonGene
The study evaluates an automated digital imaging analysis (DIA) platform for detecting tertiary lymphoid structures (TLSs) in lung adenocarcinoma (LUAD), which are key indicators of therapeutic response and survival. The DIA platform showed greater reproducibility and sensitivity than manual identification by pathologists. In a prospective cohort, the platform detected more TLSs and was associated with improved overall survival in patients with higher TLS density. This method provides a standardized approach to TLS detection, which could enhance clinical trial selection and treatment decisions in precision oncology.
About BostonGene Corporation
BostonGene powers an AI model of tumor and immune biology to deliver disease-level insights and enable precision decision-making across oncology and immune-mediated diseases, spanning drug development and clinical care. By integrating multimodal data, including genomic, transcriptomic, immune, and clinical signals, BostonGene generates biologically grounded intelligence to optimize patient selection, trial design, and therapeutic strategy. This creates a scalable AI decision layer that improves development outcomes and clinical management. BostonGene partners with leading biopharmaceutical organizations and academic institutions to accelerate the delivery of precision therapies while continuously expanding its capabilities across new diseases and complex biological systems. For more information, visit www.BostonGene.com.
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