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BostonGene has been recognized at the 2025 Life Sciences Times Vanguard Awards for its innovative approach to oncology drug development. The company’s AI-powered platform combines data from tumor and immune biology to help researchers better understand how treatments may work before they reach patients. By supporting smarter trial design and faster decision-making, BostonGene is helping make the drug development process more efficient and focused.

A new research collaboration between academia and AI-driven technology is helping advance precision oncology by combining molecular, genomic and immune profiling insights to support more personalized cancer treatment approaches. The initiative focuses on transforming complex clinical and biological data into actionable insights that can help improve therapeutic decision-making and support future oncology research.

BostonGene has received recognition from Frost & Sullivan for its contribution to AI-driven oncology innovation. The company’s multimodal platform supports biopharma teams by analyzing complex biological and clinical data to improve trial design, biomarker strategies, and patient selection in cancer treatment research.

The recognition reflects the growing role of AI and data-driven technologies in helping researchers make faster and more informed decisions throughout the drug development process.

BostonGene and Unilever are working together to explore how AI and multiomics can support scientific research and deepen the understanding of human biology. The collaboration combines data integration, analytics, and scientific expertise to study biological variation and identify insights that may contribute to future consumer research and product development. It also highlights the increasing use of AI in broader areas of scientific exploration and innovation.

BostonGene is presenting its AI-powered disease modeling platform at JSMO 2026, highlighting how multimodal data and foundation models are improving drug development and clinical decision-making. By enabling better patient stratification and therapy insights, the platform is helping advance precision oncology and supporting collaborations with leading biopharma companies.

BostonGene is working with ImmunoGenesis to study IMGS-001, a therapy under evaluation in the NCT06014502 trial for solid tumors. The collaboration uses AI-based multiomic analysis and spatial biology to examine how treatments interact with both tumors and the immune system. By focusing on detailed biological data from individual patients, the research aims to improve understanding of treatment response and support more informed clinical decisions.

BostonGene will present 13 abstracts at the AACR Annual Meeting 2026, highlighting its advanced AI platform for tumor and immune biology. The presentations demonstrate how AI-driven multiomic analysis is accelerating drug discovery, improving patient stratification, and reducing risks in clinical development.

BostonGene, in collaboration with The University of Texas MD Anderson Cancer Center, shares results from a prospective study demonstrating how RNA transcriptome profiling can reveal new therapeutic targets in advanced solid tumors. By integrating RNA expression with DNA sequencing and AI-powered multiomic analysis, the research highlights how previously hidden treatment opportunities can be identified, especially for patients who lacked actionable insights from DNA testing alone. The findings also point to the growing importance of antibody-drug conjugates (ADCs) and comprehensive molecular profiling in expanding precision oncology approaches and enabling more personalized treatment strategies.

BostonGene has been honored with the 2025 Global Technology Innovation Leadership recognition by Frost and Sullivan for its AI driven precision oncology solutions.

The company’s omnimodal foundation model integrates multiple layers of biological and clinical data to deliver insights that support biomarker strategies, improve patient selection and enhance therapeutic development.

By enabling more data driven decision making, BostonGene is helping accelerate clinical trials and increase efficiency in oncology drug development.

Artificial intelligence continues to play a major role in accelerating cancer research and therapeutic innovation. BostonGene has partnered with Ottimo Pharma to support development of a first in class PD1 and VEGFR2 immuno oncology therapy.

The collaboration leverages advanced analytics and multiomic insights to improve clinical research strategies and support next generation precision oncology treatments.

Artificial intelligence is reshaping the future of oncology development. BostonGene has partnered with AstraZeneca to advance foundation model driven cancer research and strengthen precision medicine strategies.

This collaboration reflects a significant step toward smarter therapeutic innovation powered by AI analytics.

HER2 scoring plays an important role in breast cancer diagnostics, influencing treatment pathways and clinical decisions. An independent multi vendor study has validated BostonGene’s AI driven approach for precision HER2 scoring, demonstrating strong alignment with expert pathology assessments.

The findings highlight how artificial intelligence can help reduce variability in biomarker evaluation while supporting reproducible and consistent results across different environments. As AI continues to be explored in oncology research, validated approaches like this contribute to broader adoption in diagnostic workflows.

The BostonGene article Tumor-associated macrophage TAMs and cancer-associated fibroblasts CAFs profiles in invasive lobular carcinoma vs no special type reports a comprehensive comparison of stromal and immune cells using large transcriptomic data sets. Macrophage subsets (M1/M2) and CAF subtypes including inflammatory iCAFs myCAFs and PVL profiles were quantified to compare ILC with NST tumors.

Analyses across discovery and validation cohorts indicate overall similarity in TAM and CAF distributions across subtypes, with evidence for modest increases in specific CAF populations in luminal ILC. These results provide a data resource for further research on the role of tumor microenvironment composition in cancer progression and response to therapy.