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BostonGene and Kyoto University Establish Strategic Partnership to Advance Biomarker Discovery for Combination ImmunotherapyBostonGene, the developer of the leading AI model for tumor and immune biology, today announced a strategic research partnership with Kyoto University, a research institution known for its groundbreaking advancements in medicine and science. The partnership supports a multicenter, Phase II clinical trial led by Dr. Manabu Muto of Kyoto University, evaluating the safety and efficacy of a combined therapeutic approach using immune checkpoint inhibitors (ICI) and photodynamic therapy (PDT) for patients facing advanced gastrointestinal cancers. The study is being conducted as an investigator-initiated trial with financial support from Meiji Seika Pharma Co., Ltd. "By combining PDT with ICIs, our goal is to enhance anti-tumor responses in patients where current treatment options remain limited," said Dr. Manabu Muto, Professor at Kyoto University. "Applying BostonGene's AI-driven molecular and immune system profiling capabilities allows us to better characterize the tumor microenvironment and identify the biological features associated with durable clinical benefit. Ultimately, this work will help us support more precise and personalized therapeutic strategies for patients with advanced cancers." BostonGene will apply its multimodal AI analytics platform to ntegrate genomic, transcriptomic, immune, and clinical data generated through the study, identifying molecular signatures and immune-response patterns associated with therapeutic response and resistance to establish a biologically grounded framework for future patient stratification and combination therapy development. "Integrating advanced AI-driven multiomics analysis into clinical development is essential for accelerating and de-risking next-generation oncology therapeutics," said Yukimasa Shiotsu, PhD, President of BostonGene Japan. "This partnership allows us to better understand the biological mechanisms underlying response to ICI and PDT combination therapy and identify the patient populations most likely to benefit from these approaches." Insights generated through this study are expected to support future clinical trial design decisions, biomarker-driven patient selection strategies, and broader for development efforts involving combination immunotherapy approaches.
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