Dana-Farber Accelerator Cancer Diagnostic Awardee
Following its Fall Diagnostics RFP, the Dana-Farber Accelerator awarded a grant to Margaret Shipp, MD, Chief, Division of Hematologic Neoplasia at Dana-Farber for her work in developing a Classification Tool for Diffuse Large B Cell Lymphoma (DLBCL). Known as DLBclass, the diagnostic platform tool aims to improve the molecular diagnoses, prognostic accuracy, and treatment strategy for the various types of DLBCL. Read more about the project and the team’s recent paper in Blood.
2024 Dana-Farber Accelerator Impact Report
We are excited to announce the release of the 2024 Dana-Farber Accelerator Impact Report! This year’s report highlights some of the latest technological advancements and the significant strides Dana-Farber researchers and their collaborators have made in creating new cancer treatments and diagnostics. Dive into the stories of innovation, collaboration, and impact that define our mission to conquer cancer.
CD45-PET Technology Breaks New Ground in Inflammation Imaging
Mohammad Rashidian, PhD, Principal Investigator, Department of Cancer Immunology and Virology at Dana-Farber, and his team have unveiled a novel imaging technology that promises to recast the detection and monitoring of inflammation. This innovative approach, centered around a CD45-targeted PET probe, offers unprecedented precision in visualizing immune activity, potentially reshaping how inflammatory diseases are diagnosed and treated. Read more.
Predictive Tool for Melanoma has Potential to Guide Immunotherapy Choices
A new study co-led by senior author and melanoma oncologist David Liu, MD, MPH, and published in Science Advances, describes a machine learning-based tool that can predict which patients with melanoma are likely to fare poorly with single-agent therapy and, therefore, might benefit from combination therapy. The tool is not ready for clinical use but suggests the potential to develop a clinically validated tool that could help guide treatment decisions and patient outcomes. Read More.
Deep Learning Model Predicts Immunotherapy Response in Non-Small Cell Lung Cancer
A team of international and local researchers, including Dana-Farber scientists, has unveiled a deep learning model that promises to improve the personalized treatment of patients with advanced non-small cell lung cancer (NSCLC). This innovative technology, detailed in a recent JAMA Oncology paper, leverages artificial intelligence to predict patient responses to immune checkpoint inhibitors. Read More.
You’re Invited – May 2025 Workshop on Engineered Cell-Based Therapies
This spring, the Parker Center for Cancer Immunotherapy (PICI) at Dana-Farber and Friends of Cancer Research are convening experts for a new workshop, Unlocking Next-Generation Therapies: Exploring Innovative Development and Manufacturing Models for Cell Therapies. Held in-person and virtually on Friday, May 9, in Washington, DC, or virtually, presenters will explore innovative models for the development and manufacturing of engineered cell-based therapies. Discussions will focus on overcoming challenges in scalability, production efficiency, and regulatory adaptability to streamline their delivery to patients. Register now.
In other PICI-related news, listen to Elizabeth Mittendorf, MD, PhD, MHCM, Co-Director of the PICI Center at Dana-Farber, share her journey from military surgeon to breast cancer research trailblazer. Now poised to lead ASCO as President in 2026/2067, Dr. Mittendorf is helping drive the next era of breast cancer vaccines and immunotherapy. 🎧 Listen now to the Bench to Fireside podcast From the Front Lines to the Frontiers of Defeating Breast Cancer.