Biomarkers for Diagnosis and Drug Development: A Data Science Approach (B4D-ARC)

Co-Directors:

Project 1: Weining Lu
Project 2: Manju Subramanian
Project 3: Joel Henderson
Project 4: Liang Hao

Initiated: November 2024

ARC Summary

The mission of the Innovative Technology and Novel Biomarker Discovery and Development for Disease Diagnosis and Treatment (B4D-ARC) is to bring investigators together across the Boston University Medical Campus (BUMC: https://www.bumc.bu.edu/), Boston Medical Center (BMC: https://www.bmc.org/) and Charles River Campus (CRC: https://www.bu.edu/tag/charles-river-campus/) to conduct translational cross-disease biomarker research to improve disease diagnosis and treatment. The B4D-ARC will comprise four research projects and two cores with more than 50 investigators and trainees from the Department of Medicine, Ophthalmology, Pathology, Neurology, BUMC Data Science Core, and DOM Research Cores at BU/BMC, and the Biomedical Engineering Department at CRC.

This ARC will focus on generating interdisciplinary research ideas for biomarker discovery and novel therapeutic development using new technology and a data science approach, forming new collaborations to publish jointly, and applying for muti-PI external grants. It will also establish a mechanism for sharing knowledge, data, and resources across four research projects in this ARC and provide trainees with new education opportunities in biomarker and data science translational research.  Monthly meetings, seminars, and annual research symposiums will be organized regularly.

The B4D-ARC is co-directed by Drs. Weining Lu (Project 1 in Cardiovascular–Kidney–Metabolic biomarker research), Manju Subramanian (Project 2 in Ophthalmology and Neurology biomarker research), Joel Henderson (Project 3 in Pathology, Laboratory Medicine, and Imaging biomarker research), and Liang Hao (Project 4 in Biomedical Engineering and non-invasive biomarker discovery), together with other investigators in different departments and research cores at BU/BMC.

The data science and machine learning tools and high-quality datasets that will be used in this B4D ARC include but are not limited to the following databases: KPMP (https://atlas.kpmp.org/), AI-READI (https://aireadi.org/), dkNET (https://dknet.org/), PanKbase (https://hirnetwork.org/consortium/pankbase), and NIDDK-CR-R4R (https://repository.niddk.nih.gov/home/).