The Blood Profiling Atlas in Cancer (BloodPAC) Consortium was launched on October 17, 2016 to accelerate the development and validation of liquid biopsy assays to improve the outcomes of patients with cancer.
To do so BloodPAC will develop a collaborative infrastructure that enables sharing of information between stakeholders in industry, academia, and regulatory agencies.
BloodPAC is a consortium managed by the Center for Computational Science Research, Inc. (CCSR), which is an Illinois based not-for-profit corporation.
The goals of BloodPAC are: to aggregate, make freely available, and harmonize for further analysis: i) data from CTC, ctDNA, proteins including tumor associated autoantibodies, and exosome assays, ii) associated clinical data, such as clinical diagnosis, treatment history and outcomes. and iii) sample collection, preparation and handling protocols.
The BloodPAC Consortium includes representatives from academia, private foundations, industry and the government that are working to accelerate the exploration, implementation and assessment of potential clinical utility of liquid biopsies with the aim to understand the temporal evolution of a patient’s disease.
Our mandate is to accelerate the development and validation of liquid biopsy assays to improve the outcomes of patients with cancer. To do so we will develop a collaborative infrastructure that enables sharing of information between stakeholders in industry, academia, and regulatory agencies.
The BloodPAC consortium is committed to open and active membership and considers new applications on a rolling basis. If you would like more information please contact us. If you are interested in joining the BloodPAC you can find membership related materials here.
Lauren Leiman; Executive Director, BloodPAC Consortium
The Data working group provides a secure and compliant data commons to store, harmonize, and analyze blood profiling data submitted by the member organizations.
The Technology Applications working group analyzes the tools used to collect and convert blood profiling samples into datasets.
- Robert L. Grossman - University of Chicago, Open Commons Consortium
- Brandi Davis-Dusenbery - Seven Bridges
- Jake Vinson - Prostate Cancer Clinical Trials Consortium
- Peter Kuhn - University of Southern California
- Muneesh Tewari - University of Michigan
- John Simmons - Personal Genome Diagnostics
- Howard Scher - Memorial Sloan Kettering Cancer Center
- Anne-Marie Martin - Novartis