Project Data Sphere's Data Sharing Platform
Welcome to the leading oncology open access data sharing platform. We host de-identified patient-level data contributed by industry, academia, and PDS research programs.
Register for Access
Register now for full access to our datasets and powerful SAS® tools, or to share your data.
Registration is quick and easy. There are no fees, and no research proposal is required.
Learn More
For more information about Project Data Sphere, our talented team, and ongoingresearch initiativesvisit ourparent site.
To learn more about how our data has been used to advance science visit our listed of peer-reviewed journalpublications.
PDS Platform Announcements
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Our Mission
Improve outcomes for cancer patients by openly sharing data, convening world-class experts, and collaborating across industry and regulators to catalyze new scientific insights that accelerate effective treatments to patients.
Our Data
>205
Patient Level Datasets
>260k
Patient Lives
>18
Data Providers
>135
Peer-Review Publications
Data is being used to drive new research and treatment methods, develop innovative technology (ML/AI models), and more efficiently plan and design clinical trials. Data contained on the PDS platform is made available through contributions from industry and key partnerships in academia, research, and government
This data is de-identified, patient-level, randomized clinical trial data and linked or enriched data sets. To learn more about how researchers leverage the data on our platform, please visit our list of peer-reviewed journalpublications.
Through an active funding partnership with the Robert Wood Johnson Foundation, PDS has been able to offer enriched randomized clinical trial data containing socioeconomic information prepared by RTI International and made available by theAgency for Healthcare Research and Quality's Medical Expenditure Panel Survey information.
SAS® Analytics Tools
Registration includes access to powerful SAS analytics tools at no cost.
Life Sciences Analytics Framework (LSAF)Securely analyze datasets using Base SAS®, SAS/STAT®, and SAS/GRAPH®.
Visual Data Mining and Machine Learning (VDMML)Scalable, in-memory processing environment combines data wrangling, exploration, statistical, data mining and machine learning techniques.
