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

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.