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Delivering on the Promise of Synthetic Data

Ten Recommendations for Regulating Non-identifiable Data

This article provides ten recommendations on how to regulate the generation and processing of non-identifiable data based on our experiences.

Data Synthesis Platform Available for the PHUSE Community

At a PHUSE workshop in September we organised a half-day session on synthetic data and its applications. l.

CNIL Recommends Against US Service Providers for Processing Health Data – What Does that Mean?

Organizations processing the personal data of EU citizens, and data from France in particular, took note of recent recommendations made by France’s Data Protection Authority (CNIL) following the Schrems II ruling this fall.

Can synthetic data help organizations respond to 'Schrems II'?

Synthetic data has the potential to help address some of the most intractable privacy and security compliance challenges related to data analytics.

PETs and Sharing Clinical Trial Data

Stephen Bamford, Janssen’s Head of Clinical Data Standards & Transparency, discusses the company’s commitment to clinical trial data transparency and sharing, and the ways in which privacy enhancing technologies (PETs) are employed to help fulfill that commitment.

Death to Privacy Shield

Due to contemporary surveillance laws in the United States, on July 16th the European Union’s Court of Justice ruled that E.U. data was not adequately protected under the existing Privacy Shield agreement with the U.S.

PETs to Manage Emerging Privacy Risks

As the pace of technological innovation continues to grow, new risks to consumer and patient privacy are appearing at a rate which could be difficult for regulators to keep up with.

Artificial Intelligence in Health Care - GAO Report

The adoption of Artificial Intelligence (AI) technologies in healthcare could lead to great improvements in efficiency, patient care and medical research, accelerating the discoveries that lead to new cures. 

Managing the Risks from AI Algorithms

In the webinar organized by Replica Analytics in November 2019 entitled "Managing the Risks from AI Algorithms," Daniel Shapiro and Khaled El Emam discussed some of the risks in developing and using AI tools, with an emphasis on healthcare applications.

Reflections on Generating Synthetic Data for the Vivli-Microsoft Data Challenge

In June 2019 we generated synthetic clinical trial data for the inaugural Vivli-Microsoft Data Challenge. The goal of the competition was to propose innovative methods to facilitate the sharing of rare disease datasets, in a manner that maintains the analytic value of the data while safeguarding participant privacy. 

Cutter Publishes Update on Synthetic Data

In May 2019, the Cutter Consortium published an executive update on synthetic data that is intended to inform technology and analytics executives about what synthetic data is and when it can be applied.

Replica Analytics Generates Data for Vivli Innovation Challenge

On 21st June Vivli and Microsoft will be hosting an innovation challenge (datathons) on methods and technologies to perform privacy-protective analysis on rare disease clinical trial datasets. The challenge will take place for a full day in Boston.

Real Data vs Synthetic Data: Propagating Constraints

As we are working through a number of data generation projects, one issue that has come up a few times is the extent to which synthetic data is constrained by original data.