Anonymized clinical trial data and documents

Sponsor boosts data-sharing throughput to 35+ studies a month

Includes clinical trial data and docs

The challenge

A large, global pharmaceutical sponsor needed to safely share a higher volume of clinical trial data and documents to achieve multiple goals. Driving greater advances in patient health, achieving transparency with external researchers and fueling its drug innovation were among the company’s key priorities.

At the same time, it needed to comply with many data privacy regulations. This included submissions to the European Medicines Agency under Policy 0070 and to Health Canada in line with the Canadian Public Release of Clinical Information (PRCI).

The sponsor required an end-to-end anonymization solution to help it achieve all its business needs.

The solution

Privacy Analytics’ health data experts, in conjunction with proprietary software, anonymized the sponsor’s data and documents using a proven statistical method.

The Privacy Analytics Platform was used to anonymize the sponsor’s clinical trial data. The product is designed to automate the anonymization of high volumes of clinical data sets. It delivers highly useful information for health research that’s compliant with global privacy regulations.

The results

  • Ramped up data-sharing throughput to over 35 studies per month, each comprised of structured data and a clinical study report document.
  • Consistency in approach across documents and data, allowing for linkage to documents by data scientists working on structured data.
  • Cost efficiencies attained through highly efficient data sharing program and cross-leverage of the same anonymization capability and solution.

Privacy Analytics can help your company quickly anonymize structured patient data and documents.

Archiving / Destroying

Are you unleashing the full value of data you retain?

Your Challenges

Do you need help...

OUR SOLUTION

Value Retention

Client Success

Client: Comcast

Situation: California’s Consumer Privacy Act inspired Comcast to evolve the way in which they protect the privacy of customers who consent to share personal information with them.

Evaluating

Are you achieving intended outcomes from data?

Your Challenge

Do you need help...

OUR SOLUTION

Unbiased Results

Client Success

Client: Integrate.ai

Situation: Integrate.ai’s AI-powered tech helps clients improve their online experience by sharing signals about website visitor intent. They wanted to ensure privacy remained fully protected within the machine learning / AI context that produces these signals.

Accessing

Do the right people have the right data?

Your Challenges

Do you need help...

OUR SOLUTION

Usable and Reusable Data

Client Success

Client: Novartis

Situation: Novartis’ digital transformation in drug R&D drives their need to maximize value from vast stores of clinical study data for critical internal research enabled by their data42 platform.

 

Maintaining

Are you empowering people to safely leverage trusted data?

Your Challenges

Do you need help...

OUR SOLUTION

Security / compliance efficiency

CLIENT SUCCESS

Client: ASCO’s CancerLinQ

Situation: CancerLinQ™, a subsidiary of American Society of Clinical Oncology, is a rapid learning healthcare system that helps oncologists aggregate and analyze data on cancer patients to improve care. To achieve this goal, they must de-identify patient data provided by subscribing practices across the U.S.

 

Acquiring / Collecting

Are you acquiring the right data? Do you have appropriate consent?

Your Challenge

Do you need help...

OUR SOLUTIONS

Consent / Contracting strategy

Client Success

Client: IQVIA

Situation: Needed to ensure the primary market research process was fully compliant with internal policies and regulations such as GDPR. 

 

Planning

Are You Effectively Planning for Success?

Your Challenges

Do you need help...

OUR SOLUTION

Build privacy in by design

Client Success

Client: Nuance

Situation: Needed to enable AI-driven product innovation with a defensible governance program for the safe and responsible use
of voice-to-text data under Shrems II.

 

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