De-identified data fuels AI-driven drug differentiation

De-identified data fuels AI-driven drug differentiation

Client Context

  • Global pharma company consolidating large volumes of patient data into a diverse data platform.
  • The goal is to improve drug development by unleashing the power of artificial intelligence.

Business Challenge

  • Unlocking the value of clinical study data for internal use with highly automated de-identification.

Privacy Analytics Solution

  • Using Eclipse, the company will de-identify thousands of clinical studies, achieving high-utility data that is compliant with global privacy regulations.
  • Eclipse enterprise-class anonymization software provides auditable proof that the company is taking legally defensible steps to protect the privacy of clinical trial participants.
  • In addition to trial-specific features for real world evidence, Eclipse provides capability to anonymize other data types (e.g. DICOM headers) and measure the risk of re-identification for various disclosure contexts (e.g. external researchers).

Business Impact

  • The company is now well positioned to transform life sciences and change the way medicines are developed.
  • Competitive advantage by leveraging best-of-breed anonymization software that is proven across diverse tech environments globally.

Discover our Eclipse Trials software and how it can help your business.

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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