How to Build a Data-Sharing Strategy for Pharma Innovation

How to Build a Data-Sharing Strategy for Pharma Innovation

Now more than ever, the eyes of the world are on sponsors to collaborate, sharing their clinical trial data to combat human health emergencies.

While individual patient-level data sharing is largely done on a voluntary basis, privacy is just as important as when clinical studies are published by regulators.

This webinar, held in collaboration with DIA, will investigate the different decisions pharma companies face and look at how these decisions impact brand reputation and public trust.

Featured Topics:

  • Data sharing as a clinical trial sponsor’s social responsibility
  • The real-world cost of not sharing safe, insight-rich data
  • A framework for safely sharing and using sensitive clinical trial data

Learning Objectives:

  • Compare qualitative and quantitative approaches to anonymization
  • Evaluate whether to build an in-house anonymization capability, buy software, or engage a vendor
  • Analyze methods for balancing patient privacy and data utility

Presenters

Niamh McGuinness, PhD, Senior Analyst, Clinical Trial Transparency, Privacy Analytics
Laura Dodd, Global Data Sharing Manager, PRA Health Sciences, Takeda
Jingyi Liu,
Principal Research Scientist, Eli Lilly and Company

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About this webinar

Now more than ever, the eyes of the world are on sponsors to collaborate, sharing their clinical trial data to combat human health emergencies.

While individual patient-level data sharing is largely done on a voluntary basis, privacy is just as important as when clinical studies are published by regulators.

This webinar, held in collaboration with DIA, will investigate the different decisions pharma companies face and look at how these decisions impact brand reputation and public trust.

Featured Topics:

  • Data sharing as a clinical trial sponsor’s social responsibility
  • The real-world cost of not sharing safe, insight-rich data
  • A framework for safely sharing and using sensitive clinical trial data

Learning Objectives:

  • Compare qualitative and quantitative approaches to anonymization
  • Evaluate whether to build an in-house anonymization capability, buy software, or engage a vendor
  • Analyze methods for balancing patient privacy and data utility

Presenters

Niamh McGuinness, PhD, Senior Analyst, Clinical Trial Transparency, Privacy Analytics
Laura Dodd, Global Data Sharing Manager, PRA Health Sciences, Takeda
Jingyi Liu,
Principal Research Scientist, Eli Lilly and Company

Presenter

Niamh McGuinness is a technical lead with Privacy Analytics’ Clinical Trial Transparency (CTT) business unit. Her team works with a variety of clinical trial sponsors that have turned to us to meet the stringent requirements of regulations such as EMA Policy 0070 and Health Canada Public Release of Clinical Information (PRCI). Drawing on her academic research background, Niamh has helped develop Privacy Analytics’ CTT methodology and our proprietary toolsets.

Niamh McGuinness

Senior Manager of Clinical Trial Transparency and Privacy

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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