Navigating Transparency Requirements Under the EU CTR with AI/ML-driven Solutions

Navigating Transparency Requirements Under the EU CTR with AI/ML-driven Solutions

How Can AI/ML Help with EU CTR?

About this webinar

As a clinical trial sponsor, the EU Clinical Trials Regulation (CTR) rules that become mandatory on January 31, 2023, will present new scalability challenges when it comes to ensuring that you maintain compliance and privacy protection throughout the clinical trial lifecycle.

This will be especially true during the trial setup and execution phases, which will require the publication of many documents not included in the scope of the previous EU Clinical Trial Directive.

In this webinar, David Di Valentino, PhD, AI/ML Solutions Lead at Privacy Analytics, shows you how AI/ML approaches combined with redaction and anonymization can help sponsors navigate the new transparency landscape under EU CTR.

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About this webinar

As a clinical trial sponsor, the EU Clinical Trials Regulation (CTR) rules that become mandatory on January 31, 2023, will present new scalability challenges when it comes to ensuring that you maintain compliance and privacy protection throughout the clinical trial lifecycle.

This will be especially true during the trial setup and execution phases, which will require the publication of many documents not included in the scope of the previous EU Clinical Trial Directive.

In this webinar, David Di Valentino, PhD, AI/ML Solutions Lead at Privacy Analytics, shows you how AI/ML approaches combined with redaction and anonymization can help sponsors navigate the new transparency landscape under EU CTR.

Presenter(s)

David Di Valentino applies his expertise in data science and data analysis to help clinical trial sponsors maximize the analytical value of their data, while meeting global standards for patient privacy. Before joining Privacy Analytics, David had an extensive academic research career in particle physics. He published a number of papers, and gained expertise in software development, machine learning and data analysis.

David Di Valentino

CTT Data Scientist

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Archiving / Destroying

Are you unleashing the full value of data you retain?

Your Challenges

Do you need help...

  • Unleashing the full value of retained data so they can be put to work safely and responsibly in line with privacy regulation?
  • Defining and implementing effective archival and disposal processes for personal data?

OUR SOLUTION

Value Retention

  • Retain the business value in your data through anonymization.
  • Ensure compliance in your retention & destruction strategy.
  • Maximize the reuse of information by removing what is personal.

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.

Read the full story >

Evaluating

Are you achieving intended outcomes from data?

Your Challenge

Do you need help...

  • Optimizing the use / analysis of data to achieve your organization’s intended outcomes with measured success?

OUR SOLUTION

Unbiased Results

  • Reduce / minimize risk of bias in your data for machine learning.
  • Ensure transparency, fairness, and AI ethics / compliance.
  • Ensure data ethics & compliance in your data models and 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.

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Accessing

Do the right people have the right data?

Your Challenges

Do you need help...

  • Ensuring the right people have access to the right data at the right times?

OUR SOLUTION

Usable and Reusable Data

  • Enable internal access and / or external sharing of data for primary and / or secondary uses.
  • Ensure data are useful and reusable in alignment with FAIR principles.
  • Ensure data have the right level of privacy protection for the use.

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.

 

See the full story >

Maintaining

Are you empowering people to safely leverage trusted data?

Your Challenges

Do you need help...

  • Maintaining / processing data securely and efficiently to promote data enablement with auditable proof of compliance?

OUR SOLUTION

Security / compliance efficiency

  • Creating synthetic versions of data to be used for innovation / AIML.
  • Applying data minimization principles to reduce your risk exposure.
  • Transforming your data for secondary uses and access.

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.

 

Visit ASCOPubs.org to read the full story >

Acquiring / Collecting

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

Your Challenge

Do you need help...

  • Ensuring the acquisition / collection of the right data under the appropriate consent / contracts to maintain corporate integrity?

OUR SOLUTIONS

Consent / Contracting strategy

  • Developing a consent / contractual framework for collecting / sourcing.
  • Creating a comms strategy for internal / external stakeholders.
  • Ingesting and transforming data safely to earn trust.

Client Success

Client: IQVIA

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

 

Read the full story >

Planning

Are You Effectively Planning for Success?

Your Challenges

Do you need help...

  • Defining a clear data strategy to achieve desired outcomes?
  • Getting it right at the start to avoid costly privacy missteps later?

OUR SOLUTION

Build privacy in by design

  • Building privacy into your data plan / platform / pipeline upfront.
  • Establishing a trusted data strategy (ethics, compliance, privacy).

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.

 

Visit Nuance.com to read the full story >

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