Navigating Transparency Requirements Under the EU CTR with AI/ML-driven Solutions
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.
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.
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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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.
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.
Situation: Needed to ensure the primary market research process was fully compliant with internal policies and regulations such as GDPR.
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of voice-to-text data under Shrems II.
This course runs on the 2nd Wednesday of every month, at 11 a.m. ET (45 mins). Click the button to register and select the date that works best for you.