Privacy Analytics > Resources > Events > Safely Accelerate Clinical Document Submissions While Protecting Commercially Confidential Information (CCI)
Safely Accelerate Clinical Document Submissions While Protecting Commercially Confidential Information (CCI)
Date of Event: March 9, 2023
Location: Virtual Event
As a clinical trial sponsor, you’re under tight timelines to balance participant privacy and data utility in clinical document submissions while justifying and protecting commercially sensitive information.
To help with this, Privacy Analytics offers a complete, end-to-end solution for your clinical document submissions.
You’ll ensure your competitive edge by meeting deadlines for initiatives such as EU CTR, Health Canada PRCI, and EMA Policy 0070 while protecting participant privacy and identifying and protecting commercially confidential information (CCI).
Join Niamh McGuinness, Senior Advisor, Clinical Trial Transparency and Privacy, on March 9 to find out which combination of our flexible solutions best meets your needs:
Niamh McGuinness is an expert in clinical trial document submissions and a senior member of the Privacy Analytics team, focused on Clinical Trial Transparency (CTT). She has personally managed many successful projects, with documents representing hundreds of clinical trials. Under her watch, no client has ever missed a regulatory submission deadline or a deadline to make their trial data publicly available.
Niamh’s team works with a variety of clinical trial sponsors that have turned to Privacy Analytics to meet the stringent requirements of regulations such as EMA Policy 0070, Health Canada Public Release of Clinical Information (PRCI), and EU CTR.
Niamh McGuinness, PhD
Associate Director, Safety, Regulatory & Transparency
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.
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.
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.
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.
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.