Niamh McGuinness, PhD
Associate Director, Safety, Regulatory & Transparency
How to Protect Your Company’s Commercial Interest Under EU CTR
As a clinical trial sponsor, you’re under pressure to be transparent, but how do you ensure your clinical study documents don’t reveal confidential trade secrets when published by regulators?
Starting January 31, when mandatory compliance with EU Clinical Trials Regulation (EU CTR) comes into effect, you’ll need to submit documents for eventual publication much more quickly than you did under EMA Policy 0070 and do under Health Canada PRCI – even if you choose the less-desirable option of deferral.
To help with this, Privacy Analytics offers a complete solution for your clinical document submissions, enabling you to meet your regulatory submission deadlines while protecting patient privacy and identifying and protecting commercially confidential information (CCI).
Join Niamh McGuinness, Senior Advisor, Clinical Trial Transparency and Privacy, to find out how Privacy Analytics can help you:
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.