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  • Pauline Lavigne

Data Science and Information Technology Revolutionizing Clinical Trials

Thursday, December 3rd: 5:30 – 7:30 pm

Artificial Intelligence, Machine Learning, Data Science… Are they here or are they still just something out of a Steven Spielberg movie? Well, yes they are here. Are you ready? Do you know what they mean, and how to make optimal use of them in your clinical trials? In a rapidly changing field, come learn how to benefit from digital technology in the design and conduct of your clinical trials.

This session will be chaired by two of the top research directors in the USA. Dr. Adrian Hernandez is Vice Dean for Clinical Research at the Duke University School of Medicine in Durham, NC, USA, and Dr. Harlan Krumholz is Director of the Center for Outcomes Research and Evaluation at Yale-New Haven Hospital in New Haven, CT, USA.

Topics in this session include use of Electronic Medical Records (EMRs), artificial intelligence, simulated outcome modelling, and automated endpoint adjudication in clinical research. Joining the co-chairs, and Dr. David Kao (Colorado, USA), are representatives from corporations in the health technology field including: Dr. Jianying Hu (IBM, USA), François Henri Boissel (Novadiscovery, France), Dr. Thomas Clozel (Owkin, France), and Abraham Gutman (AG Mednet, USA).

But…. There are always the concerns about patient privacy. How do we protect patient rights? To learn the current state-of-the-art, join Dr. Ivor Pritchard from the Office for Human Research Protections in the USA, who is an expert in research ethics and federal policy, moral and civic education research and practice, and education policy. Nikolai Brun (EMA, DEN), and Bakul Patel (FDA, USA) will further enhance the session by providing regulatory viewpoints.

We know you will have a lot of questions, so please stay tuned after the presentations for the moderated, multi-stakeholder debate.

Making CV Precision Medicine Become a Reality

Thursday, December 3rd: 7:30 – 9:30 pm Advances in disease stratification tools, such as molecular and imaging technologies, will help to identify more specific patient populations. This will help to


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