Rob Scott | Chief Medical Officer, VP, Head of Development

Rob Scott, Chief Medical Officer, VP, Head of Development, AbbVie

Dr Rob Scott is Zimbabwean born and studied medicine at the University of Cape Town. For thirty years Rob has held leadership positions in global Pharma, starting with J&J in South Africa. As the Global Head of CV and Metabolic at Pfizer he was responsible for what was then the world’s largest pharmaceutical product and the largest cardiovascular product – Lipitor and Norvasc. As Executive Vice President of R&D at AtheroGenics in Atlanta Georgia, he designed and implemented the first large cardiovascular outcomes study to be wholly performed by a small biotech. As CMO and Head of Development of Cerenis Therapeutics in Toulouse, France, Rob advanced the science of synthetic HDL. At Amgen, Rob ran the Cardiovascular, Metabolic, Nephrology, Bone, Inflammation and Neuroscience TAs. He also created a Center of Excellence focused on using predictive analytics for designing and implementing clinical trials, called the Development Design Center. Since 2016, Rob has been the Chief Medical Officer and leads Development at Abbvie, in this role, he is a board member of Transcelerate and serves on the PhRMA Biomedical Advisory Committee. Rob was a member of the FDA Cardiac and Renal Drug Advisory Committee from 2012 to 2016 and served on the Endocrine and Metabolic Advisory Committee. Rob has been involved with every therapeutic area and mode of drug delivery as well as both small molecules and biologics.  He invented and developed the first drug combination to simultaneously treat two different disease states - Caduet.


Day One World Pharma Pricing & Market Access EU Congress @ 12:05

Using a Center of Excellence for Clinical Trial and Program Design to support Market Access

  • Driving best practices in soliciting input from Countries, Regions and Market Access professionals during clinical trial design phase.
  • Using RWD to identify patient populations with a combination of high event rates and likelihood to respond to a specific intervention to drive best in class clinical outcomes.
  • Using RWD to identify patient characteristics which predict likelihood of having an adverse event 

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