Current trends in data science for pharma – findings from a qualitative survey and what we should do about it!

Interview with Ursula Garczarek

Do you want to learn where the health sector might be heading in terms of data science?

Do you understand the opportunities and barriers in terms of the application of data science?

Are you prepared to learn the individual skills needed for these changes?

Then this interview with Ursula from Cytel provides you with the relevant answers. We are talking about:

• What is big data, data science, machine learning and AI?
• How was the survey run by Cytel?
• What data sources will play an important role?
• What do we hope to get out of applying data science given that more and more companies have dedicated resources in this area?
• What are the barriers for achieving these goals? How can we overcome them?
• Will RCTs become obsolete in the future?
• What can statisticians do to prepare themselves for the future?

About Ursula Garczarek

Ursula Garczarek, Ph.D. is an Associate Director of Strategic Consulting at Cytel. She has extensive experience in providing statistical support for clinical and non-clinical aspects of product development within both pharmaceutical and consumer companies. 

As a member of Cytel’s Strategic Consulting team, Ursula provides guidance to trial sponsors on optimizing their development strategy, and successfully implementing trial design innovations. She applies new and pragmatic methodologies to address the needs and requirements of the sponsor within the regulatory environment.

Prior to Cytel, Ursula was the Program Leader Data Science at Unilever R&D (NL), and Biostatistician at Roche Diagnostics GmBH (DE) developing multi-marker diagnostics based on proteomics and metabonomics approaches. She received her Ph.D. from the University of Dortmund (DE), in context of a project on Machine Learning and Statistics within a collaborative research center on complexity reduction in high-dimensional data spaces.

References:

• Data sciences – bridging the gap article
• Data science survey results