How Does Roche’s Data Science Team Help Shape the Future of Healthcare?

Laura Aguiar

Laura Aguiar, Ph.D., MBA, MPM, PMP is the Data Science Decision Support Service Manager for Roche Pharmaceutical Research and Early Development Informatics at the Roche Innovation Center in New York.

She’s also a presenter at the Marketing Analytics & Data Science Conference on June 8-10, 2016 in San Francisco, California.

As a preview to her presentation, “Data Science in Early R&D Informatics,” Laura shared how her data science team supports R&D innovation at Roche:

Peggy L. Bieniek, ABC: How does Roche use data to help shape the future of healthcare?
Laura Aguiar: Various types of data are used. For example, market research data is used for constructing/optimizing business strategy, by understanding the physicians’ needs and their expectations for specific disease indication. Genetics and genomics data is used for identifying and assessing biomarkers (predictive drug response biomarkers, drug safety biomarkers, etc.). Real world data (insurance claim data, Electronic Healthcare Record [EHR] data) is starting to be used for optimizing clinical trial study protocols (by understanding disease populations), patient recruitment, etc.

PB: How does R&D informatics support collaboration?
LA: R&D informatics can support collaboration on many levels. It can provide user-friendly collaboration platforms that makes it easier to store and share relevant information in unstructured (file share) and structured databases (for scientific data from collaboration). The R&D informaticians also provide a bridge between collaborators (usually scientists) and Roche, particularly for data and information sharing.
PB: How are big data and data science impacting R&D currently?
LA: We are making use of big data, like Next Generation Sequencing (NGS) data, to identify additional disease indications that certain drugs have the potential to cure (based on their mechanism of action and disease etiology fit) and to identify predictive drug response biomarkers. Using mixed data science capabilities, we combine different types of big data, like NGS, literature, and real world data to support pre-clinical and clinical project teams, scientists, and clinical operation experts.
PB: What will people gain from attending your conference presentation?
LA: People will get insight on the formation and value of a Data Science team in a Research Pharma organization. They will learn how it’s managed, the interface with stakeholders, value through drug project impacts, and employment of a cross-functional team in a global setting.

Want to hear more from Laura Aguiar? Join us at the Marketing Analytics & Data Science Conference. Learn, network and share best practices with the most influential leaders in data science and analytics. Stay connected at #MADSCONF.
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Peggy L. Bieniek, ABC is an Accredited Business Communicator specializing in corporate communication best practices. 

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