23andMe: The Power of Genetic Information

October 17, 2017
Free for AMIA members; $50 for non-members
Shirley Wu, PhD

What happens when you democratize DNA? 23andMe started 12 years ago with the belief that when you break down barriers to genetic information, you enable revolutions in healthcare and research. With the largest genotyped, phenotyped, consented and recontactable database of individuals in the world, we can do research in unprecedented ways. Find out how we are leveraging these capabilities in scientific discovery, therapeutics, and consumer product development.

The audience for this webinar are those who believe consumers will power the future of genetic research.

Learning Objectives

After participating in this activity, the learner should be better able to:

  • Describe the characteristics of 23andMe’s research platform
  • Understand the value of engaging individuals in research
  • Discuss how 23andMe is utilizing its platform to advance research, therapeutics, and consumer genetic products

Speaker Information

Shirley Wu, PhD
Director, Product Science

Shirley Wu is Director of Product Science at 23andMe, where she’s led the team responsible for scientific curation and content development since 2010. The Product Science team at 23andMe is critical both on the front lines in communicating complex scientific information to consumers, and behind the scenes in demonstrating clinical validity and user comprehension of the health product to the FDA, which has led to the industry’s first ever regulatory authorizations for direct-to-consumer genetic reports. While continuing to support new regulatory paths for consumer genetics, Shirley’s team has a growing focus on leveraging machine learning and the more-than-2-million strong 23andMe research database to create even more powerful ways for individuals to connect to their genetics.

Shirley is an East Coast native, receiving a B.S. in Computational Biology from Brown University before heading West for her graduate studies. She earned her PhD in Biomedical Informatics from Stanford University, developing computational methods for protein function prediction under the mentorship of Russ Altman.