Presentation on Research Reproducibility at Friends of the National Library of Medicine on June 10, 2016.

1. Thoughts on reproducibility
atul.butte@ucsf.edu
@atulbutte
Atul Butte, MD, PhD
Director, Institute for Computational
Health Sciences
University of California, San Francisco

2. Conflicts of Interest
• Scientific founder and
advisory board membership
– Genstruct
– NuMedii
– Personalis
– Carmenta
• Honoraria for talks
– Lilly
– Pfizer
– Siemens
– Bristol Myers Squibb
– AstraZeneca
– Roche
– Genentech
– Warburg Pincus
• Past or present consultancy
– Lilly
– Johnson and Johnson
– Roche
– NuMedii
– Genstruct
– Tercica
– Ecoeos
– Helix
– Ansh Labs
– Prevendia
– Samsung
– Assay Depot
– Regeneron
– Verinata
– Pathway Diagnostics
– Geisinger Health
– Covance
– Wilson Sonsini Goodrich & Rosati
– 10X Genomics
– Medgenics
– GNS Healthcare
– Gerson Lehman Group
– Coatue Management
• Corporate Relationships
– Northrop Grumman
– Aptalis
– Allergan
– Astellas
– Thomson Reuters
– Intel
– SAP
– SV Angel
– Progenity
– Illumina
• Speakers’ bureau
– None
• Companies started by students
– Carmenta
– Serendipity
– NuMedii
– Stimulomics
– NunaHealth
– Praedicat
– MyTime
– Flipora

4. bit.ly/genedata

5. bit.ly/geobrca

6. bit.ly/immport
The next big open data: clinical trials data
immport.org

7. Public microarray data led to
• Novel receptor in type 2 diabetes
• Mouse knockout model
• Human serum companion diagnostic
• Prototype drug for type 2 diabetes
Integrating publicly-available data yielded CD44 as a new targetable receptor for
type 2 diabetes

8. Use contract research services for the parts of research you don’t do well

10. Share successful, failed, and so-so data
• Rituximab in ANCA-Associated Vasculitis (RAVE) trial of new approach to
the induction of remission
• But even though rituximab was found to be non-inferior than
cyclophosphamide, which drug is the right one to use?

11. The five lessons I’ve learned in the past 18 years
• Be careful asking for standard procedures, or you will risk over-fitting
those standard models
• Make data and computational methods publicly available, no exceptions
for clinical or clinical trials data
• Wisdom of the crowd approach: trust what you see in common across
experiments
• Outsource the problematic parts to experts or companies
• Failed, successful, and so-so studies should all be shared