This document discusses translating large datasets into therapies and medical insights. It describes how over 1 trillion points of biological and clinical data are being analyzed across thousands of genes, compounds, and cell types. The goal is to identify new drug targets and repurpose existing drugs for additional diseases. As an example, a drug used for seizures was found to help a rat model of inflammatory bowel disease. Open data from clinical trials is also being reanalyzed to find new predictors of patient responses and outcomes. The work involves collaborations across multiple research institutions and industries.

1. Translating a Trillion Points of Data into
Therapies and New Insights in
Health and Disease
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
– 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
– Thomson Reuters
– Intel
– SAP
– SV Angel
– Progenity
• Speakers’ bureau
– None
• Companies started by students
– Carmenta
– Serendipity
– NuMedii
– Stimulomics
– NunaHealth
– Praedicat
– MyTime
– Flipora

3. bit.ly/genedata

4. 5,178 compounds
· 1,300 off-patent FDA-approved drugs
· 700 bioactive tool compounds
· 2,000+ screening hits (MLPCN and others)
3,712 genes (shRNA + cDNA)
· targets/pathways of FDA-approved drugs (n=900)
· candidate disease genes (n=600)
· community nominations (n=500+)
15 cell types
· Banked primary cell types
· Cancer cell lines
· Primary hTERT immortalized
· Patient derived iPS cells
· 5 community nominated

6. @AssayDepot

9. Validation methods are increasingly
commoditized

12. Rat colonoscopy Rat with
Inflammatory
Bowel Disease
Inflammatory
Bowel Disease
After
Anti-seizure Drug
bit.ly/scitmtop
Anti-seizure drug works against a rat model of
inflammatory bowel disease
Joel Dudley
Marina Sirota

13. Psychiatric Drug Imipramine Shows Significant Activity
Against Small Cell Lung Cancer
Vehicle control Imipramine
p53/Rb/p130
triple knockout
model of SCLC
Mice dosed after
tumor formation
Joel Dudley
Nadine Jahchan
Julien Sage
Alejandro Sweet-Cordero
Joel Neal
@NuMedii

14. Need more drugs
for more diseases
Public big data
available
NIH funding
Data analyzed,
method designed
Company launched,
ARRA, StartX,
Stanford license,
first deal
Claremont Creek,
Lightspeed ($3.5
million)
@NuMedii

15. bit.ly/immport
The next big open data: clinical trials
Download 100+ studies today
Jeff Wiser
Patrick Dunn
Sanchita Bhattacharya

16. Reanalyzing RAVE
• Rituximab in ANCA-Associated Vasculitis (RAVE) trial of new approach to
the induction of remission
– randomized
– double-blind
– double-dummy
– active-controlled
– non-inferiority

17. RAVE re-analysis
• 63 of the 99 patients in the rituximab group (64%) reached the
primary end point, as compared with 52 of 98 in the control group
(53%).
• The treatment difference of 11% points between the groups met the
criterion for non-inferiority (P<0.001).
In retrospect, do any measured factors
predict response?
Mazen Nasrallah
Nasrallah M, …, Butte AJ. Arthritis Research & Therapy (2015) 17:262.

18. Nasrallah M, …, Butte AJ. Arthritis Research & Therapy (2015) 17:262.
ANCA-
associated
Vasculitis
Profiled
Therapy
~ 54% of patients
Non-profiled
Therapy
~46% of patients
Treat with
Rituximab
~ 30% of patients
Remission Rate ~ 83%
Treat with
Cyclophosphamide
~24% of patients
Remission Rate ~ 66%
Do not treat with
Cyclophosphamide
Failure rate ~ 67%
Do not treat with
Rituximab
Failure rate ~ 70%
GI ≤ -9.25%
OR
GI ≥ 47.6%
GI ≤ -9.25% GI ≥ 47.6%
Treat with either Rituximab or
Cyclophosphamide
according to best clinical judgement
Average Remission Rate ~ 60%
Non-profiled
Therapy
100% of patients
NO
Proposed
Method
Current
Method
Measure the Granularity Index
(GI)
YES
Mazen Nasrallah

19. Institute for Computational Health Sciences

20. Collaborators
• Jeff Wiser, Patrick Dunn, Mary Shaffran / Northrop Grumman
• Ashley Xia and Quan Chen / NIAID
• Takashi Kadowaki, Momoko Horikoshi, Kazuo Hara, Hiroshi Ohtsu / U Tokyo
• Kyoko Toda, Satoru Yamada, Junichiro Irie / Kitasato Univ and Hospital
• Shiro Maeda / RIKEN
• Alejandro Sweet-Cordero, Julien Sage / Pediatric Oncology
• Mark Davis, C. Garrison Fathman / Immunology
• Russ Altman, Steve Quake / Bioengineering
• Euan Ashley, Joseph Wu, Tom Quertermous / Cardiology
• Mike Snyder, Carlos Bustamante, Anne Brunet / Genetics
• Jay Pasricha / Gastroenterology
• Rob Tibshirani, Brad Efron / Statistics
• Hannah Valantine, Kiran Khush/ Cardiology
• Ken Weinberg / Pediatric Stem Cell Therapeutics
• Mark Musen, Nigam Shah / National Center for Biomedical Ontology
• Minnie Sarwal / Nephrology
• David Miklos / Oncology

21. Support
• University of California, San Francisco
• National Institutes of Health
• March of Dimes
• Juvenile Diabetes Research Foundation
• Hewlett Packard
• Howard Hughes Medical Institute
• California Institute for Regenerative Medicine
• Luke Evnin and Deann Wright (Scleroderma Research Foundation)
• Clayville Research Fund
• PhRMA Foundation
• Stanford Cancer Center, Bio-X, SPARK
• Tarangini Deshpande
• Sam Hawgood
• Keith Yamamoto
• Isaac Kohane
Admin and Tech Staff
• Mary Lyall
• Mounira Kenaani
• Kevin Kaier
• Boris Oskotsky