Bio in 2015 is like software in 2005. The bio fund is really about funding software companies in the bio space.

1. Bio Fund

2. Bio startups that operate like software startups
The emerging macro trend: Bio 2.0
Bio in 2015 is like software in 2005
Software is eating Bio
Cloud biology
emergence of low
CapEx startups
Software at the center
Machine learning,
cloud computing
Minimize FDA Risk
DTC, digital health,
consumer genomics, etc

3. Storage cost-performance and computing cost-performance
Moore’s law: cost of storage, compute ⇒ zero
0.01
0.1
1.
10.
100.
1000.
1994 1996 1998 2000 2002 2004 2006 2008 2010 2012
Dollars($)
Compute cost ($ per 1 million transistors)
Storage cost ($ per gigabyte)

4. Silicon content: $20-22
NAND Flash
$18-20
Display
$15-17
Applications Processor
$8-10
DRAM
$10-13
Baseband
$4-5
RF and FEM
$3-4
Power
Amplifier
$3-4
PMIC
$3-4
Combo-chip
(WIFI/BT/FM)
$3-4
Touch
Controller
$3-4
GPS
$3-4
Image
Sensors
Silicon content: $9-10
Camera Module
$7-11
Touch Panel
$5-6
Battery (Li Polymer)
$3-5
HDI PCB
$1-2
Camera Lens
$2-3
Gyroscope/Accelerometer
$0.70-0.80
Audio
Codecs
$0.50-0.60
Speaker IC
Substrate
$1-2
LCD Drive IC
$0.70-0.80
MEMs Microphone
$1.00-1.50
LCD Drive IC
Moore’s law: cost of storage, compute ⇒ zero
Source: Nomura Securities, Gartner 2013 report.

5. Side benefits of Moore’s law: cost of sensors ⇒ zero
Source: Qualcomm
IntegratedSensors,UserExperiences
Ambient Light
Accelerometer
Magnetometer
Ambient Light
Accelerometer
Magnetometer
Ambient Light
Accelerometer
Magnetometer
Ambient Light
Accelerometer
Magnetometer
Ambient Light
Accelerometer
Magnetometer
Gyroscope
Proximity
Gyroscope
Proximity
Gyroscope
Proximity
Pressure
RGB
Pressure
RGB
Pressure
RGB
Gyroscope
Proximity
Temperature
Humidity
Hall Effect
Temperature
Humidity
Hall Effect
Heart Rate
Fingerprint
2010 2011 2012 2013 2014 2015+
GALAXY 1
GALAXY S2
GALAXY S3
GALAXY S4
GALAXY S5

6. Beyond Moore’s law: cost of sequencing ⇒ zero
Source: Nature, 2014
Cost of genome
sequencing.
Next generation
sequencers enter
the market.
Moore’s law for
computing costs.
The price of
sequencing a whole
human genome hovers
around $5,000 and is
expected to drop even
lower.
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
10,000
1,000
100
10
1
Cost(thousandsUS$)

7. Putting these trends together
This is disrupting traditional biotech
= SOFTWARE IS EATING BIO
Compute Sensors Biology
+ +

8. Bio 2.0 is not Biotech
BIOTECH STARTUPS SOFTWARE STARTUPS
Subject Uncontrollable organisms Perfectly determinate code
Environment Poorly understood, natural Well understood, artificial
Approach Indefinite, random Definite, engineering
Regulation Heavily regulated Basically unregulated
Cost Expensive ( > $1B per drug) Cheap (a little seed money)
Team High-salaried, unaligned lab drones Committed entrepreneurial hackers
& BIO 2.0
From Peter Thiel’s Zero to One

9. Eroom’s law: $/drug exponentially increasing
Source: Nature Biotechnology
$10M
$100M
$1,000M
$10,000M
1949.97 1970.05 1990.11 2010.28
Development$perdrug

10. Bio in 2015 is like software in 2005
SOFTWARE IS EATING BIO
EROOM’S = NO MOORE’S = YES
The emerging macro trend: Bio 2.0

11. Three emerging areas
Cloud Biology Computational MedicineDigital
Therapeutics

12. Slow and expensive to develop
Toxic side effects
FDA regulated
Traditional therapeutics
IMAGE: Champlax

13. Title Text
Subtitle text
Digital therapeutics for chronic
disease
Mobile enables traction, patient
success, and a new model for
insurance companies
Digital health & digital therapeutics
IMAGE: Omada Health

14. Large capital outlay
Poor reproducibility
Empirically driven
doesn’t scale
The four horsemen of Eroom’s law
Traditional biology

15. Title Text
Subtitle text
Biology that works like programming:
Cloud experiments run through software
Cloud biology
IMAGE: Emerald Therapeutics

16. Tsunami of data
Flood of new drugs
Traditional medicine

17. Title Text
Subtitle text
Personalized cancer treatments based on
patient tumor genetic screenings
Computational biomedicine

18. New a16z fund for Bio 2.0
Vijay Pande new GP:
uniquely suited for Bio 2.0
a16z approach
applied to Bio
Bio 2.0 software +
cloud bio, w/o
traditional FDA risk

19. Title Text
Subtitle text

20. Vijay Pande:
Bio2.0 background
Chemistry
Camille and Henry Dreyfus Professor, Stanford Univ.
Thomas Kuhn Paradigm Shift Award, American Chemical
Society Teacher-Scholar Award, Dreyfus Foundation
Physics
AB Princeton University, 1992, PhD MIT, 1995 | Michael and
Kate Bárány Award for Young Investigators, Biophysical
Society Fellow, American Physical Society
Computer Science:
Founder, Folding@home Distributed Computing | MIT TR100
Guinness World Record, Folding@home First to a Petaflop
Netxplorateur of the Year
Biology
Chair, Biophysics, Stanford University Medical School
Delano Award for Computational Biosciences, American Soc.
for Biochem. and Molecular Biology | Irving Sigal Young
Investigator Award, Protein Society

21. Title Text
Subtitle text
Crowd sourced computational
biology for biomedicine
Anticipated the future
Cloud before Loudcloud
GPU computing before CUDA
Crowdsourcing before wikipedia
Founding Director, Folding@home
Approximately 2,000,000
people have donated
computer time.
More processing power than
Amazon Web Services,
Guinness World Record
FOLDING@HOME

22. Title Text
Subtitle text
$900M
Next generation approaches to
therapeutics for infectious disease
Computation at its heart
Regulatory Innovations: drug repurposing
Co-founder, Globavir BioSciences

23. Vijay Pande – Bio & IT entrepreneur
ADVISOR TO STARTUPS IN BIO
Acumen Pharmaceuticals (Alzheimer’s
Disease)
Counsyl (Carrier testing)
Globavir (Infectious Disease)
EMPLOYEE #1 AT NAUGHTY DOG
Started at 15 years old
writing computer games
Naughty Dog later
sold to Sony
ADVISOR TO STARTUPS IN IT
Clearspeed (high speed compute hardware)
Discovery Engine (Semantic search)
Numerate (Computational Drug Design)
Omnipod (Software for pharma)
OpenEye (Software for pharma)
Pharmix (Computational Drug Design)
Protein Mechanics (molecular simulation)
Schrodinger (Software for pharma)
Stack IQ (Cloud software stack)