© 2015 Illumina, Inc. All rights reserved.

Illumina, 24sure, BaseSpace, BeadArray, BlueFish, BlueFuse, BlueGnome, cBot, CSPro, CytoChip, DesignStudio, Epicentre, ForenSeq, Genetic Energy, GenomeStudio, GoldenGate, HiScan, HiSeq,

HiSeq X, Infinium, iScan, iSelect, MiSeq, MiSeqDx, MiSeq FGx, NeoPrep, NextBio, Nextera, NextSeq, Powered by Illumina, SureMDA, TruGenome, TruSeq, TruSight, Understand Your Genome, UYG,

VeraCode, verifi, VeriSeq, the pumpkin orange color, and the streaming bases design are trademarks of Illumina, Inc. and/or i ts affiliate(s) in the US and/or other countries. All other names, logos, and

other trademarks are the property of their respective owners.

Turning Big Data

Into Smart Data Brady Davis, Sr. Director, Strategy & Market Development

2

Advance research and make new

medical breakthroughs

– Gives insight into symptoms you

have today

– Suggests symptoms/predisposition

for your future

– Guides drug choices

– Suggests conditions your children

might be at risk for

Based on genetics, environment,

and lifestyle

The Precision Medicine Revolution Better prevention, diagnosis, prognosis, and treatment

3

2010 1st sub-10K genome $10,000

2007 1st NGS Genome $2,000,000

2003 Human Genome Project $3,000,000,000

2006 1st individual genome $20,000,000

2008 1st 30x genome $200,000

2014 1st $1,000 genome $1,000

Enabling Precision Medicine Decreasing cost of sequencing

4

Global NGS Activity

5

Business Driver Healthcare data will be big, real BIG

Omics

Sensor

Electronic Medical Record

Health Info Exchange

Personal Health Record

Claims

Social

Relative volume of healthcare-relevant

data for a given person

6

Healthcare Needs a Comprehensive,

Patient-Centric View of Information

Individual

Therapy Adherence

Family Time

Va

lue

Electronic Health

Information Diet, Lifestyle

and Exercise Environment Genetics

Omics Data

7

Informatics Barriers to Realizing the Promise

Immaturity

Interpretation

Integration

• DIY legacy

• Unprepared for scale

• Tedious curation

• Scarce geneticists

• Multiple point solutions

• Manual processes

8

Infrastructure Maturity: Its “Back to the Future”

9

The Interpretation Conundrum

“People to curate is the slow leg … it’s still largely manual” Dr. Jason Merker, Stanford Hospital

3 billion Base Pairs

1.5 million Variants

1-10 Variants of Significance

10

What Makes Informatics a Challenge And an opportunity in the clinics

Diversity of of

genotypic/ phenotypic

data is daunting

Defined workflows

(mostly) do not exist

Lack of bioinformatics

resources

Underlying science

constantly evolving

Lack of budget

Balance of

security/privacy vs.

need to share

Drives the need for off-the-shelf

informatics solutions

11

We need analytics that can answer the hard

questions like…

Challenge: Multiple Data Sources Make Producing

Usable Analytics Extremely Challenging

These questions may require data from many

source systems to be properly merged

CLINICAL

IMAGING

BILLING

CLAIMS

CENSUS/MARKET

CALL CENTER

BENCHMARK

GENOMICS

CLINICAL TRIALS

BIOBANKS

BASIC RESEARCH

ALL H

OS

PIT

ALS

A

MC

/ L

S

Many Data Silos

Data Integration

Challenging

Lots of Data – Few Insights

• How might the presence/absence of a given

variant guide my treatment decisions?

• How valuable are your samples?

• Is this patient a fast or slow metabolizer of drug

X, Y or Z?

• Do you know the cost associated with storing

samples if not accessed?

• 1 year

• 10 years

• 20 years

• By combining phenotypic & genotypic data with

a patient’s EMR, can we determine the best

therapeutic course?

12

Challenge: Critical Healthcare Provider Information Is

"Unstructured" With Formats Not Addressable With

Current Tools

Data from many disparate

internal systems must be

merged & synthesized

Over 60% of useful data is

often housed in

unstructured data fields

External comparative &

demographic data sources

add more complexity Content Systems,

Files, Email

Web & Social Media

Unstructured Data

Physician Notes

OLTP & ODS

Systems

Enterprise Applications

(Oracle, SAP, Others)

Data Warehouse

& Data Marts

Structured Data

13

Challenge: Current Analytics Creation, Distribution & Consumption

Processes Are Highly Manual at Most Providers

Inefficient, expensive, inflexible processes

Multiple Data

Sources

Manual Data

Manipulation &

Report Distribution

Inconsistent Views

by Recipients, Lack

of Mobility

Genomics

Quality/

Outcomes

Other

Operational

Data

Patient

Accounting

Limiting knowledge workers from making timely decisions when and where they are

needed, reducing overall staff efficiency, and introducing compliance risks

14

The Transformation of Healthcare Will Require the Entire Value Chain to Evolve

Collaborating across the life sciences and healthcare industries improves care, lowers costs and delivers greater value

R&D Productivity

Translational Medicine

Quality & Safety

Personalized Care

Participatory & Preventive Care

Diagnostics

Pharma/Biotech

Medical Devices

Clinical

Research

Care

Delivery

Care

Management

Population/

Global Health

Value-based healthcare

Discovery

Research

15

Our Vision

Advance human health by unlocking

the power of the genome

Advance human health by unlocking

the power of the genome

16

Personal Experiences – How Far Have We

Come

17

Healthcare From a Patient’s Perspective

Only a fraction of “treatments” are evidenced-based

It takes 10+ years for evidence to be widely adopted

Complete care is rendered only 50% of the time

We patients only adhere to our meds 50% of the time

Treatments result in adverse events and even death far too often

All of this is terribly expensive (and we are starting to pay for it)

And, the whole system is not designed by and for us, the patients!

18

Co

nta

ct

Time

Discharge Date

02-25-10

1 Week

03-04-10

1 Month

04-04-10

3 Months

07-04-10

5 Months

12-04-10

Patient’s Healthcare Experience Patient Controlled

Knee/Hip Replacement Patients

4 1/2-hour appointments

Over 5 months time

0.00125% of patient’s healthcare experience

19

Social Network Analysis of Whatcom Medicare

Care Transitions: When Patients Transition Following Hospitalization Where Do They Go?

Data source: All FFS Medicare transitions from part A and part B claims data covering the period 1/1/2009 - 1/31/2010 .

Prepared by Qualis Health, the Medicare Quality Improvement Organization for Washington, under contract with the Centers for Medicare & Medicaid Services (CMS), an agency of the U.S. Department of Health and Human

Services. The contents presented do not necessarily reflect CMS policy.

The Most Central

Receiver of Data in

This Network is

The Home

20

Better Health Through Patient Engagement

Source: World Health Organization – Social Determinants of Health, October 2011

Patient Engagement!

$ 3,000,000,000,000 / yr

21

Photo credit:: David Hallet/The Press

Your Genomic Blueprint

22

All Diseases have a Genetic Component

Cancer Infectious

Complex Disease

“Genetics loads the gun and the

environment pulls the trigger”

– Francis Collins

Mendelian

23

Drug-Centered Oncology Rx: Traditional Approach

The (One) Drug

▶ One drug … that is effective in a small fraction of patients…

▶ Requires a (single-target) CDx for each patient… to identify likely responders

The Patients The “Companion” Test (single-target)

24

Precision Oncology Treatment From companion diagnostics to precision medicine

The Patient Multi-target Test

Target 1

Target 2

Target 3

CRx

The Drug

25

Data Mining

New Knowledge

Published Literature Patient Data (Public, Private)

Literature Curation

New Paradigm: Data-Driven Discovery

Data Standardization

My Population Knowledge

Global Knowledge

My Patient Populations

Global Patient Populations

Patient Knowledgebase Biomarker Knowledgebase

Clinical Translational Clinical Reporting

26

Open Platform Enables Big Data Analytics for

Clinical Genomics

Illumina Platform

Optimized pipeline

or highly skilled

curation team for

ingesting public and

private genomic (&

clinical) data

Highly effective data

correlation engine –

millions of associations

and correlations

pre-computed

Advanced analytical

and visualization tools

offer a means of

exploration & analysis

by experts &

non experts alike

Knowledgebase

Provides annotation,

interpretation

drives report generation

APIs

Secure Data Center

Data Encryption

HIPAA Compliant

27

We Aim to Achieve the Following… Patient to answer in a standardized, integrated platform

LIS

EHR

Billing

Informed

clinical

decision

FDA

CMS

NCCN

CAP/CLIA

Stakeholders

aligned around a

standard

Specimen

processing

Library

preparation

Sequencing

analysis Informatics

28

Clinical evidence

– Patient outcomes

Health Economics

– Operational efficiencies of NGS

– Total costs to the system

Clinical impact through change in management behavior

– Courses of treatment, timing

– Testing

How Will We Know If We’re Succeeding?

© 2015 Illumina, Inc. All rights reserved.

Illumina, 24sure, BaseSpace, BeadArray, BlueFish, BlueFuse, BlueGnome, cBot, CSPro, CytoChip, DesignStudio, Epicentre, ForenSeq, Genetic Energy, GenomeStudio, GoldenGate, HiScan, HiSeq,

HiSeq X, Infinium, iScan, iSelect, MiSeq, MiSeqDx, MiSeq FGx, NeoPrep, NextBio, Nextera, NextSeq, Powered by Illumina, SureMDA, TruGenome, TruSeq, TruSight, Understand Your Genome, UYG,

VeraCode, verifi, VeriSeq, the pumpkin orange color, and the streaming bases design are trademarks of Illumina, Inc. and/or i ts affiliate(s) in the US and/or other countries. All other names, logos, and

other trademarks are the property of their respective owners.

Questions

Brady Davis, Sr. Director, Strategy & Market Development