The Health Industry Forum

October 12, 2006

Mara G. AspinallPresidentGenzyme Genetics

Themes for today

Diagnostics (both genetic and non-genetic) to play larger role in the future

Evolving toward sustainable business models

Policy decisions needed today to support innovation and improved outcomes

Diagnostics: Key to unlocking the power of genome dataDiagnostics: Key to unlocking the power of genome data

Source: Lab Industry Strategic Outlook 2005; Frost & Sullivan

Testing segment

Drugs of abuse

Routine

Revenues, 2003

28.5

Cytology 1.3

0.9

Anatomic pathology 5.8

Esoteric 3.7

14

9

$ Billions %

71

3

2

Growth, 2001- 2003% CAGR

5

12

(5)

7

15

Requires board-certified pathologist. Includes complex cancer diagnostics

Too complex & low volume for most hospitals, physician offices and routine independent labs

Description

Predominantly urine tests required by employers

Relatively simple and common tests

Predominantly Pap testing

Total 40.2 100 8

Genetic testing accounted for ~$1.2 billion in 2003

Diagnostics: Genetic testing accounts for ~3% of Dx industryDiagnostics: Genetic testing accounts for ~3% of Dx industry

U.S. Laboratory Industry, 2001 2003 Segments including genetic testing

Source: Frost & Sullivan

Infectious disease

Pharmacogenetic testing

Prenatal & newborn screening

Predictive testing

Diagnostics: Genetic testing spans multiple disease areasDiagnostics: Genetic testing spans multiple disease areas

U.S. genetic testing market, 2003100% = $1.2 billion

6%7%

25%63%

Diagnostics: Valuable information at modest cost

Source: Lab Industry Strategic Outlook 2005; AdvaMed

Rx & Dx as components of national healthcare spending, 2000 2003$ billions

$122

$33 $40$48

$184

$280

2000 2003 2006E

CMS Clinical Laboratory Fees in real terms, 1984 2004Index: 1984 = $1.00

$1.00

$0.75

1984 2004

15% CAGR

7% CAGR

Testing is 70% of decisions

Therapeutics

Diagnostics

Diagnostics: Genetic testing provides tools to personalize treatmentDiagnostics: Genetic testing provides tools to personalize treatment

What is the most accurate diagnosis?

How severe is their disease?

Are they at risk for disease?

Diagnosis &Stratification

What Rx is appropriate for this patient?

What drug will they respond to?

Will they have an adverse reaction?

Drug selection

Clinical decision being made Examples Dx-Rx

BCR-Abl Gleevec

ER/PR Tamoxifen

5Q deletion - Revlimid

1

HER2 expression Herceptin

EGFR expression Erbitux

EGFR mutation Tarceva, Iressa

BCR-Abl mutation Gleevec

What dose is appropriate for this patient? UGT1A1 polymorphism Camptosar

CYP450 polymorphism Multiple

Dose selection

Is this patient responding to therapy? BCR-Abl RT-PCR Gleevec

CLL MRD Campath

Patient monitoring

2

3

4

Feb. 2005 PriceWaterhouseCoopers report titled Personalized Medicine: the Emerging Pharmacogenomics Revolution Nov. 2005 Thomas Weisel Partners report titled Beneficiaries of Personalized Medicine and Market UpdatePharmacogenetics and the concept of individualized medicine published in The Pharmacogenomics Journal (Vol 6, Pg 16-21).Molecular Diagnostics and Personalized Medicine 2003, Drug & Market Development August 2003

Need for Change:Strong case for personalized medicineNeed for Change:Strong case for personalized medicine

50% of drugs not efficacious as prescribed

FDA interested in biomarkers and diagnostic algorithms

US diagnostics spending decreased since 1984

Adverse drug reactions 6th leading cause of death

US drug spending $250+B per year and growing fast

Building the Case for Personalized

Medicine

Successful when it leads to innovation and

improves standard of

care.

Fails when we settle for Trial

and ErrorMedicine as the

standard of care.

Need for Change:Current system - Cycle of trial and errorNeed for Change:Current system - Cycle of trial and error

Need for Change:Current System Intervention is often lateNeed for Change:Current System Intervention is often late

Health Care Cost vs. Disease Progression

Dis

ease

Bur

den

Baseline Risk

EarliestMolecular DetectionInitiating

Symptoms

Earliest Clinical

Detection

Typical Current

Intervention

Time

Cost / 1/R

eversibility

Source: Model by Ralph Snyderman, Duke University

Increase inantibiotic use Increase in

resistant strains

Ineffective empirictherapy

increased morbidity more antibiotics

Increased healthcare resource use

Limited treatment alternatives

more antibiotics increased

mortality

Increasedhospitalization

more antibiotics

Estimated unnecessarycost of resistance =

$4B annually

Source: McKinnon, Academy for Infection Management, February 2004

Need for Change: Costs to the system without personalized treatmentNeed for Change: Costs to the system without personalized treatment

Combining Testing with Treatment

A More Direct Answer

Observation Test Action Predictable Response

Need for Change: Breaking the cycle The new traditional medicineNeed for Change: Breaking the cycle The new traditional medicine

Disease1 Year

Survival5 Year

Survival

Lung cancer (small cell-non small cell) 36-41%

Colorectal cancer 60% 39%

Chronic myeloid leukemia (CML) 73% 37%

Heart failure (male-female) 76-72% 41-55%

End stage renal disease 78% 38%

6-13%

12005 USRDS Annual Data Report2 Levy, et. al., Long-term trends in the incidence and survival from heart failure, NEJM, 2002; 347(18):1397-4023Cancer Perspectives U.S., 2004 Fourth Edition, DaVinci Healthcare Partners; NCI SEER data, average across all stages at Dx

Need for Change:Patients dont have time for trial & errorNeed for Change:Patients dont have time for trial & error

93% 80%

Need for Change:Payors wasting money on drugs that are not workingNeed for Change:Payors wasting money on drugs that are not working

Drug ClassFrequency of

Absent or Incomplete

Efficacy (%)1

Total Market Size

Cost to the Health Care System of Ineffective Therapy

Angiotensin-converting enzyme (ACE) inhibitors

10-30

15-25

20-50

30-70

40-70

$390M-$1.2B

Beta blockers

$3.9B2 (2003)

$ 2.3B2 (2003)

$11.7B3 (2003)

$12.6B4 (2004)

$345M-575M

Anti-depressants $2.3B-$5.8B

Statins $3.8B-$8.8B

Beta agonists $1.4B5 (2004) $560M-$1B

1 Ross JS & Ginsburg GS, Am J Clin Pathol 2003;119:26-362 Datamonitor, August 1, 20053 Global Industry Analysts, October 10, 20044 Carnegie Research5 Specialty Pharmaceutical Pulse, SG Cowen, October 2005

Past Macro Level Diagnostic Testing Disease defined by location and size Tests differentiated disease from non-

disease

Today Molecular Diagnostic and Prognostic Testing

Disease defined by individual biology/DNA Tests to subcategorize disease and:

predict outcomes of specific Rx screen for adverse events monitor disease

Tomorrow Predictive Testing Predictive testing for development of

common diseases Disruptive technologies

Why Now: Testing technology has improvedWhy Now: Testing technology has improved

Ries LAG, Eisner MP, Kosary CL, Hankey BF, Miller BA, Clegg L, Mariotto A, Feuer EJ, Edwards BK (eds). SEER Cancer Statistics Review, 1975-2002, National Cancer Institute. Bethesda, MD, http://seer.cancer.gov/csr/1975_2002/, based on Nov 2004 SEER data submission, posted to the SEER web site 2005.

Why Now:Disease better understood, segmented, & personalizedWhy Now:Disease better understood, segmented, & personalized

60 Years Ago

Leukemia or Lymphoma50 Years Ago

Chronic LeukemiaAcute LeukemiaPreleukemia

Indolent LymphomaAggressive Lymphoma

70 Years Ago

Disease of the Blood

Today

38 Leukemia types identified:Acute myeloid leukemia (12 types)Acute lymphoblastic leukemia (2 types)Acute promyelocytic leukemia (2 types)Acute monocytic leukemia (2 types)Acute erythroid leukemia (2 types)Acute megakaryoblastic leukemiaAcute myelomonocytic leukemia (2 types)Chronic myeloid leukemiaChronic myeloproliferative disorders (5 types)Myelodysplastic syndromes (6 types)Mixed myeloproliferative/myelodysplastic syndromes (3 types)

51 Lymphomas identified:Mature B-cell lymphomas (14 types)Mature T-cell lymphomas (15 types)Plasma cell neoplasm (3 types)Immature (precursor) lymphomas (2 types)Hodgkins lymphoma (5 types)Immunodeficiency associated lymphomas (5 types)Other hematolymphoid neoplasms (7 types)

5 yearSurvival

~ 0%

70%

Why Now: Targeted Rx will drive growth of companion DxWhy Now: Targeted Rx will drive growth of companion Dx

Projected impact of targeted therapies on genetic testing*

2 to 4 per year

Today 2010 2010 2015

Stage of Rx development

Percent Rx with predictive biomarker

Time to market

Phase III

~10%

Zero to 4 years

Projected joint Rx/Dx launches

6 to 9 per year

Phase I