How Personalized Medicine is Changing the ...cancercoalitionofvirginia.org/PDFs/Home...January 2015 How Personalized Medicine is Changing the Biopharmaceutical Marketplace Personalized

Marc Chioda, PharmD Associate Medical Director, Pfizer Oncology. Presentation to the Cancer Action Coalition of Virginia January 2015

How Personalized Medicine is Changing the Biopharmaceutical Marketplace

Personalized Medicine: Towards a Definition

“Personalized medicine” refers to the tailoring of medical treatment to the individual characteristics of each patient. It does not literally mean the creation of

drugs or medical devices that are unique to a patient, but rather the ability to classify individuals into subpopulations that differ in their susceptibility to a

particular disease or their response to a specific treatment. Preventive or therapeutic interventions can then be concentrated on those who will benefit,

sparing expense and side effects for those who will not.

Report of the President’s Council of Advisors on Science and Technology, September 2008

The right drug …for the right person …in the right dose …at the right time

1

Older Drugs were Developed Empirically

– Source of data: Brian B. Spear, Margo Heath-Chiozzi, Jeffery Huff, “Clinical Trends in Molecular Medicine,” Volume 7, Issue 5, 1 May 2001, Pages 201-204.

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Today’s Medicines are Developed with More Precision

Medicines targeting patient segments that will have an optimal response to therapy

Building disease understanding to identify the right

pathways and targets

Linking disease understanding

and clinical outcomes

Precision Medicine

Segmented (not personalized)

3

Recognition of Leukemia and Lymphoma Sub-types has Improved Outcomes

100 years ago Disease of the blood

80 years ago Leukemia or lymphoma

60 years ago

Chronic leukemia Acute leukemia Preleukemia

Indolent lymphoma Aggressive lymphoma

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 leukemia •  Acute myelomoncytic leukemia (2 types) •  Chronic myeloid leukemia •  Chronic 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) •  Hodgkin’s lymphoma (5 types) •  Immunodeficiency-associated

lymphomas ~ 5 types) •  Other hematolymphoid neoplasm's

(~7 types)

5-Yr Survival

~0%

70%

Source: Malorye, Allison. “Is Personalized Medicine Finally Arriving?” Nature Biotechnology, May 2008

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The Human Genome: A Great Opportunity for Drug Discovery?

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Biopharmaceutical R&D Investment and New Medicines Approved

Sources: Paraxel's Pharmaceutical R&D Statistical Sourcebook 2005/2006; FDA; PhRMA 6

12

22

30

20 21 20 23 23

30 26 25

22 28

53

39

30 25 27

24

17 21

36

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24 26 21

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39

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15.2 16.9

19.0 21.1

22.7 26.0

29.8 31.0

34.5 37.0

39.9

43.4

47.9 47.4 46.4

50.7 48.6 48.5

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10

20

30

40

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83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12

$ B

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Num

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Year

Genomic-based Research Enables Precision Medicine

Right Target Right Patient Goal to improve survival

7

Drug targeted to specific oncogene or aberrant pathway driving the

specific tumor

Patient identified through molecular profiling of

their tumor

Ultimate objective is to improve survival

New treatment Comparator

0 6 12 18 24 30 36 0

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0.6

0.8

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rall

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ival

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babi

lity

Months of survival

For illustrative purposes only

Rationale for Precision Medicine R&D

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Phase 1 Phase 2 Phase 3

Clinical Development

Challenges for Coordination of Rx/Dx Co-development

PMA (CDRH)

CDER/CBER

Sponsor must coordinate between different FDA Centers

FDA has multiple programs to expedite drug/biologic development and review: Fast Track, Accelerated Approval, Breakthrough Therapy, Priority Review

Diagnostic

Therapeutic

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FDA Framework for Personalized Medicine: A “Mosaic” of Guidance Documents

Document Type Title Date Concept Paper Drug-Diagnostic Co-Development April 2005

Guidance Pharmacogenetic Tests and Genetic Tests for Heritable Markers

Feb 2006 (draft) June 2007 (final)

Draft Guidance In Vitro Diagnostic Multivariate Index Assays Sept 2006 (draft) Feb 2007 (public meeting) July 2007 (revised) 2010 (withdrawn)

Draft Guidance (FAQ)

Commercially Distributed In Vitro Diagnostic Products Labeled for Research Use Only or

Investigational Use Only

June 2011

Guidance Clinical Pharmacogenomics: Premarket Evaluation in Early Phase Clinical Studies

Feb 2011 (draft) January 2013 (final)

Guidance In Vitro Companion Diagnostic Devices July 2011 (draft) July 2014 (final)

Additional guidance documents forthcoming 10

Evolution of Selected Biomarker-Driven Therapies

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! The Personalized Medicine Coalition launched !  Introduction of the Genomics and Personalized Medicine Act

– 2011

! Human genome sequencing completed

– 2001 – 1997 – 1998 – 2003 – 2004 – 2006 – 2007

! Personalized Healthcare Initiative launched by HHS

– 2012 – 2013 – 2014

Personalized Medicine Coalition. The case for personalized medicine. Washington, DC: Personalized Medicine Coalition; 2009.

= indicates approval of a biomarker driven therapy (for illustrative purposes – not all inclusive)

Next Generation Sequencing (NGS) For Cystic Fibrosis

•  Nov. 19, 2013, FDA allowed marketing of NGS devices to aid in screening and diagnosis of cystic fibrosis

•  Illumina MiSeqDx Cystic Fibrosis 139-Variant Assay,

–  Checks specific points in the patient’s CFTR gene sequence to detect known variants in the gene

–  Information about DNA changes associated with cystic fibrosis is found in the Clinical and Functional Translation of CFTR database (CFTR2)

•  Illumina MiSeqDx Cystic Fibrosis Clinical Sequencing Assay

–  Sequences a large portion of the CFTR gene to detect any difference in the CFTR gene compared to a reference CFTR gene

FDA News Release. http://www.fda.gov/NewsEvents/Newsroom/PressAnnouncements/ucm375742.htm. Accessed 1 Dec 2014. 12

NGS-­‐Based  Assays  Are  Not  Currently  Cleared  by  FDA  as  Companion  Diagnos;cs    

•  CDx  are  part  of  many  clinical  trial  designs,  par6cularly  in  oncology  

•  Challenges  exist  in  valida6ng  NGS  pla=orms  to  meet  CDx  standards  

–  Wide  range  of  gene6c  variants  covered  makes  it  difficult  to  verify  that  each  variant  is  interpreted  correctly    

•  Clinical  trials  to  establish  analy6cal  validity  

–  Require  a  high  level  of  coordina6on  between  developers  of  the  drug  &  diagnos6c  

13 FDA News Release. http://www.fda.gov/NewsEvents/Newsroom/PressAnnouncements/ucm375742.htm. Accessed 1 Dec 2014.

Dx  Co.  

FDA  

Drug  Co.  

Personalized Medicine: Key Components

•  Science & Technology •  Driving the understanding of disease and the discovery and

development of medicines •  Regulatory science advances

•  Medical Practice -  What’s best for the patient? -  Changes in medical practice

•  Health Care Environment

o How do we get personalized o medicines to patients?

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Understanding of Oncologic Drivers is Rapidly Increasing—NSCLC as an Example

References: 1. Massachusetts General Hospital, data on file 2. Horn L, Pao W. J Clin Oncol 2009;26:4232–5 15

Adenocarcinoma Histology-driven Selection

K-RAS EGFR B-RAF HER-2 PIK3CA ALK MET

Unknown

Adenocarcinoma Targeting Oncogenic Drivers1

–  The majority of these biomarkers are investigational –  EGFR and ALK are associated with approved therapies

Evolving Personalized Paradigm

Metastatic disease

Biomarkers can direct treatment towards targeted therapy or clinical

trials (where available)

EGFR K-RAS ERCC1 ALK TS B-RAF HER-2

Traditional Paradigm

Non-squamous cell carcinoma

Metastatic disease

Squamous cell carcinoma

Creating a New Paradigm for NSCLC Treatment

"  Oncologist sole treatment decision maker "  Treatment decisions depend on histology

"  More complex decisions involving more stakeholders beyond oncologist (surgeon, pathologist)

"  Education required to integrate molecular diagnostics into treatment decisions

"  Need for multiple molecular Dx creates competition for available tissue, budget, manpower

"  Not a “simple” issue of a single drug-diagnostic combination

Multiple test options

Biomarkers Support Expansion of Use — GLEEVEC as an Example

Therapeutic   Biomarker   Indication(s)  

GLEEVEC® Imatinib  

C-Kit  Gastrointestinal stromal tumors, aggressive systemic mastocytosis  

Philadelphia Chromosome  

chronic myeloid leukemia, acute lymphocytic leukemia  

PDGFR  myelodysplastic/ myeloproliferative diseases  

FIP1L1-PDGFRα  hypereosinophilic syndrome and/or chronic eosinophilic leukemia  

Adapted from GLEEVEC® prescribing information (www.novartis.com)

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Challenges to Personalized Medicine in the Marketplace

•  Precision medicine may drive efficiencies in drug development but applying new technologies is challenging

•  Drug development may or may not be less costly

•  If targeting smaller, more defined populations, medicines should have greater efficacy / safety risk ratios but also likely be more expensive

•  Diagnostics landscape is rapidly evolving – needs investment to sustain innovation

•  Integrating each new intervention into healthcare management takes time

•  Growing pressure to show Personalized Medicine improves health outcomes

•  Access may be restricted

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Rx to Deliver the Pipeline for Personalized Medicine

•  Aggressive application of science to R&D

–  Informatics tools to analyze large, multi-dimensional data sets

–  Closer industry-academia collaboration to drive customized therapies

–  Novel clinical trial designs that incorporate new drug development tools

–  Finding opportunities in existing and potential medicines

•  Secure systems that allow safe sharing of data between health care providers, industry and regulators to streamline development and approval processes

•  Collaborative relationships with regulators that strengthen patient safety but also speed the approval of novel biomarker applications and Dx technologies

•  Evidence standards to demonstrate the effectiveness of diagnostics in improving patient outcomes

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Toward a Health Care System that Delivers the Value of Personalized Medicine

•  Data systems that assure security and access to the growing body of patient data •  Quality standards to insure data compatibility and comparability •  Integrated health information: a complete systems-based readout

of the health status of an individual in a given environment

•  Physicians need easy-to-interpret results •  user-friendly technological interface •  data from multiple sources •  continuously refined algorithms and

database updates

•  Enabling functions: standards, infrastructure, systems approach, sharing mechanisms

•  Education along the entire health care ecosystem

Policy will determine success or failure of personalized medicine implementation

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Thank You!

Questions ???

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