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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
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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)
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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
20 22 18
24 26 21
30
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3.2 3.6 4.1 4.8 5.7 6.5 7.3 8.4 9.6 11.6 12.7 13.4
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
0
10
20
30
40
50
60
0
20
40
60
80
100
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
illio
ns
Num
ber o
f Pr
oduc
ts
Year
Genomic-based Research Enables Precision Medicine
Right Target Right Patient Goal to improve survival
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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
0.2
0.4
0.6
0.8
1.0
Ove
rall
Surv
ival
Pro
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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