How Personalized Medicine is Changing the Biopharmaceutical Marketplace Marc Chioda, PharmD Associate Medical Director, Pfizer Oncology. Presentation to the Cancer Action Coalition of Virginia January 2015
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. 2
Today s Medicines are Developed with More Precision Precision Medicine 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 Segmented (not personalized) 3
Recognition of Leukemia and Lymphoma Sub-types has Improved Outcomes 100 years ago 80 years ago 60 years ago Today Chronic leukemia Acute leukemia Preleukemia ~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) Disease of the blood Leukemia or lymphoma Indolent lymphoma Aggressive lymphoma 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 4
The Human Genome: A Great Opportunity for Drug Discovery? 5
Biopharmaceutical R&D Investment and New Medicines Approved 100 60 80 43.4 50.7 47.9 48.648.5 47.4 46.4 50 Number of Products 60 40 20 53 39 22.7 21.1 36 19.0 30 30 2816.9 30 26 25 15.2 25 27 22 20 21 23 23 24 22 20 21 20 22 24 26 12.713.4 11.6 21 9.6 17 18 12 3.2 3.6 4.1 4.8 5.7 6.5 8.4 7.3 26.0 31.0 29.8 39.9 37.0 34.5 30 39 40 30 20 10 $ Billions 0 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 Year 0 Sources: Paraxel's Pharmaceutical R&D Statistical Sourcebook 2005/2006; FDA; PhRMA 6
Genomic-based Research Enables Precision Medicine Right Target Right Patient Goal to improve survival 1.0 New treatment Comparator Drug targeted to specific oncogene or aberrant pathway driving the specific tumor Patient identified through molecular profiling of their tumor Overall Survival Probability 0.8 0.6 0.4 0.2 0 For illustrative purposes only 0 6 12 18 24 30 36 Months of survival Ultimate objective is to improve survival 7
Rationale for Precision Medicine R&D 8
Challenges for Coordination of Rx/Dx Co-development Sponsor must coordinate between different FDA Centers Diagnostic PMA (CDRH) Therapeutic Clinical Development Phase 1 Phase 2 Phase 3 CDER/CBER FDA has multiple programs to expedite drug/biologic development and review: Fast Track, Accelerated Approval, Breakthrough Therapy, Priority Review 9
FDA Framework for Personalized Medicine: A Mosaic of Guidance Documents Document Type Title Date Concept Paper Drug-Diagnostic Co-Development April 2005 Guidance Draft Guidance Draft Guidance (FAQ) Guidance Pharmacogenetic Tests and Genetic Tests for Heritable Markers Feb 2006 (draft) June 2007 (final) In Vitro Diagnostic Multivariate Index Assays Sept 2006 (draft) Feb 2007 (public meeting) July 2007 (revised) 2010 (withdrawn) Commercially Distributed In Vitro Diagnostic Products Labeled for Research Use Only or Investigational Use Only Clinical Pharmacogenomics: Premarket Evaluation in Early Phase Clinical Studies June 2011 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! Human genome sequencing completed! The Personalized Medicine Coalition launched! Introduction of the Genomics and Personalized Medicine Act! Personalized Healthcare Initiative launched by HHS 1997 1998 2001 2003 2004 2006 2007 2011 2012 2013 2014 = indicates approval of a biomarker driven therapy (for illustrative purposes not all inclusive) Personalized Medicine Coalition. The case for personalized medicine. Washington, DC: Personalized Medicine Coalition; 2009. 11
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 FDA Dx Co. Drug Co. FDA News Release. http://www.fda.gov/newsevents/newsroom/pressannouncements/ucm375742.htm. Accessed 1 Dec 2014. 13
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? 14
Understanding of Oncologic Drivers is Rapidly Increasing NSCLC as an Example Adenocarcinoma Histology-driven Selection Adenocarcinoma Targeting Oncogenic Drivers 1 K-RAS EGFR B-RAF HER-2 PIK3CA ALK MET Unknown The majority of these biomarkers are investigational EGFR and ALK are associated with approved therapies References: 1. Massachusetts General Hospital, data on file 2. Horn L, Pao W. J Clin Oncol 2009;26:4232 5 15
Creating a New Paradigm for NSCLC Treatment Traditional Paradigm Metastatic disease Evolving Personalized Paradigm Metastatic disease Multiple test options Biomarkers can direct treatment towards targeted therapy or clinical trials (where available) Non-squamous cell carcinoma Squamous cell carcinoma EGFR K-RAS ERCC1 ALK HER-2 TS B-RAF " 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
Biomarkers Support Expansion of Use GLEEVEC as an Example Therapeutic Biomarker C-Kit Indication(s) Gastrointestinal stromal tumors, aggressive systemic mastocytosis GLEEVEC Imatinib Philadelphia Chromosome PDGFR FIP1L1-PDGFRα chronic myeloid leukemia, acute lymphocytic leukemia myelodysplastic/ myeloproliferative diseases hypereosinophilic syndrome and/or chronic eosinophilic leukemia Adapted from GLEEVEC prescribing information (www.novartis.com) 17
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 18
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 19
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 20
Thank You! Questions??? 21