Successes in Pharmacogenomics: Progress to Date and Future Opportunities

Transcription

1 Successes in Pharmacogenomics: Progress to Date and Future Opportunities 2008 International Conference on Pharmacogenomics April 9, 2008 Busan, Republic of Korea Lawrence J. Lesko, Ph.D., FCP Director, Office of Clinical Pharmacology Center for Drug Evaluation and Research Food and Drug Administration Silver Spring, Maryland, USA Hae-Young Ahn Sally Choe Young-Moon Choi Sang M. Chung Seong H. Jang Hyun-Jin Kim Insook Kim Myong-Jin Kim David Lee Jang-Ike Lee Joo-Yeon Lee Young-Jin Moon Chongwoo Yu Howard Lee Hwa-Kyung Lim Dong-Seok Yim Deputy Division Director Team Leader Team Leader Pharmacometrician Senior Reviewer Reviewer Reviewer Team Leader Senior Reviewer Team Leader Pharmacometrician Reviewer Reviewer Visiting Scientist Visiting Scientist Visiting Scientist

2 Disclaimer This presentation represents my personal views and does not necessarily reflect the polices or endorsement of the Food and Drug Administration Outline Basic Concepts and Myths Efficacy responsive patient subset Safety predicting at risk patients Dosing optimizing benefit-to-risk ratio Challenges to Future Success Trends in Consumer Genomics

3 What is Success: The Extent to Which Fears Are Addressed Patient Will drug help me? Will drug hurt me? Health Care Provider Too prescriptive? Pharmaceutical Company Reduce market share or add market value? Diagnostic Company Poor reimbursement for test? Health Care Payer Add to costs without return Concepts Pharmacogenomics (PGx): science of using inherited variations in genes that dictate whether a drug will be effective or safe Genomic biomarkers: measurable DNA or RNA characteristics in human, tumor or virus samples that are indicators of: -- normal biologic processes -- pathogenic processes -- response to drugs Source: Adapted from ICH E15 Guideline on Definitions and Coding, January 2008

4 Genomic Biomarker Are the Basis for Diagnostic Tests Diagnostic tests are the linchpin of personalized medicine What Is Personalized Medicine? Personalized medicine (PM) is the science of individualizing drug therapy based on each patient s genetic make-up 1. Entire patient populations are stratified into subgroups with similar genetic make-up 2. PM intended to be more predictive of drug benefit and risk than traditional medicine 3. PM is not using an individual s genetic makeup to identify disease or predict future risk of disease

5 Myths About PGx and PM PGx: deterministic and expresses the probability of efficacy, toxicity or dosing being optimal PM: genetics is only one factor but demographics, environment and lifestyle interactions influence drug response efficacy or safety Approach to Medicine in Drug Development is Based on Populations Public Health: maintaining or restoring health through the study, diagnosis, treatment and prevention of disease in populations Clinical Trials: conducted in populations of carefully selected patients to assess average efficacy and observe toxicity

6 Approach to Medicine in Clinical Practice is Based on Individuals Health care providers: concerned with how to maintain or restore health through diagnosis, treatment and prevention of disease in individuals Patients: want to know will this drug work for me or will this drug hurt me; influence compliance and clinical outcomes PGx and Genomic Biomarkers Bridge The Gap Between Populations and Individuals PGx and Genomic Biomarkers Information About Populations Knowledge About Individuals

7 How Will PGx and Genomic Biomarkers Change the Paradigm of Medicine? Traditional Medicine Example Personalized Medicine Example Diagnosis disease as collection of symptoms High blood pressure has many causes Diagnosis disease by underlying biology of physiology Breast cancer where tumors overexpress HER2 Treatment guidelines treat symptoms as single disease Non-Hodgkin's lymphoma defines many cancers of immune system Customized guidelines based on disease stratification Subclasses of B-Cells and T-Cells -- Use of rituximab if CD-20 positive One size fits all dosing 5 mg/day of warfarin for all patients Patient stratification and genotype-guided dosing Genotypes defined by 2C9 and VKORC1 need 0.5 to 6 mg/day Lack of physician and patient awareness Little formal education and access to genetic testing New, educated generation of health care providers and patients Continuing education by AMA, consumer genomics such as 23andMe, SNPedia Drugs Where Successful Diagnostic Tests Have Been Used EFFICACY SAFETY Drug Test Drug Test Herceptin HER2 6-MP TPMT Gleevec BCR-ABL Camptosar UGT1A1 Rituxan CD20 Warfarin 2C9, VKORC1 Donepezil ApoE4 Ziagen HLA-B5701 Erbitux EGFR CBZ HLA-B1502 Selzentry Tropism Tamoxifen 2D6

8 Success Example # 1 Efficacy Responsive Patient Subset Importance of Identifying Responders to Drug Therapy Source: Spear, Trends in Medicine 2001: 7(5), and Aspinall, ACMG Presentation March 13, 2008

9 Rheumatoid Arthritis: Preapproval Pivotal Clinical Trials in Drug Development Example: Drug X Randomize 500 patients to active treatment or placebo Clinical approval endpoint: average 20% improvement rate in ACR20 in all patients given 50 mg Drug X Efficacy response rate: 52% for Drug X vs 26% for placebo (p < 0.05) Approximately 1/2 patients in active treatment arm did not achieve mean 20% improvement in ACR20 ACR20: composite endpoint measuring joint swelling, pain, range of motion and functional status Clinical Practice Dilemma: Taking Guesswork Out of Treatment Effects If an individual patient is given 50 mg per day of Drug X, what improvement would a health care provider predict for the ACR20? Based on clinical trials, Drug X will be the wrong drug for many patients Some of those patients will experience adverse events of Drug X and no benefit

10 Example of HIV-AIDS: Provides an Alluring Target for PGx and PM Why? HIV-AIDS has many disease subtypes Rapid disease progression and high mortality Drugs that target cellular disease pathways Many viral biomarkers and gene mutations Relatively low efficacy rate over time Potentially frequent and serious adverse events Patient stratification using resistance testing Physician familiarity with diagnostic tests Examples: PhenoSense GT assay for complete picture of viral resistance and susceptibility to guide drug selection; HIV viral load (viral RNA) in blood to monitor response Life Cycle of CCR5-Tropic HIV in Patients with AIDS Incoming R5-virus enters CD4 or T-cells by attaching to the CCR5 and/or CXCR4 co receptors (called tropism) x New virus capable of infecting other uninfected cells Virus uncoats and viral RNA is released which is reverse transcribed into viral cdna that integrates into genome of infected cell

11 Selzentry R (Maraviroc): Drug-Test Combination Approved in August 2007 Selzentry R antagonizes CCR5 co-receptor and not effective in dual or mixed CXCR4 HIV-1 Trofile R test stratifies HIV strains based on which receptor virus uses to enter CD4-positive T cells RCT could not have been conducted in patients without first identifying CCR5-tropic patients Selzentry R reduces viral load and increases CD4- positive T cell counts by blocking CCR5-tropic virus Approval based on 24 week data from phase IIB-III clinical trial in treatment-experienced HIV patients Selzentry R (Maraviroc) Label and Success Factors Selzentry R label requires use of tropism assay before prescribing to identify responders Tropism assay also identifies non-responders and lack of response was confirmed Generally well-tolerated although label has warning of hepatotoxicity Success Factors Knowledge of disease pathology and drug target Ability to identify disease subsets to increase efficacy signal Validation of test clinical utility during pivotal drug efficacy trials

12 Success Example # 2 Safety Predicting At Risk Patients Importance of Identifying Patients at Risk for Toxicity from Drug Therapy Heart Disease Cause of Death Malignant Hyperplasia CV Disease Respiratory Disease ADR 2.2 million ADR / year $177 billion annual costs No good way to distinguish responders, non-responders and those at-risk Number of Annual Deaths x 1000 Source: National Vital Statistics Reports 2005: 53 (17) US data from 2001

13 Ziagen R (Abacavir): Post-Marketing Test Development for Hypersensitivity Syndrome Abacavir (Ziagen R ) approved for HIV-1 infection in 1999 Main limitation is hypersensitivity reaction affecting 5% of patients causing physicians hesitation to prescribe Fever, rash, GI and respiratory symptoms 90% occurs with 6 weeks and resolve with discontinuation Re-challenge leads to multi-organ failure and possibly death Genetic association between HLA-B*5701 and HS reported in 2001 by two independent groups Mainly Caucasian males; extended to African Americans and females in % selectivity (3% false + rate); 50-94% sensitivity (false rate) Physicians tend to overestimate HS phenotype due to abacavir LabCorp offered test to US HIV clinicians in 2005 for screening Source: Lancet 2002;359: , Lancet 2002;359: Prospective, Multi-Center RCT to Validate Clinical Utility of Diagnostic Test Does prescreening HIV-1 patients for HLA-B*5701 before abacavir reduce incidence of HS reaction based defined clinically and immunologically? 1956 enrolled and randomly assigned to two arms with ~ evaluable, matched patients per arm HS more than twice as likely without genetic test: 7.8% - no test arm vs. 3.4% - tested arm Similar findings for immunologically confirmed HS; 2.7% - no test arm, vs. 0% - test arm NPV = 100% (confidently give drug if test - ) PPV = 48% (deny abacavir almost 1/2 patients if test + ) NNT = 14 (screen 14 to prevent 1 event of HS) Source: New England Journal of Medicine 2008;358:

14 Are Physicians Ready: Yes Based on Clinical Demand for HLA-B*5701 Testing Source: Dr. Eric Lai (GSK) and LabCorp, presented at CPAC on March 18, 2008 Abacavir-HLA-B*5701 Hypersensitivity Success Factors Success Factors Hypersensitivity reaction was frequent and potentially severe; real clinical problem Development of high resolution HLA typing allow detection of HLA*5701 Patch test for accurate phenotype definition HLA-B*5701 test provided an effective solution; rule out patients unnecessarily at risk (high specificity) Strength of evidence based on prospective validation of clinical utility ~ the Achilles Heel for PGx

15 Success Example # 3 Dosing Optimizing Benefit/Risk Ratio Ethnic Frequency Differences in Low-to- Intermediate Metabolism CYP Genotypes Phenotype CYP2C9 CYP2C19 CYP2D6 Korean 2-12% 53% 28% Caucasian 35% 28% 15-25% 17 of 100 most frequently prescribed drugs have polymorphic metabolism in Korea; 7 of 17 drugs have serious dose-related AE 36% of US Caucasian patients are on drugs having polymorphic metabolism; 35% of labels of US FDA approved drugs have PGx 16% of PMDA-approved labels in Japan have PGx Source: Kim, YM et al, Am J Health Sys Pharm 2007:64; ; Medco Health Solutions

16 Warfarin As An Anticoagulant: Taking the Guesswork Out of Dosing Risks of warfarin over-anticoagulation not in doubt: one of top 3 drugs for ER visits and AE reports Bleeding is serious, sometimes fatal, and results in poor long-term compliance INR used as biomarkers to monitor rate and extent of anticoagulation; target range of 2-3 Greatest risk occurs in initial dosing phase of 4-6 weeks until INR and dosing stabilizes Problem is NTI and large interinvidiual variability in maintenance doses due to PK and PD differences Warfarin Risk Factors: Primarily Determined by PK and PD PGx 25% of variability AG, AA CYP1A1 CYP1A2 CYP3A4 R-warfarin Warfarin R-warfarinwarfarin Vitamin K Reductase S-warfarin S-warfarin CYP2C9 15% of variability *2, *3, *5 Oxidized Vitamin K Calumenin Reduced Vitamin K CO 2 O 2 Hypofunctional F. II, VII, IX, X Protein C, S, Z γ-glutamyl carboxylase Functional F. II, VII, IX, X Proteins C, S, Z Source: Gage and Eby, Pharmacogenomics J, 2004

17 Warfarin Dosing Equation: Accuracy from 53% to 80%; Clinical Factors Alone ~ 21% Entry Variable Effect on Dose R 2 P value 1 VKOR-1639/ % 25% < BSA, per 0.25 m 2 11% 34% < CYP2C9*3 33% 40% < Age, per decade 7% 45% < CYP2C9*2 19% 50% < Target INR 11% 51% < Amiodarone 22% 52% < Smokes 10% 52% AA race 9% 53% Prior DVT or PE 7% 53% INR measurements 80% Source: Brian Gage Presentation at American College of Medical Genomics, March 2008 New Warfarin Label Containing Recommendation for Genetic Testing Source: Medco Health Solutions, 2007

18 Warfarin Success Factors or Lack Thereof: Slow Uptake by Health Care Providers Scientific issues Debate over evidence; surrogate (INR) vs clinical endpoints (bleeding) and absence of RCT No specific genetically-based dosing recommendation in revised warfarin label Lack of agreement on 2C9, VKORC1 and other genes that addresses needs of all ethnic or racial groups Other issues Perception that INR-stabilized patients don t need test Assumption that current INR monitoring system works Concern that PGx tests will not eliminate need for INR Cost of gene tests ($500) not paid by insurance Surveys show < 10% of physicians have heard of tests Value of PGx Testing for Warfarin: 2/3 of Patients Require a Change in Standard Dose Risk Associated with Dose Adjustment and Any Hemorrhage/Thrombosis Hospitalization Event Number of Dose Adjustments Number of Patients Hospitalization Event Rate < % % Total % Source: Medco-Mayo Study, Dr. Rob Epstein, Medco Health Solutions

19 Ethnic Differences in Allele and Genotype Frequencies Play Important Role in Dosing Allele or Genotype CYP2C9*2 CYP2C9*3 VKORC1 AA Asian < 1% 1-6% 89% Caucasian 8-13% 6-10% 14% Asian Hispanic Caucasian African- American Weekly Warfarin Dose 24 mg 31 mg 36 mg 43 mg Source: Coumadin (BMS) Label: 2007, and Ann Pharmacotherapy 2005: 39; Irinotecan: Ethnic Differences in Allele Frequencies of UGT1A1 Severe Neutropenia From Irinotecan in Patients with Two *28 or *6 Alleles Ethnicity Caucasian African-Amer Chinese Korean Japanese Prevalence of Allele *28 45% 39% 2% 6% 10% *6 0% 0% 15% 6% 17% Est. Odds Ratio for Homozygous Genotype Source: Kaniwa et al, Drug Metab Dispos: 2005 and FDA Clinical Pharmacology Advisory Committee, 2004; Lee et al, Clin Chem 2003:49;

20 Stevens Johnson Syndrome Induced by Carbamazepine FDA updated the label of carbamazepine in December 2007 that Asian patients should undergo genetic testing for HLA-B*1502 Frequency of at risk gene variant: China, Taiwan, Thailand and Indonesia: 15% South Asia: 2-4% Japan and Korea: <1% Challenges to Future Success

21 Key to PGx and PM Is Routine Collection of the Biospecimen in Drug Development BIOLOGY OF DISEASE Changes in biology caused by gene mutations and environment INDIVIDUALIZED TREATMENT PLAN GENETICS OF PATIENT PhRMA Industry Survey on ADME PGx in 14 Participating Companies DNA collection 80-90% of companies in phase I studies; PK, DDI etc as a study requirement 40-50% of companies in phase II phase III studies; POC, D/R and pivotal RCT as an optional activity 70% of companies use ADME genotype as inclusion or exclusion analysis DNA analysis Only 15% of companies have performed genotyping Preclinical data indicates PGx will influence PK An adverse event suggests PGX is at fault Failure of efficacy that is unexpected Intention to make a label claim Source: Dr. Lisa Shipley, CPAC, March 18, Data collected from

22 Genome-Wide SNP Screening in Industry: Target Selection and Validate Associations Find Collect patient biospecimens GWAS and/or targeted SNP search Training biomarker set Feature selection PHASE I PHASE IIA PROOF OF CONCEPT Cross validation Class prediction Responder Non-responder Validate Use Best predictor model Biomarker validation set Analytical and clinical validation Predictive test for two RCT of drug vs. placebo PHASE IIB EXPLORATORY PHASE III CONFIRMATORY Major Challenges to Future Success in PGx and PM in Drug Development and Clinical Practice 1. Focus on real problems in drug development and clinical practice; find effective solutions 2. Translation of GWAS and SNP analysis to clinical utility; understand disease biology 3. Weight and strength of evidence that documents usefulness of PGx; clinical utility 4. Cost structure for reimbursement of genetic testing; support sustainable business model 5. Changes in medical infrastructure to accelerate adoption; physician education, electronic records

23 Trends in Consumer Genomics Personal Genomics Available from 20 Companies for $999 to $350,000 23andMe, Inc. Navigenics, Inc. decode Genetics, Inc. Knome, Inc. Cheek-swab kit from 23ANDME Personal Genome Project Based on most common gene-specific association statistical studies with occurrence of disease using Affymetrix and Lumina platforms

24 Example: Craig Ventner s Genome Analysis Gene variant linked to soggy ear wax Gene (SORL1) linked to heart disease Genes (APOE) linked to Alzheimer s disease Gene linked to macular degeneration Gene linked to high cholesterol Genes linked to tobacco addiction Sources: Majority of Genetic Risks Factors Increase Risk by 10% to 40% But what does it mean to be told that you have a 40% greater chance of heart disease compared to others without a specific gene variant? (Assuming the results are correct) Can lifestyle changes (diet, exercise) do more to prevent onset of heart disease?

25 Physician Referrals to Trained Health Care Providers Is Essential.. Only 37% of physicians know that BRCA genes can be passed on by the father.. Only 17% of patients with familial colon cancer risk are referred to genetic counseling.. Only 10% of women who meet indications are offered prenatal counseling.. Only 2% of physicians have ever heard of warfarin genes 2C9 and VKORC1.. Most oncologists have never heard of 2D6 and its importance to tamoxifen.. Sources: Clin Gastroenterol Hepatol Sep;2(9):813-9, J Med Genet Oct;42(10): J Genet Couns Apr;14(2): and Robert Epstein, Medco (Personal Conversation) Match Day 2008: Linking Residency Programs with Aspiring Doctors Wish List Approximately 48% get first choice, 28% get 2nd choice, 13% get 3rd choice and 4% get no choice Stats for 2008 on specialties Internal medicine chosen by largest # of doctors (22%) Dermatology had highest % of positions filled (100%) Medical genetics had lowest % of positions filled (33%) Medical genetics had lowest # of positions available (10) Relative salary of dermatology/medical genetics ~ 5-10X Source:

26 Ask Your Doctor..In 10 Years: Physician Education Is Critical to PGx and PM March 28, all revolutions start with people in their 20 s. Medicine is no exception. Students entering medical school now, encouraged by the needs of their patients, will be the ones to make personalized medicine happen. Ralph Snyderman, M.D., Former Chancellor of the Duke University Medical Center Conclusion PGx and PM are not hype Simply the next step in applying science to understanding disease and drug response Driving forces are technology not available 10 years ago, advances in bioinformatics, decreased productivity in drug development, consumer interest in genomics and societal expectations for safe and effective drugs

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