David C. Whitcomb, MD, PhD and Philip E. Empey, PharmD, PhD

Transcription

1 David C. Whitcomb, MD, PhD and Philip E. Empey, PharmD, PhD

2 Part 1 MODERN MEDICINE - FOCUSED ON GERMS

3 Germ Theory of Disease The germ theory of disease states that some diseases are caused by microorganisms. These small organisms, too small to see without magnification, invade humans, animals, and other living hosts. Their growth and reproduction within their hosts can cause a disease. Louis Pasteur in his laboratory by A. Edelfeldt in (Public domain)

4 Koch s Postulates

5 Based on the Germ theory of disease One agent Complex syndrome Based on the Scientific Method of Koch Complex syndrome one factor Based on clinicopathologic disease definitions Syndrome, pathology-based (e.g. ICD codes) Results: Progress in infectious diseases and simple genetics Poor progress in complex* disorders Little guidance for managing complex disorders * Complex disorders: two or more factors are required. Can be gene x environment, gene x gene, etc. Individual factors may not be necessary nor sufficient to cause disease.

6 Part 2 SOME PROBLEMS WITH THE GERM THEORY

7 Expected Observed (if no germ ) Sx Inflammation Pain Organ dysfunction Sx Inflammation Pain Organ dysfunction Bacteria Scientific method previously identified germs with disease symptoms Germ Theory: symptom complex predicts single etiology Multiple etiologies are loosely associated with the same symptoms! Germ Theory: A Paradigm Failure!

8 High speed computers Structured databases Electronic health records Machine learning Computer modeling and simulations Massive parallel experiments Genetics Chips, NGS Biomarkers -omic datasets Major breakthroughs in patient care are lacking!!! Whitcomb, Nature Reviews: Gastroenterology & Hepatology, 2012

9 (Germ theory fails in complex data interpretation) EMR Not Meaningful: Based on clinicopathologic taxonomy rather than etiologies or mechanism. EBM Guidance limited to the mean of simple disorders in large populations using older studies GWAS Statistical approach requires massive international studies; limited clinical progress. NGS data from individual patients is too big and complex to interpret using traditional statistical approaches. EMR, electronic medical records; EBM, evidence based medicine; GWAS, genome-wide association studies; NGS, next generation sequencing. Whitcomb, Nature Reviews: Gastroenterology & Hepatology, 2012

10 Part 3 WHAT IS PERSONALIZED PRECISION MEDICINE AND WHAT DOES IT REPLACE? PMID:

11 Approach to disease treatment and prevention that seeks to maximize effectiveness by taking into account individual variability in genes, environment and lifestyle Precision medicine endeavors to redefine our understanding of disease onset and progression, treatment response, and health outcomes through the more precise measurement of potential contributors The Precision Medicine Initiative Cohort Program: Building a Research Foundation for 21st Century Medicine A precise delineation of the molecular, environmental, behavioral factors that contribute to health and disease will lead to more accurate diagnoses, more rational disease prevention strategies, better treatment selection, and the development of novel therapies

12 When is a new paradigm needed? Personalized/Precision/Individualized Medicine Needed when a syndrome is complex Multiple etiologies same pathology Same pathology multiple outcomes Treatment effects unpredictable (NNT >1) Needed for Complex & functional disorders; cancer Focus on mechanism rather than associations (RCT) Relies on modeling and simulation, not classification. Guidance for individuals rather than populations. Requires a New framework for new technologies

13 Fraction of Population Mechanism 1 Mechanism 2 Mechanism 3 Mechanism 4 Best evidence with NNT>>1 NO evidence! Less severe Inclusion/Exclusion criteria Disease Severity More severe

14 Fraction of Population Mechanism 1 Mechanism 2 Mechanism 3 Mechanism 4 Non-responders Highest cost Less severe Inclusion/Exclusion criteria Disease Severity More severe

15 Millions USD ($) Click BH, et al. Gastroenterology 2015; 148:S-40 S-41. Median $14,191 High $683, Patient # (N=2203) Slide courtesy of David Binion MD, University of Pittsburgh and UPMC

16 Of members with rare conditions: 1 in 2 visit the ER each year 1 in 3 are admitted to a hospital 3 out of 4 have at least one comorbidity 4.5x as expensive as an average member 3x as expensive as a common chronic member No comorbidities (6%) 94% of Commercial members who are using a Specialty drug for MS, CI, Hep C, or HIV are managing at least one comorbidity One comorbidity (7%) Two comorbidities (8%) Three - five comorbidities (28%) >5 comorbidities (52%) 16 Slide courtesy of Chronis Manolis, RPh, VP UPMC Pharmacy (used with permission, 4/16)

17 Part 5 IMPLEMENTATION OF PERSONALIZED PRECISION MEDICINE

18 Deep Focus: rare [expensive] complex disorders Example: RA, MS, IBD, Pancreatitis Methods: Whole genome sequencing Wide Focus: common complex disorders Example: drugs, pain Methods: targeted panels and SNP chips

19 Precision Medicine: Why focus on drugs? Oncology Perinatal Screening PGx (pharmacogenomics) Complex Diseases Many drugs work through common pathways Easily measurable phenotypes Germline polymorphisms Variants are common Testing is feasible Few ethical concerns

20 Trial and Error pharmacotherapy is not sustainable Billions (US$) $300 $250 $200 $150 $100 $50 US Total Prescription Drug Spending $ Year CMS data; 1/9/2012.

21 Medications often don t work for people % of patients for whom drugs are ineffective FDA. Paving the way for personalized medicine. 10/2013.

22 Truly achieving precision medicine Treatment Outcome Success Failure Toxicity Excessive Minimal Treat with conventional drug and dose Treat with alternative drug Treat with alternative drug or dose Treat with alternative drug

23 Principles of PGx Image: FDA. Paving the way for personalized medicine. 10/2013.

24 Emergence of PGx: a wealth of data Pubmed Citations All citations Excluding reviews annotations; 34 at level 1A 23 genetics-guided drug therapy guidelines published covering 33 drugs DPWG 57 drugs: 33 at level 4 Drug(s) Gene(s) Recommendation thiopurines TPMT Dosing based on genotype clopidogrel CYP2C19 Alternative therapy warfarin CYP2C9, VKORC1 Use algorithms incorporating genotype with clinical factors codeine CYP2D6 Avoid in ultrarapid or poor metabolizers abacavir HLA-B Avoid in those with HLA-B*5701 simvastatin SLCO1B1 Dosing based on genotype allopurinol HLA-B Avoid in those with HLA-B*5801 tricyclic CYP2D6, Dosing based on genotype antidepressants CYP2C19 carbamazepine HLA-B Avoid in those with HLA-B*1502 Empey et al. Crit Care Med. 38(6):S106-16

25 PGx is already in medication labeling 141 drugs currently have genetic data in their FDA-approved product labeling 7% 12% 17% 10% 17% 30% 7% Therapeutic areas: psychiatry neurology oncology cardiovascular infectious disease gastrointestinal other

26 Clopidogrel: A simple use case 2C19, 1A2, 2B6 Esterases 2C19, 1A2, 2B6

27 Clopidogrel: Genetic basis for variation Shuldiner et al. JAMA 2009;302(8):

28 Clopidogrel and CYP2C19 ~30% of Caucasians are intermediate or poor metabolizers (eg. *2) 1-5% Caucasians are ultrarapid metabolizer (eg. *17) Drug levels Normal PM Platelet reactivity Normal PM Scott et al. CP&T. 2011;90(2): ;Kim et al. CP&T. 2008;84(2):

29 Clopidogrel: CYP2C19 and outcomes 1reduced function allele = 55% increased risk of death, heart attack, stroke 3 fold increased risk of stent thrombosis 2reduced function alleles = 3.58 fold increased risk of death, heart attack, stroke FDA Black Box Warning (3/2010) Mega et al. NEJM. 2009;360(4): Simon et al. NEJM. 2009; 360(4):

30 Prospective Clinical Implementation Outcomes Cavallari et al, ASCPT, 2015

31 Barriers to standard of care PGx Clinical Testing Societal Education IT Few drug or dose selection algorithms Lack of prospective RCT data on clinical outcomes Little cost effectiveness data Availability/cost/reimbursement of testing Slow turnaround time for results Data management Poorly-designed clinical informatics systems Inadequate decision support Challenges in training current and future health professionals in PGx Ethics (privacy, equity, incidental findings, decision making) Privacy issues (informed consent) Legal issues (eg. discrimination, patents)

32 PGx clinical implementation is at a tipping point

33 The Pitt/UPMC vision for PGx implementation PreCISE-Rx Study: Pharmacogenomics-guided Care to Improve the Safety and Effectiveness of medications (Rx) Goal: Be a leader in pharmacogenomics implementation, research, and education.

34 Success through stakeholder teams PHASE I Cardiology Antiplatelets (clopidogrel) GI/Oncology Anticoag ID Pharmacy Informatics Pathology Med Genetics Medical Genetics EHR Teams Enterprise Analytics UPMC Healthplan Internal Med/Pain

35 Metrics collected and projected outcomes Research Study - IRB approved - Biobank/EHR Data Clinical Outcomes - Major adverse events - Any bleeding Process Efficiency - Turnaround time - Capture rate Medication Use - Adherence - Conversions Patient Satisfaction - Care model - Education $ Financial Impact - Reimbursement - Business model Hypothesis: pharmacogenomics-guided therapy individualization is clinically feasible

36 Aim 1: Clinical Governance and PGx Services PGx-guided antiplatelet selection algorithm Patient presents to Cath Lab P2Y12 inhibitor initiated CYP2C19 genotype testing (if not previously done) UM (*1/*17, *17/*17) EM (*1/*1) IM (*1/*2) PM (*2/*2) clopidogrel 75 mg daily ticagrelor 90 mg BID or prasugrel 10 mg daily

37 Aim 2: Establish PGx testing

38 Aim 3: Informatics and analytics CDS Alerts Drug Policy LOINCS Discrete results VCF training Analytics 1 Phenotyping Goal: Demonstrate value to drive clinical ROI

39 PreCISE-Rx EHR Configurations Discrete Results

40 PreCISE-Rx Clinical PGx Service Pharmacist note Page PGx-Rx (74979)

41 *2/*17 EHR Alerting

42 Networks for sharing data and collaboration

43 Persistent Challenges Continuity of care Data transitions Education of clinicians and patients Phenotyping and outcomes collection

44 PreCISE-Rx 9 Month Data 4% 18% Reported Genotypes 3% 6% 1% 29% 39% *1/*1 *1/*17 *17/*17 *1/*2 *2/*2 *2/*17 Other Predicted Phenotypes 3% 26% 39% 32% EM UM IM PM Loss of Function (LOF) Launched 12/1/2015; n=537 as of 9/1/16 Reduced testing turnaround time from 5-7 days to 27 h with onsite CLIA testing. 29% (n=157/537) with LOF variants 21% (n=114/2537) with actionable genotype (LOF carriers necessitating alternative therapy)

45 Conclusions A shift in treatment paradigm is needed to achieve precision medicine Implementation requires a multi-prong approach (deep and wide) PGx and complex diseases are ideal use cases for the application of precision medicine and UPMC is taking a leading role. Barriers remain, but precision medicine is here and is being led by pharmacogenomics

46 EXTRA SLIDES

47 Translational Leadership Team David Whitcomb MD PhD Pancreatitis Jaideep Behari MD PhD Fatty Liver Disease David Binion MD - IBD Philip Empey PharmD PhD Pharmacogenomics Erin Kershaw MD Diabetes, Obesty, HTG Larry Morland MD Rheumatoid Arthritis Ajay Wasan MD MSc Pain Zongqi Xia MD PhD Multiple Sclerosis