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2013-04-17: The Promise, Current State, And Future of Personalized Medicine
2013-04-17: The Promise, Current State, And Future of Personalized Medicine
2013-04-17: The Promise, Current State, And Future of Personalized Medicine
2013-04-17: The Promise, Current State, And Future of Personalized Medicine
2013-04-17: The Promise, Current State, And Future of Personalized Medicine
2013-04-17: The Promise, Current State, And Future of Personalized Medicine
2013-04-17: The Promise, Current State, And Future of Personalized Medicine
2013-04-17: The Promise, Current State, And Future of Personalized Medicine
2013-04-17: The Promise, Current State, And Future of Personalized Medicine
2013-04-17: The Promise, Current State, And Future of Personalized Medicine
2013-04-17: The Promise, Current State, And Future of Personalized Medicine
2013-04-17: The Promise, Current State, And Future of Personalized Medicine
2013-04-17: The Promise, Current State, And Future of Personalized Medicine
2013-04-17: The Promise, Current State, And Future of Personalized Medicine
2013-04-17: The Promise, Current State, And Future of Personalized Medicine
2013-04-17: The Promise, Current State, And Future of Personalized Medicine
2013-04-17: The Promise, Current State, And Future of Personalized Medicine
2013-04-17: The Promise, Current State, And Future of Personalized Medicine
2013-04-17: The Promise, Current State, And Future of Personalized Medicine
2013-04-17: The Promise, Current State, And Future of Personalized Medicine
2013-04-17: The Promise, Current State, And Future of Personalized Medicine
2013-04-17: The Promise, Current State, And Future of Personalized Medicine
2013-04-17: The Promise, Current State, And Future of Personalized Medicine
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2013-04-17: The Promise, Current State, And Future of Personalized Medicine

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By Jeff Otto

By Jeff Otto

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  • 1. The promise, current state, andfuture of personalized medicineJeffrey M. Otto, PhD MBA National Director, CHI’s Center for Translational Research April 17, 2013
  • 2. Overview§  Intro to personalized medicine §  Short look at the early days, circa2000-2001 §  Review of current state §  Discussion of the gap between the initialpromise and the current state §  The CTR’s approach §  Summary and conclusion
  • 3. Definitions§  Personalized medicine: the tailoring of medical treatment tothe individual characteristics of each patient in order to classifyindividuals into subpopulations that differ in their susceptibilityto a particular disease or their response to a specific treatment. Preventative or therapeutic interventions can then beconcentrated on those who will benefit, sparing expense and sideeffects for those who will not. §  Biomarkers: An indicator or pattern in a patient that reflectsnormal biologic processes, disease processes, or the effect ofmedical treatment. §  Translational Research: Translational research transformsscientific discoveries arising from laboratory, clinical, orpopulation studies into clinical applications to reduce diseaseincidence, morbidity, and mortality.
  • 4. Personalized Medicine 101The Promise §  Better diagnoses and earlier interventions §  More efficient drug development §  More effective therapies The Challenges §  Intellectual property §  Regulatory oversight §  Reimbursement Retrieved 03/28/2013 fromhttp://www.personalizedmedicinecoalition.org/about/about-personalized-medicine
  • 5. The ClassicPersonalized Medicine ParadigmToxic   Not  Toxic  Effec%ve  Not  Effec%ve  The standard approach to medicine does not distinguish between individuals…. …although individuals within a population are often very different. Biomarkers can be used to stratify patients… …and to select a safer, more efficacious treatment for the individual.
  • 6. Personalized medicine is akin to shoemanufacturing:Like shoes at a department store, manydifferent drugs are available. Althoughseveral drugs may be available to treata particular disease, all drugs are notsafe or effective for all people.Similar to sizing for a shoe,molecular diagnostic testsinform the selection of theappropriate drug.Although the selected drugwas not createdspecifically for you, it ismore likely to work for you.
  • 7. Biomarkers currently usedin clinical medicine§  Electrocardiogram §  PET brain image §  Bone densitometricmeasurement §  Serum chemistries §  Auto-antigens in blood §  Pulmonary function test §  X-ray §  MRI
  • 8. Examples of -Omic Biomarkers§  DNA variation q  SNPs, rearrangements,CNVs §  DNA methylation §  Chromosomalrearrangements §  microRNA §  RNA expression §  Protein panels
  • 9. The beginning of “irrationalexuberance” in personalized medicine
  • 10. June  11,  2001    "We  strongly  believe  that  pharmacogenomics  will  shortly  transform  the  way  drugs  are  developed,  marketed,  and  prescribed.  I  think  youre  going  to  see  the  benefits  of  this  appearing  within  a  five-­‐year  %meframe,"      Gerald  F.  Vovis    SVP  &  Chief  Technology  Officer  of  Genaissance  Pharmaceu%cals  
  • 11. The Challenge of “chasing the tail”§  Statistically significantresults are easier toachieve betweenpopulations at the leftand right ends of thediagram, but are notnecessarily meaningfulfrom a health economicsperspective Treatment efficacyFrequencyinpopulation
  • 12. Genomic medicine milestones1953:  Structure  of  DNA  elucidated  by  Watson  &  Crick  1950 19601956:  1st  discovery  of  a  gene%c  basis  for  selec%ve  toxicity  (primaquine  –  an%malarial  drug)  19701977:  DNA  sequencing  technology  developed  by  Fred  Sanger  1977:  Discovery  of  CYP450  metabolic  enzymes  -­‐  varia%on  in  these  enzymes  significantly  influence  the  effec%ve  dose  of  a  drug  19801994:  EGFR  TKI  cla19901990:  The  Human  Genome  Project  is  launched  20001998:  HHER2+  m1998:  1sHercep-­‐Milestones  Research  Drugs  Diagnos?c  Drug  +  CDx  Regulatory  
  • 13. Overview of Targeted Cancer TherapiesManchana, T., Ittiwut, C., Mutirangura, A., & Kavanagh, J. J. (2010). Targeted therapies for rare gynaecological cancers. LancetOncol, 11(7), 685-693. doi: http://dx.doi.org/10.1016/S1470-2045(09)70368-7
  • 14. Why so few success stories?§  Genomic era of medicine isless than 15 yrs old §  Technology is notsufficient on its own §  Biomarkers are notnecessarily “fit forpurpose” §  Test needs to work withinthe existing healthcareworkflow §  Stakeholder alignment §  Is the patient the customer? Cartoon: Agres, Ted. (2009) The hunt for personalization. Retrieved 03/08/2013 fromhttp://www.dddmag.com/articles/2009/06/hunt-personalization
  • 15. Catholic Health Initiatives &The Center for Translational Research
  • 16. CHI: 5th Largest Hospital Network in USStrength in Numbers§  5th largest US network§  81 acute care hospitals in 17 states§  40 LTC facilities§  86,000 employees§  2,900 physicians and midlevel providers§  Diverse markets with 90% ranked #1 or #2§  $15B in assets, $9.8B in annual revenue§  FY 2012 – provided $715M+ in charity care16
  • 17. CIRI OverviewCenter  for  Transla%onal  Research  (CTR)  • Discovery  Research  Network  na%onal  biospecimen    collec%on  &  repository  with  EHR  connec%vity  • Biomarker  discovery,  molecular  diagnos%c  development  &  valida%on    Center  for  Clinical  Research  (CCR)  • Ownership  and  management  of  • Research/clinical  trial  opera%ons:  single  site,  mul%-­‐site,  mul%-­‐therapeu%c    • Research  data  warehouse  connected  to  EHR  and  de-­‐iden%fied  pa%ent  data/outcomes    Center  for  Healthcare  Innova%on  (CHCI)  • Design  and  test  innova%ons  in  care  delivery  • Co-­‐develop  new  technology  and  methods  to  manage  popula%on  health      17 Personalized  Medicine  Clinical  Opera%ons  +  EHR  Research  Environment  Popula%on  Health  Management  
  • 18. Executive Summary:The CHI/CIRI Research “Onion”18 CCR  CTR  CHCI  CIRI  Hospitals  Government  Academia  Industry  Lab  Pharmacy  Radiology  Tumor  Registry  Pathology  
  • 19. Cloud-based Informatics:Network StrengthResearch  Datamart  CCR   CTR  Research  Data  Analysis  19
  • 20. Cloud-based informatics:Patient Data & Sample AnnotationHospital  Network  Digital  Slide  Images  (QC)  Staging  –  pTNM,  cTNM  Images  Radiology  Reports  Genomic  Data  Blood  Report  Demographics  Clinical  History  Epidemiology  Drugs  Interac%ons/Adverse  Events  Consent  &  IRB  Approval  Pre-­‐Sampling  Ischemic  dura%on    Chain  of  Custody  Anesthesia  outcomes  Lab  Radiology  ADT*  Tumor  Registry  Pharmacy  Pathology  Post-­‐Sampling  Time  to  freeze  samples  Type  and  %me  of  fixa%ve  Tissue  QC  ELECTRONIC  HEALTH  RECORD   BIOREPOSITORY  NETWORK  Drug  and  Biomarker  Discovery  Protocol  De-Identified Data WarehouseBiospecimenVariablesTissue ReportAnesthesiaIschemic TimeTime to FreezeTumor StagingDiagnosis% Tumor% NecrosisImage Data DemographicsMRIPET/CT ScanImage ReportAgeRaceGene ExpressionProfilingGenotype/Sequence DataAffy Human GenomeExpression ArrayEGFRKRASFollow Up Data TreatmentTreatment OutcomeRecurrenceDisease StatusDrugsRadiationResponse      Pre-­‐Acquisi%on  Variables                    Post-­‐Acquisi%on  Variables  *Admission/Discharge/Transfer  TRANSLATIONAL  INFORMATICS  
  • 21. Bench to Bedside Translational ResearchCTR  CCR  Benefits  to  CHI  Hospitals  Clinical  Trials  Personalized  Medicine  Benefits  to  Pa%ents  Bener  Drugs  Bener  Diagnos%cs  Research  Ques?ons  Hypothesis  Generated  Hypothesis  Tested  Results:    IP  &  Publica?ons  Generated  Benefits  Research  Data  21 Key  Opinion  Leaders  Physicians  Academic  Researchers  CIRI  Staff  Others  21
  • 22. Study Design: An Integrated ApproachFFPE  Sample  EHR  data  Biosta%s%cal  Analysis  Predic%ve  Signature  Gene%c  Epigene%c  Environmental  22
  • 23. Thank You

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