Biomarker Based PGx Strategies

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Biomarker Based PGx Strategies

• Rick Hockett, MD
• Chief Medical Officer
• Affymetrix

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Why Are Biomarkers So Important?
Providing meaningful improved health outcomes
for patients by delivering the right drug at the
right dose at the right time.
Goal Improve individual patient outcomes and
health outcome predictability through tailoring
drug, dose, timing of treatment, and relevant
information
Targeted Therapy
One size fits all
Tailoring
(e.g. oncology productscomprising drug and
companion diagnostic)
assess spectrum of patient response to therapy
stratify patient populations optimize
benefit/risk.
Measure something in a patient to learn how to
prescribe medicine
Tailoring is Broader Than Pharmacogenomics
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Increased BenefitRisk Scenarios
Providing meaningful improved health outcomes
for patients by improving diagnosis, prognosis,
or therapy choice.
Can apply one or more scenarios to each Lilly
compound. Scenarios can often be interdependent.
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Why do we think genetics will play?
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Pinpoint the right biomarker
Large Scale Fishing DNA 100K to 2x106
SNPs Chip Based Electrophoresis RNA
30K Chip Based -oligos Slide Based -
cDNAs Protein 1K upward Mass Spec
Med. Scale Confirm. DNA 2K to 30K Chip
Based Electrophoresis PCR Based RNA 30 to
1K Chip Based -oligos Slide Based
cDNAs RT-PCR Based Protein 50 to 500 Mass
Spec Luminex Type
Small Scale Valid. DNA 1 to 25 PCR
Based Electrophoresis RNA 1 to 25 RT-PCR
Based Protein 1 to 30 ImmunoAssay
Large Scale Fishing Whole Genome Scan
Medium Scale Confirmation Many Different Groups
Small Scale Validated Clinical Trial Support
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Shrinking Clinical PGx Funnel
Needs
Examples
Disease vs. Response
Predictive

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Apo E, CETP
5 - LO
vs.
Variants in Growth Genes
Situation Specific Onc vs. Neuroscience
DMET
OncotypeDx
Clinically Utilized PGx Tests
UGT1A1
Hercept Test
CYP2C9/VKORC1
c-kit
Tissue of Origin
HLA
EGFr
TPMT
Philly Chromosome
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Hurdles to applying -omics to medicine

• Strategic
• Gearing the infrastructure
• Obtaining the talent
• Technologic
• Information overload
• Lack of biologic understanding
• Platform challenges
• Regulatory
• Understand how to apply technology
• Implementation
• Clinician education, understanding, and acceptance

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DMET PlusDrugMetabolismEnzymes
TransportersAn Example of Applying New
Technologies to the Clinical Marketplace
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The Genesis of DMET

• March of 2004 Collaboration initiated between
  Lilly, ParAllele, and Affymetrix
• The goal for Eli Lilly was to develop a clinical
  solution for better understanding the genetic
  components behind metabolism and transport
• Better ability to understand PK outliers in early
  phase trials
• Build a database for selective recruitment of
  healthy volunteers with a defined genotype
• Work with the FDA in an attempt to decrease the
  number of biopharm (DDI) trials needed for future
  NDAs
• June 2006 was the inception of a working assay
  for clinical trials
• Dec 2007 first NDA was submitted the FDA

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Pinpoint the right biomarker
Using existing Affymetrix technology
Large Scale Fishing DNA 100K to 2x106
SNPs Chip Based Electrophoresis RNA
30K Chip Based -oligos Slide Based -
cDNAs Protein 1K upward Mass Spec
Med. Scale Confirm. DNA 2K to 30K MIP
Based True Materials RNA 30 to 1K Panomics
Expression Protein 50 to 500 Mass
Spec Luminex Type
Small Scale Valid. DNA 1 to 25 MIP
Based True Materials RNA 1 to
25 Panomics Expression Protein 1 to
30 ImmunoAssay
Large Scale Fishing Whole Genome Scan
Medium Scale Confirmation Many Different Groups
Small Scale Validated Clinical Trial Support
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Setting the stage for adoption of genetic
analysis tools for use in personalized medicine

• Risks associated with taking
• popular heart disease medication
• Plavix (Clopidogrel)
• Paper published in New England Journal of
  Medicine
•  
• Conclusion Patients taking Clopidogrel and who
  were carriers of a certain gene variation had
  higher rates of heart attack, death and other
  cardiac-related events
• Two additional independent studies recently
  published in NEJM and Lancet show similar PGx
  associations.
•  
•  

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No Relationship between Genetics and PK/PD for
Prasugrel, Significant Effect for Clopidogrel
Pharmacokinetics
Pharmacodynamics
Integrated Genetic Analyses in Healthy Subjects
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PGx associated clinical outcomes of 1459 acute
coronary syndrome patients treated with
clopidogrel were significant

• 1477 Patients were randomly assigned Plavix
  treatment with 98.8 being genotyped
• CYP2C19 variant allele (1) frequency in treated
  population was 27.1.
• Primary efficacy outcome composite of death from
  cardiovascular causes, MI and stroke.
• 395 variant carrier patients had a 1.5 fold
  higher risk of death vs non-carriers.
• 1389 Rx patients had stents implanted with a
  secondary endpoint of stent thrombosis.
• 375 2C19 variant patients had a 3 fold increase
  in risk of thrombosis.
• Two additional independent studies recently
  published in NEJM and Lancet show similar PGx
  associations.

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Pharmacogenomics in drug development
Development of a biomarker
Biomarker A physiological response or
laboratory test that occurs in association with
a pathological process and that has putative
diagnostic and/or prognostic utility
DNA or RNA Samples
A.
B.
Identification of potential biomarker or drug
target
C.
D.
Retrospective confirmation on clinical samples
Use of marker in prospective clinical trials
Patient Stratification
Plasma or Serum Samples
Patient Samples are the Key
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What we Must Do to Enable -omics Impact

• Align focus on what can be done and where
  genetics is likely to work
• Analyze, Integrate and Learn from data
• Enable the field of Molecular Epidemiology
• Enhance our biologic understanding of genetic
  influence of complex traits and produce more
  examples
• Develop and validate technologies for clinical
  use
• IT Infrastructure
• Standards Controls
• Educate the medical infrastructure
• Engage patients and third party payers

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How Do We Enable -omics Uptake?

• We cannot maintain silos
• We must enable certain, common functions
• Sample banking
• Clinical trials
• We must look to the regulators for direction
• Standards
• Controls
• Critical Path Initiative

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The Biotech/Genomics Revolution Increase the
BenefitRisk Ratio Develop clinical aids
for Diagnosis Prognosis Dosing Therapy Decisions