Omics, Biomarkers, Personalized Medicine: A New Era, or More of the Same?

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Omics, Biomarkers, Personalized Medicine A
New Era, or More of the Same?

• Klaus Lindpaintner
• Roche Genetics/Roche Center for Medical Genomics

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Differential drug efficacy
Same symptoms Same findings Same disease (?)
Same Drug.
Genetic Differences
Different Effects
?
Possible Reasons Non-Compliance
Drug-drug interactions Chance Or.
SNP
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Pharmacotherapy State-of-the-Art

• Inter-individual differences in drug efficacy
• Significant incidence of serious adverse effects
  among elderly hospitalized patients (US)
• Serious 6.7 2 M cases
• Lethal 0.3 100,000 cases
  JAMA 982791200

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Pharmacogenetics and Personalized MedicineAn
altogether new concept?

• Knowledge of inter-individual differences wrt
  metabolism as old as civilization 6th century
  B.C. Pythagoras observesthat ingestion of fava
  beans is harmful to some individuals yet
  innocuous to others
• Finding the optimal treatment for every patient
  is as old as medicine differential diagnosis
• Tailoring treatments to drug-specific test
  results is nothing new. Example antibiotics
• Gram-positive bacteria e.g. penicillin
  derivatives
• Gram-negative bacteria e.g. aminoglycosides
• M. tuberculosis isoniazid/rifampin/pyrazinamide

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Yet great excitement/hyperbole New buzzwords,
or more?

• MedLine citations for biomarker recent
  exponential growth
• 1 in 6 is a review paper where are the data?
• MedLine citations for personalized and
  individualized medicine
• 1 in 2 (81 of 183) articles is a review article
  for Personalized Medicine,
• 2 in 3 (18 of 30) for Individualized Medicine
• Where ARE the data?

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Bridging a Historical Divide
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Pharmacogenetics, PharmacogenomicsGlossary of
Terms

• Pharmacogenetics
• a concept to provide more patient/disease-specific
  health care
• based on the effects of inherited (or acquired)
  genetic variants
• assessed primarily by sequence determination (or
  single gene expression)
• one drug many genomes (patients)
• focus patient variability
• Pharmacogenomics (1)
• a concept to provide more patient/disease-specific
  health care
• based on the effects acquired (or inherited)
  genetic variants
• assessed primarily by expression profiles (many
  mRNAs)
• one drug many genomes (patients)
• focus patient variability
• Pharmacogenomics (2)
• a tool for compound selection/drug discovery
• many drugs one genome (inbred animal/chip)
• focus compound variability

as conceptualized by Motulsky (1957), Vogel
(1959), Kalow (1962) and endorsed in the 2003
Nuffield Councils Report on Pharmacogenetics
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2 Major Classes of Pharmacogenetics Both
Resulting in Patient Stratification

• Strictly affecting drug response not predictive
  of disease risk Differentiating people
  (classical pgx Archibald Garrod)
• Pharmacokinetics (not only M, but also AADE)
• Pharmacodynamics
• Has not had much impact
• Related to molecular subclass of clinical
  diagnosis Differentiating disease (molecular
  differential diagnosis)
• Inherently linked to disease mechanism/prognosis
• Likely increasing impact in indications where we
  begin to treat causally oncology, inflammatory
  disease
• Both are conceptually rather different (and
  arguably the second should not be included) but
  have practically the same consequencePatient
  stratification according to novel, DNA-based
  parameters

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Omeprazole response rate and CYP2C19
response frequency ()
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Drug metabolism Inherited differences affect
drug effects
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Pharmacogenetics molecular DDCase Study
Herceptin
Bimodal response 2/3 of patients addition of
Herceptin to chemoRx ? no benefit 1/3
of patients addition of Herceptin to chemoRx
? 50 survival time increased by factor 1.5
(20 ?29 weeks)
Low HER2
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Xeloda (capcitabine)Patient stratification
based on enzyme patterns
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BiomarkersWhats new and why now?

• Availability of powerful, highly parallel new
  screening methods (omics) makes looking for new
  biomarkers a reasonable proposition.
• Paradigm shift(?) maturation of these basic cell
  and molecular biology tools makes them newly
  applicable to later-stage RD
• Opportunities personalized medicine
• Challenges technical, scientific
  (clinical-epidemiological) economical, ethical
• CAVEAT 1 Association ? Causality
• Good news and bad news

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Caveat 2 Responders Non-RespondersReality
Check
FDA benchmark 35 improvement/response
AN
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Single Gene Disease
Mutation
health outcome
health outcome
intermediatephenotype
intermediatephenotype
Heritability h2 1
Deterministic possible stigma
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Diseases
Common Complex Diseases
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Single Gene Disease
Mutation
health outcome
intermediatephenotype
health outcome
intermediatephenotype
Common Complex Disease
health outcome
health outcome
intermediatephenotype
intermediatephenotype
SNP
Probabilistic, not deterministic - no reason for
stigma.
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Complex Common DiseaseNature and Nurture
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Heritability estimates in CCD
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Heritability estimates in cancer
Czene et al, Int J Cancer 99260 2002
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Medical Progress Evolution or Revolution?
Historic Drivers of Medical Progress
Clinical expertise
Genetics
Classical epidemiology
More differentiated, molecular understanding of
pathology and drug action
Molecular Disease Definition Molecular Diagnosis
Clinical Disease Definition Clinical Diagnosis
in-vitro Diagnostics
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Consumption
Phlebotomy
Tuberculosis
Heart Failure
Cancer
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Pharmacogenetics vs. other MarkersA useful
distinction?
alteration germ-line in origin heritable
alteration somatic acquired (environment,
life-style)
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Pharmacogenetics and beyond Biomarkers

• Key conceptMore targeted medicines
  (personalized medicine)
• More effective
• Safer
• More cost-effective (?)
• Based on a better understanding of
  inter-individual differences among patients
• Inherited (the classical pharmacogenetics)
• Acquired (flavors of disease, underlying
  molecular heterogeneity of any one clinical
  diagnosis molecular differential diagnosis)
• Paradigm carry out specific test that point to
  one or another medicine as optimal for the
  patient before prescribing it. What does not
  matter Nature of test (DNA, RNA, protein,
  other) What does matter Information content

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Biomarker tests in medical practiceTwo sets of
considerations

• Test performance
• Analytical performance QC and accreditation of
  labs
• Clinical performance
• Clinical validity retrospective/observation
  studies
• Clinical utility prospective intervention
  trials
• Note Prior probability critical for test
  performance, esp. screens (sensitivity/specificity
  , PPV/NPV)
• Nature of illness
• Serious (life-threatening) illnessDefault
  dont withhold in error If in doubt
  treat
• Less serious illnessDefault dont treat in
  error If in doubt dont treat

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EGFR MutantsMuch ado about?
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EGRF-R variants Colocation with ATP-binding
domain
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Regulators are Taking Note
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Interpretation? Consequences?

• NEJM
• 8/9 responders for mutation
• 7/7 non-responders for mutation
• 2 of 25 untreated for mutation
• Pre-testing will increase response rate to 100
  among those who test
• Pre-testing will result in denial of treatment
  to 11 of who would responders
• Pao et al, MSKCC (PNAS)
• 7/10 responders for mutation
• 8/8 non-responders for mutation
• 4/81 NSCLC smokers for mutation
• 7/15 non-smoker, adeno-Ca for mutation
• Pre-testing will result in denial of treatment
  to 30 of who would be responders

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EGF-R variants and Drug Response

• Gefitinib (IRESSA) Response in Caucasians
  10Prevalence of variants in Boston
  patients 2/25
• (NEJM)
• Gefitinib (IRESSA) Response in Japanese 28Preva
  lence of variants in Japanese patients 26
• (Science)
• Erlotinib (TARCEVA) Monotherapy in NSCLSEGFR
  Mutratoin prevalence 12Response Rate 42

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Analytical Performance MetrologyAything but
straight-forward

• Precision
• Repeatability under same conditions, precision
  in a series of measurement in the same run and
• Reproducibilityunder different conditions, which
  are usually specified, e.g. day-to-day or lab-to
  lab
• Trueness
• the closeness of agreement of an average value
  from a large series of measurements with a "true
  value" or an accepted reference value.
• Numerical value bias
• Accuracy
• referring to a single measurement and comprising
  both random and systematic influences.
• Numerical value total error of measurement.

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Biomarker tests in medical practiceTwo sets of
considerations

• Test performance
• Analytical performance QC and accreditation of
  labs
• Clinical performance
• Clinical validity retrospective/observation
  studies
• Clinical utility prospective intervention
  trials
• Note Prior probability critical for test
  performance, esp. screens (sensitivity/specificity
  , PPV/NPV)
• Nature of illness
• Serious (life-threatening) illnessDefault
  dont withhold in error If in doubt
  treat
• Less serious illnessDefault dont treat in
  error If in doubt dont treat

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Analytical performanceThe dirty (not so) little
secret

• Multiple complex variables
• Tissue heterogeneity
• Limited sample quantity and quality (FFPE)
• LCDM/macro-dissection commonly necessary
• PCR-pre-amplification
• 4 exons x 2 amplification runs each

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Analytical performance EGFR sequencingSometimes,
far from it
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EGFR mutation analysis analytical performanceThe
dirty (not so) little secret

• Multiple complex variables
• Tissue heterogeneity
• Limited sample quantity and quality (FFPE)
• LCDM/macro-dissection
• PCR-pre-amplification
• 4 exons x 2 amplification runs each
• How to deal with drop-outs?
• How to deal with non-replicated mutations
  artifact or quantitative manifestation of
  relative abundance of mutation?
• None of current publications disclose this
  difficulty
• Own experience using different calling
  algorithms
• Algorithm 1 6.1 (13 mut / 200 wt / 94
  indeterminate)
• Algorithm 2 7.5 (15 mut / 186 wt / 106
  indeterminate)
• Algorithm 3 9.9 (23 mut / 210 wt / 74
  indeterminate)

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EGFR-Mutations, Erlotinib, and SurvivalThe
picture is more complex
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Biomarker tests in medical practiceTwo sets of
considerations

• Test performance
• Analytical accuracy QC and accreditation of
  labs
• Clinical performance
• Clin validity retrospective/observation studies
• Clinical utility prospective intervention
  trials
• Note Prior probability critical for test
  performance, esp. screens (sensitivity/specificity
  , PPV/NPV)
• Nature of illness
• Serious (life-threatening) illnessDefault
  dont withhold in error If in doubt
  treat
• Less serious illnessDefault dont treat in
  error If in doubt dont treat

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Optimizing Sensitivity vs. SpecificityTarget
Product Profile Definition is Essential
Note Sliding the ROC-cutoff value may be more
difficult with (categorical) genotype
data than with other (quantitative) biomarker
data
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Biomarker performanceUp and down the ROC curve
Serious illness dont withhold inappropriately
Efficacy marker High sensitivity
Less serious illness dont prescribe
inappropriately
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Case-in-point Herceptin/HerCepTestThe search
for new biomarkers and its implications
Status quo, ? 66 success rate ? no potential
responder denied Rx
Add-on-BM scenario 1 ? 78 success rate ? 5
of would-be responders denied Rx
Add-on-BM scenario 2 ? 88 success rate ? 20
of would-be responders denied Rx
Specificity of combined Her2 and new BM tests
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Not all that glitters is gold TPMT
Thiopurine-treated patients with adverse drug
reactions
positive test predicts, but negative tests
by no means excludes SAE299 negative tests for
every one positive test
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Economic considerationsHow far is segmentation
of markets feasible?
Exhaustive pharmacogenetic research efforts have
narrowed your niche market down to Harry
Finkelstein of Newburg Heights here.
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Emergence of sub-critically small segmentsA
self-limited proposition

• RetrospectivelyGiven biomedical variance,
  biomarker-defined segments are unlikely to be
  recognizable unless they represent a significant
  share of the overall patient population.
• ProspectivelySmall segments known to exist will
  either not be addressed for lack of business
  case, or under Orphan Drug Guidelines

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The Tightening Reimbursement ClimateBiomarker
strategies may be essential
Elkin et al J Clin Oncol 2004 22854 ff (/
conv. rate 1/1/2003, not PPP-adjusted)
NB National Institute for Clinical Excellences
(NICE) threshold for approving
reimbursement through NHS believed to be
UK 30,000 per QUALY (quality-adjusted life
year)
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Biomarkers likely outcome

• The concept applies potentially to most
  compounds
• It will in fact, however, become reality only for
  some/few compounds but we will have to look at
  all to find the few!
• (We will likely see more examples of
  pathology-related biomarker-based
  stratification (Herceptin-paradigm) that advance
  efficacy and most likely in oncology and
  inflammatory/autoimmune disease)
• Multifactorial algorithms likely to emerge,
  rather than simple, one-variable models but
  highly complex algorithms unlikely.
• Essential Define Target-Product-Profile
• Key Modesty, Realism, robust Optimism
• we will not have perfect medicines BUT
• we will have increasingly better medicines

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No 1-on-1 custom tailoring, but towards a much
better fit
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Remember All medical decisions/knowledge are
based on group-derived (aggregate) data
analysis.Data on individuals (Harry
Finkelstein) are anecdotal and (largely)
medically/clinically meaningless
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Without information, the doctor cannot act.
With information, he cannot but act.
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HL Menckens Law
Every complex problem
has a simple solution.
And it is always wrong.