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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 * * Like to strike a ... – PowerPoint PPT presentation

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


1
Omics, Biomarkers, Personalized Medicine A
New Era, or More of the Same?
  • Klaus Lindpaintner
  • Roche Genetics/Roche Center for Medical Genomics

2
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
3
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

4
Pharmacogenetics and Personalized Medicine An
altogether new concept?
  • Knowledge of inter-individual differences wrt
    metabolism as old as civilization 6th century
    B.C. Pythagoras observes that 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

5
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?

6
Bridging a Historical Divide
7
Pharmacogenetics, Pharmacogenomics Glossary 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
8
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 consequence Patient
    stratification according to novel, DNA-based
    parameters

9
Omeprazole response rate and CYP2C19
response frequency ()
10
Drug metabolism Inherited differences affect
drug effects
11
Pharmacogenetics molecular DD Case 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
12
Xeloda (capcitabine) Patient stratification
based on enzyme patterns
13
Biomarkers Whats 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

14
Caveat 2 Responders Non-Responders Reality
Check
FDA benchmark 35 improvement/response
AN
15
Single Gene Disease
Mutation
health outcome
health outcome
intermediate phenotype
intermediate phenotype
Heritability h2 1
Deterministic possible stigma
16
Diseases
Common Complex Diseases
17
Single Gene Disease
Mutation
health outcome
intermediate phenotype
health outcome
intermediate phenotype
Common Complex Disease
health outcome
health outcome
intermediate phenotype
intermediate phenotype
SNP
Probabilistic, not deterministic - no reason for
stigma.
18
Complex Common Disease Nature and Nurture
19
Heritability estimates in CCD
20
Heritability estimates in cancer
Czene et al, Int J Cancer 99260 2002
21
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
22
Consumption
Phlebotomy
Tuberculosis
Heart Failure
Cancer
23
Pharmacogenetics vs. other Markers A useful
distinction?
alteration germ-line in origin heritable
alteration somatic acquired (environment,
life-style)
24
Pharmacogenetics and beyond Biomarkers
  • Key concept More 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

25
Biomarker tests in medical practice Two 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) illness Default
    dont withhold in error If in doubt
    treat
  • Less serious illness Default dont treat in
    error If in doubt dont treat

26
EGFR Mutants Much ado about?
27
EGRF-R variants Colocation with ATP-binding
domain
28
Regulators are Taking Note
29
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

30
EGF-R variants and Drug Response
  • Gefitinib (IRESSA) Response in Caucasians
    10 Prevalence of variants in Boston
    patients 2/25
  • (NEJM)
  • Gefitinib (IRESSA) Response in Japanese 28 Preva
    lence of variants in Japanese patients 26
  • (Science)
  • Erlotinib (TARCEVA) Monotherapy in NSCLS EGFR
    Mutratoin prevalence 12 Response Rate 42

31
Analytical Performance Metrology Aything but
straight-forward
  • Precision
  • Repeatability under same conditions, precision
    in a series of measurement in the same run and
  • Reproducibility under 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.

32
Biomarker tests in medical practice Two 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) illness Default
    dont withhold in error If in doubt
    treat
  • Less serious illness Default dont treat in
    error If in doubt dont treat

33
Analytical performance The 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

34
Analytical performance EGFR sequencing Sometimes,
far from it
35
EGFR mutation analysis analytical performance The
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)

36
EGFR-Mutations, Erlotinib, and Survival The
picture is more complex
37
Biomarker tests in medical practice Two 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) illness Default
    dont withhold in error If in doubt
    treat
  • Less serious illness Default dont treat in
    error If in doubt dont treat

38
Optimizing Sensitivity vs. Specificity Target
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
39
Biomarker performance Up and down the ROC curve
Serious illness dont withhold inappropriately
Efficacy marker High sensitivity
Less serious illness dont prescribe
inappropriately
40
Case-in-point Herceptin/HerCepTest The 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
41
Not all that glitters is gold TPMT
Thiopurine-treated patients with adverse drug
reactions
positive test predicts, but negative tests
by no means excludes SAE 299 negative tests for
every one positive test
42
Economic considerations How far is segmentation
of markets feasible?
Exhaustive pharmacogenetic research efforts have
narrowed your niche market down to Harry
Finkelstein of Newburg Heights here.
43
Emergence of sub-critically small segments A
self-limited proposition
  • Retrospectively Given biomedical variance,
    biomarker-defined segments are unlikely to be
    recognizable unless they represent a significant
    share of the overall patient population.
  • Prospectively Small segments known to exist will
    either not be addressed for lack of business
    case, or under Orphan Drug Guidelines

44
The Tightening Reimbursement Climate Biomarker
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)
45
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

46
No 1-on-1 custom tailoring, but towards a much
better fit
38
40
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
47
Without information, the doctor cannot act.
With information, he cannot but act.
48
HL Menckens Law
Every complex problem
has a simple solution.
And it is always wrong.
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