Oncology BioMarkers in Adaptive Clinical Trial Design

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Oncology BioMarkers in Adaptive Clinical Trial
Design

• Bhardwaj Desai, MD,
• Kendle

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Outline

• Why biomarkers?
• Biomarkers and surrogate end points
• Examples
• Challenges

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Goulart, B. H.L. et al. Clin Cancer Res
2007136719-6726
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The Promises of Biomarkers

• In 2007 more that 34,000 papers dealing with
  biomarkers have been published
• Biomarkers are a child of the genomics
  technologies
• reduce risk in drug development (pharma)
• improve patient outcomes (healthcare providers)
• Activities
• earlier diagnosis
• patient stratification
• assessment of drug toxicity and efficacy
• disease staging
• disease prognosis

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Two types of stratification will entail
different consequences

• Patient stratification
• Different dosing based on patient genotype
• Could increase market size
• Change to get into occupied market
• The Blockbuster model of drug development would
  still hold
• Expanding the patient subgroup by growing
  experience
• Herceptin

• Disease stratification
• Different drugs given based on patient genotype
• Would decrease market size for an individual drug
• Emphasis on a group of minibusters rather than
  one blockbuster
• Expanding indications to other diseases with same
  underlying genetic cause of disease
• Glivec

Modified from Shah, Nat Biotech 2003
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Definitions(NIH Definitions Working Group)

• BiomarkerA characteristic that is measured and
  evaluated as an indicator of normal biologic
  processes, pathogenic processes, or pharmacologic
  processes to a therapeutic intervention.
• Clinical endpointA characteristic or variable
  that measures how a patient feels, functions, or
  survives.
• Surrogate endpointA biomarker intended as a
  substitute for a clinical endpoint.

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Scientific challenges

• Biomarker/transcript profile selection
• Definition of response predictors
• Assay development
• Platform and reagent standardization
• Defining sensitivity
• Minimizing variability
• Pharmacodynamic modeling
• Biomarker validation
• Biomarker ? surrogate

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Biomarker Validation

• A biomarker that is measured in an analytical
  test system with well established performance
  characteristics and for which there is an
  established scientific framework or body of
  evidence that elucidates the physiologic,
  toxicological, pharmacologic, or clinical
  significance of the test results.

From FDA Guidance for Industry Pharmacogenomic
Data Submissions. March 2005. http//www.fda.gov/c
ber/gdlns/pharmdtasub.pdf
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Surrogate Endpoint Definition

• A laboratory measurement or physical sign that is
  used in therapeutic trials as a substitute for a
  clinically meaningful endpoint that is a direct
  measure of how a patient feels, functions, or
  survives and is expected to predict the effects
  of the therapy.

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Clinical correlates surrogate endpoint
biomarkers used for evaluation of oncology drugs
and biological products

• Objective Response/ Response Rate
• Time to Progression
• Disease free survival or time to recurrence
• Progression-free survival
• Quality of life, symptom improvement, composite
  endpoints
• Intraephithelial neoplasiaIEN are precancers
  that are treated by drug therapy or surgical
  removal. Regression of existing or prevention of
  new IEN have been considered for supporting
  approval of drugs to prevent cancers or to treat
  precancers

Kelloff, 2005
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Why Use Surrogate Endpoints?

• Faster decisions
• Smaller trials
• Some accepted as predicting a clinical outcome
• Blood pressure - heart attack and stroke
• Bone mineral density - risk of osteoporotic
  fractures
• Viral loads - progression of HIV
• BUT must translate into clinical benefit!

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How are Biomarkers and Surrogate Endpoints
Related?

• Biomarker is a candidate surrogate marker
• Biomarker data alone cannot be used to register a
  product unless it is accepted as a surrogate
  endpoint
• All surrogate endpoints are biomarkers
• but not all biomarkers are surrogate endpoints!!

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Pros/Cons of Biomarkers

• Pros
• Objective
• Change more rapidly than other endpoints
• Improved efficacy and safety individualized
  medicine
• May reduce drug development costs
• May speed time to market
• Cons
• Validation complicated and costly
• Few validated biomarkers known

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Types of Biomarkers

• Translation Biomarker a biomarker that can be
  applied in both a preclinical and clinical
  setting.
• Disease Biomarker a biomarker that relates to a
  clinical outcome or measure of disease.
• Efficacy Biomarker a biomarker that reflects
  beneficial effect of a given treatment.
• Staging Biomarker a biomarker that distinguishes
  between different stages of a chronic
  disorder.
• Surrogate Biomarker a biomarker that is
  regarded as a valid substitute for a clinical
  outcomes measure.
• Toxicity Biomarker a biomarker that reports a
  toxicological effect of a drug on an in vitro
  or in vivo system.
• Mechanism Biomarker a biomarker that reports a
  downstream effect of a drug.
• Target Biomarker a biomarker that reports
  interaction of the drug with its target.

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Predictive biomarkers used in oncology drug
development
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Monitoring Tumor Response to Treatment In Vivo

• FDG-PET as an early indicator of response to
  chemotherapy or radiation therapy in some
  cancers
• PET imaging with radiotracers could be employed
  as a surrogate marker
• Trial endpoint both in phase 3 studies and at the
  "go/no go" decision point in phase 2 clinical
  trials

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There are already several tumor associated
Markers with (proven?) predictive value

• ß-HCG (Choriocarcinoma)
• ß-HCG (Testicular Tumors)
• AFP (Testicular Tumors)
• AFP (Hepatocellular Carcinoma)
• Calcitonin (Medullary Thyroid Carcinoma)
• Thyroglobulin (Differentiated Thyroid Cancer)
• PSA (Prostate Cancer)
• Monoclonal protein (multiple myeloma)

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Biomarker driven development/ Predictive medicine
Why will it start in oncology?

• Clinics
• Cancer is a family of complex and heterogeneous
  diseases
• Awareness of new technologies (eg. Genotyping)
• Oncology deliver clear quality of life benefits
  survival periods
• Efficacy and safety of established therapies is
  low (20-40)
• Narrow therapeutic index of conventional drugs

• Market
• Subsets of cancer patients are small, new Rx
  aimed for them would not threat the blockbusters
• High competitive pressure (several drugs in
  several pipelines)
• Reimbursement easier for Rx with clear
  cost-benefit ratios (pricing)
• High public awareness that cancer is an
  increasing disease
• Possibility for pharma companies becoming a niche
  leader

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Use of Biomarker in clinical practice

• Herceptin (Trastezumab) is a monoclonal Antibody
  against the her2/neu receptor
• HER-2 is over expressed or amplified in 25-30 of
  all women with breast cancer
• Herceptin is efficacious in 20 of HER-2
  positive patients
• The overall response rate in total target
  population is about 5
• Three diagnostic tests FDA approved (costs 100)
• Screening valuable until 1.5 responders (est.
  treatment costs are 7000 per patient)

Adrian Towse, Office of Health Economics
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One more

• WALL STREET JOURNAL. , May 5, 2005. CANCER
  DRUG DEEMED FAILURE, HELPS ASIANS
• Iressa as proved effective at treating lung
  cancer in Asian patients, even as it flopped in
  helping Caucasians, Blacks and just about
  everyone elsethrough a curious quirk in
  medicine. Asians respond well to therapy because
  they have a certain genetic mutation in their
  cancer cells that Iressa is good at targeting...
• As a result, Astra-Zeneca which initially
  planned big sales of Iressa in the US, is now
  adjusting its marketing plan to focus on Japan,
  China and other Asian markets.

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Irinotecan (Camptosar)

• Irinotecan proven 1st (5-FU and leucovorin) and
  2nd line prodrug therapy for metastatic
  colon/rectal cancer
• Providers/patients face a clinical predicament
  what is the optimal dose?
• Incidence of grade 3-4 neutropenia is 35
• Nearly 70 of patients need dose reduction
• Toxicity associated with active drug exposure

causes severe myelosuppression ...death due
to sepsis following myelosuppression ...adjust
doses based on neutrophil count
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Problem accumulation of SN-38

• Exposure dependent on metabolism of camptosar by
  UGT1A1
• Prodrug (irinotecan) metabolized to SN-38 (active
  drug)
• Rate-limiting metabolic enzyme encoded by UGT1A1
• Wide interpatient variability in UGT1A1 activity
• Patients with 28 variant (7 TA repeats) have
  reduced enzyme activity
• Homozygous deficient (7/7 genotype) patients have
  the greatest risk of neutropenia
• Neutropenia matters to patients
• Original label was silent on UGT information
  approved dose not optimized

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Camptosar Label Revised and FDA Approved UGT Test
Individuals who are homozygous for the
UGT1A128 allele are at increased risk for
neutropenia following initiation of CAMPTOSAR
treatment. A reduced initial dose should be
considered for patients known to be homozygous
for the UGT1A128 allele (see DOSAGE AND
ADMINISTRATION). Heterozygous patients (carriers
of one variant allele and one wild-type allele
which results in intermediate UGT1A1 activity)
may be at increased risk for neutropenia
however, clinical results have been variable and
such patients have been shown to tolerate normal
starting doses.
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EGFR as a therapeutic target

• Epidermal growth factor receptor (EGFR) gene
  (erbB1) first sequenced in a four-member family
  of structurally related type or subclass 1
  receptors known as tyrosine kinases.
• Critical for mediating the proliferation and
  differentiation of normal cell growth
• Widely expressed in epithelial, mesenchymal, and
  neuronal tissues
• Aberrant activation of the kinase activity of
  these receptors appears to play a primary role in
  solid tumor development and/or progression
• Breast, brain, lung, cervical, bladder,
  gastrointestinal, renal and head and neck
  squamous cell carcinomas, have demonstrated an
  over expression of EGFR relative to normal
  tissue, which is associated with a poor clinical
  prognosis

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Erlotinib (Tarceva)

• Potent EGFR tyrosine kinase inhibitor
• Pre-clinical anti-tumor activity
• Inhibits tumor cell line growth
• Activity in mouse xenograft models
• Increased RR, PFS, and OS in Phase 3

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Erlotinib vs. placebo in NSCLC
1.0
0.9
HR 0.73 P0.8
0.7
0.6
Surviving
0.5
0.4
0.3
0.2
Placebo N243 Median 4.7 mos
0.1
0.0
0
5
10
15
20
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HR is from the Cox regression model with the
following covariates ECOG performance status,
number of prior regimens, prior platinum and
best response to prior chemotherapy. P-value is
from two-sided Log-Rank test stratified by ECOG
performance status, number of prior regimens,
prior platinum and best response to prior
chemotherapy.
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Erlotinib in EGFR NSCLC
1.0
0.9
HR 0.65 P0.03 Erlotinib N78 Median 10.7 mos
0.8
0.7
0.6
Surviving
0.5
0.4
0.3
0.2
Placebo N49 Median 3.8 mos
0.1
0.0
0
5
10
15
20
25
SURVIVAL (mos)
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Angiogenesis

• Bevacizumab, Sorafenib, Sunitinib and
  Temsirolimus, have been approved for clinical use
  on the basis of results from randomized phase III
  clinical trials without significant contributions
  from biomarkers. No validated biomarkers of
  angiogenesis or antiangiogeneic activity are
  available for routine clinical use
• Biomarkers of angiogenesis might be useful for
  monitoring angiogenesis, assessing drug activity
  and distinguishing between active and inactive
  drugs, predicting clinical outcome and response
  to therapy, defining the optimum biological dose,
  facilitating development of combination
  therapies, and rapidly identifying resistance to
  treatment

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Current pharmacogenomic examples

• bcr/abl or 922 translocationimatinib mesylate
  (Gleevec)
• HER2-neutrastuzumab (Herceptin)
• C-kit mutationsimatinib mesylate (Gleevec)
• Thiopurine S-methyltransferasemercaptopurine and
  azathioprine
• UGT1A1-irinotecan (Camptosar)
• Cytochrome P-450 (CYP) 2D65-HT3 receptor
  antagonists and codeine derivatives
• -FDA package insert information
• -FDA-approved device

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Confounding factors and bias why biomarker
studies fail

• Accuracy of phenotype (disease) is critical
• All patients must have same disease
• Several causes lead to the same phenotype
• Inappropriate Dx method
• Inappropriate sample sizes / control groups
• Most diseases are multifactorial by nature
  (phenotype is affected by variants in numerous
  genes)
• The same biomarker signature can result in
  different phenotypes due to the effects of age,
  sex, environment, concomitant diseases,
  nutrition, co medication.

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Summary

• Biomarkers hold enormous promise
• Conventional oncology development - small benefit
  in a large patient population
• Targeted drug development may define large
  benefit in smaller population
• The devil will be in the details
• Validation is crucial (tools and profiles)
• New development structures must be built
• Flexible regulatory mechanisms
• Need for drug-diagnostics co-development paradigm
• Need for new partnerships between industry,
  government, academics

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Thank you
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