Determining the financial and decisional risks associated with the early phase trials Understanding the best study designs and selection of controls to eliminate candidates Understanding the end point selection for Cancer clinical trials Comparing progress free and overall survival in Intend To Treat (ITT) and per protocol (PP) populations Critically analysing the decision to proceed to Phase III or to terminate the trial Case study: Discussing the best practice strategies on ‘Phase II clinical trials of vaccines – to go or not to go to Phase III

1. Vaccines Summit 2012, Hyderabad, India
30-31 August, 2012
Dr. Bhaswat S. Chakraborty
Senior Vice President and Chairman,
R&D Core Committee, Cadila Pharmaceuticals Ltd.
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2. Contents
Determining the financial and decisional risks associated
with the early phase trials
Understanding the best study designs and selection of
controls to eliminate candidates
Understanding the end point selection for Cancer clinical
trials
Comparing progress free and overall survival in Intend To
Treat (ITT) and per protocol (PP) populations
Critically analysing the decision to proceed to Phase III or
to terminate the trial
Case study: Discussing the best practice strategies on
‘Phase II clinical trials of vaccines – to go or not to go to
Phase III
Concluding remarks
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3. Success of a [Phase II] Clinical Trial
Right Right conduct of the trial
Generalizable
Scientific
Adequate scope, time & Results
Questions
budget
Does this drug increase PoC of Efficacy, Safety,
survivability in …cancer? Dose & Frequency
Proceed to higher phases
3

4. Operational Challenges under Resource
Constraints
Resource constraints
 Fiscal
 Organizaional
 Technical
 Regulatory
Operational challenges under these constraints
 Operational planning scheduling under uncertainty
 Meeting design objectives, timelines & scope
 Supply chain management
 Quality and monitoring
 Completion within variable? budget
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5. Resource Constraints – some
characteristics
Fiscal
 Very common in developing countries – low and unrealistic budgets
given the scope & conduct of the study
 Difficulty in payments even commitment issues
 Gaining approval for out-of-pocket expenses is difficult
Organizational
 Team building, team performance and team achievement are often new
concepts in some cultures
Technical
 Often drugs are developed one by one rather than a portfolio of a group
of drugs which increases success probability
Regulatory
 Often a big challenge within the firm & national body– starting from
getting a trial license, not well developed review system, no defined
performance standard in timelines up to limited expertise and
overreaction to SAEs 5

6. Design & Control Issues in Phase II Cancer
Trials
 One of the major issues is the use of controls
 One study* finds that only ~20% Phase II Cancer Trials use active or
historical control or placebo (notwithstanding a higher reporting of Onco
trials)
 Remember the primary objective of a phase II cancer clinical trials is to
determine whether to proceed for a further Phase II or a Phase III study
 This requires basically a demonstration of substantial efficacy of a new
regimen
 However, oncology Phase II has been limited by high rates of failure (lack
of efficacy) in subsequent phase III testing
 This is in part because of use of single arm studies which can easily discard
a study with an apparent low efficacy that due to factors other than the drug
itself
*Michaelis et al. (2007). Clin Cancer Res,13, 2400–5
6

7. Design & Control Issues in Phase II Cancer
Trials
 One of the major issues is the use of controls
 One study* finds that only ~20% Phase II Cancer Trials use active or
historical control or placebo (notwithstanding a higher reporting of Onco
trials)
 Remember the primary objective of a phase II cancer clinical trials is to
determine whether to proceed for a further Phase II or a Phase III stdy
 This requires basically a demonstration of substantial efficacy of a new
regimen
 However, oncology Phase II has been limited by high rates of failure (lack
of efficacy) in subsequent phase III testing
 This is in part because of use of single arm studies which can easily discard
a study with an apparent low efficacy that due to factors other than the drug
itself
*Michaelis et al. (2007). Clin Cancer Res,13, 2400–5
7

8. Design & Control Issues in Phase II Cancer
Trials..
The “go or no go” decision at the end of phase II is perhaps the most
difficult one to make in the drug development cycle
 data are limited
 future investment required for a phase III trial is vast
 success of the company may depend on the drug in question
 an informative phase II trial is crucial
 after phase II, the decision makers need to understand toxicity and
pharmacokinetics, should have strong indications of activity in a
specific kind of cancer, and should have a clear sense of an approval
strategy
There are often gaps in this knowledge, and the decision is guided by
both fact and intuition.
The decision becomes easier when the case is unmet medical needs
Chabner B. (2007). Clin Cancer Res,13, 2307
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9. Design & Control Issues in Phase II Cancer
Trials...
Herceptin, Erbitux, and Avastin may have only modest activity as
single agents and produce few clinical responses
Their effect requires more subtle trial designs
 e.g., delay time to progression or recurrence or enhance response rates
to standard cytotoxic agents.
 single arm phase II trial, with response as the end point, may lead to the
abandonment of a valuable drug
Larger trials, and more complex phase II designs with TTP end
points, may be required to show effectiveness of the new agent
 here, concurrent controls, treated with standard agents or or other
strategies might show valuable aspects of the toxicity and effectiveness
of the new agent
 e.g sorafenib, [U of Chicago Researchers] randomized stable patients to
continued therapy vs. drug discontinuation, with positive for patients
continuing with experimental drug
9
Chabner B. (2007). Clin Cancer Res,13, 2307

10. Design & Control Issues in Phase II Cancer
Trials...
 The best design for phase II will depend on the nature of the agent, activity
in phase I, the disease setting, the degree of certainty about best dose and
schedule coming out of phase I trials, and the competition faced by the new
drug.
 A randomization involving two different doses of drug might show a dose-
response relationship
 e.g., imatinib, it is unclear whether escalation beyond the recommended 400
mg/d dose might have long-term benefit for certain patients.
 New molecular technologies offer remarkable insights
 gene expression profiling and molecular studies have illuminated distinct
subpopulations within pathologic categories of cancer
 role of epidermal growth factor receptor mutations in predicting response to
gefitinib and erlotinib
 development of biomarkers
 phase II setting is the setting for appropriate patient
10
Chabner B. (2007). Clin Cancer Res,13, 2307

11. Endpoints in Oncology Trials
 Must show either direct evidence of clinical benefit or improvement
in an established surrogate for clinical benefit
 Clinical benefit: survival improvement
 Overall survival (OS)
 Progress-free survival (PFS) (usually Ph III)
 Improvement in a patient’s quality of life (QOL) (usually Ph III)
 Other endpoints on which approval has been given are:
 Objective response rate (ORR)
 by RECIST or any radiological tests or physical examinations
 Improvement in survival, improvement in a QOL, improved physical
functioning, or improved tumor-related symptoms do not always be
predicted by, or correlate with, ORR
Source: US FDA Guidance
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12. Relative Merits
Endpoint Evidence Assessment Some Advantages Some Disadvantages
Survival Clinical benefit • RCT needed • Direct measure of • Requires larger and
• Blinding not benefit longer studies
essential • Easily • Potentially affected by
measured crossover therapy
• Precisely • Does not capture
measured symptom benefit
• Includes noncancer
deaths
Disease-Free Surrogate for • RCT needed • Considered to • Not a validated
Survival accelerated • Blinding be clinical benefit survival surrogate in most
(DFS) approval or preferred by some settings
regular • Needs fewer • Subject to assessment
approval* patients and bias
shorter studies than • Various definitions
survival exist
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13. Relative Merits..
Endpoint Evidence Assessment Some Advantages Some Disadvantages
Objective Surrogate for • Single-arm or • Can be assessed • Not a direct measure of
Response accelerated randomized in single-arm benefit
Rate (ORR) approval or studies can be studies • Usually reflects drug
regular used activity in a minority of
approval* • Blinding patients
preferred in • Data are moderately
comparative complex compared to
studies survival
Complete Surrogate for • Single-arm or • Durable CRs • Few drugs produce high
Response accelerated randomized represent obvious rates of CR
(CR) approval or studies can be benefit in some • Data are moderately
regular used settings (see text) complex compared to
approval* • Blinding • Can be assessed survival
preferred in in single-arm
comparative studies
studies
13

14. Overall Survival (OS)
 OS: The time from randomization until death from any cause
 Measured usually in the intent-to-treat (ITT) population
 Most reliable cancer endpoint, and when studies can be conducted to
adequately assess survival, it is usually the preferred endpoint
 Precise and easy to measure – no influence of technicality of measurement
 Bias is not a factor in endpoint measurement
 Survival improvement should be analyzed as a risk-benefit analysis to
assess clinical benefit
 OS should be evaluated in RCTs
 Historical trials are seldom reliable for time-dependent endpoints (e.g.,
OS, PFS).
 The OS in control arm has to be compatible
14

15. Rosell et al. (2008), Annals of Oncology, 19, 362–369
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16. Endpoints Based on Tumor Assessments
 Disease-free survival (DFS)
 Objective response rate (ORR)
 Time to tumor progression (TTP)
 Progress-free survival (PFS)
 Time-to-treatment failure (TTF)
 They are all time-dependent endpoints
 Collection and analysis of these endpoints are based on indirect
assessments, calculations, and estimates (e.g., tumor measurements)
 Two critical judgments:
1. whether the endpoint will support either accelerated approval or regular
approval
2. endpoint should be evaluated for the potential of bias or uncertainty in tumor
endpoint assessments
 Drug applications using studies that rely on tumor measurement-based
endpoints as sole evidence of efficacy may need confirmatory
evidence from a second trial
16

17. Rosell et al. (2008), Annals of Oncology, 19, 362–369
17

18. Cautions in Tumor Assessments
Accuracy in measuring tumors can differ among tumor settings
Imprecision can happen in locations where there is a lack of
demarcated margins (e.g., malignant mesothelioma, pancreatic
cancer, brain tumors).
When the primary study endpoint is based on tumor
measurements (e.g., PFS or ORR), tumor endpoint assessments
generally should be verified by central reviewers blinded
to study treatments
 This measure is especially important when the study is not blinded
 It may be appropriate for the FDA to audit a sample of the scans to
verify the central review process
18

19. Quality of Life (QoL) Endpoints
Global health-related quality of life (HRQL) have not served
as primary efficacy endpoints in oncology drug approvals
They are usually patient reported outcome measures
 For example, the FACT-L is a 44-item self-report instrument which measures
multidimensional quality of life in Phase II and III lung cancer clinical trials
 Reliability and validity of such multi-item instruments must be thoroughly
examined
For QOL to be used as primary endpoints to support cancer
drug approval, the FDA should be able to distinguish between
improvement in tumor symptoms and lack of drug toxicity
An apparent effectiveness advantage based on a global QoL
instrument can simply indicate less toxicity rather than
effectiveness
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20. Biomarkers
Usually not a good idea for cancer drug approval
Other than paraprotein levels measured in blood and urine for
myeloma, biomarkers assayed from blood or body fluids have not
served as primary endpoints
Not considered good predictors of clinical benefit
The FDA has sometimes accepted tumor markers as elements of a
composite endpoint
 e,g., clinical events such as significant decrease in performance status,
or bowel obstruction in conjunction with marked increases in CA-125
was considered progression in ovarian cancer patients
Biomarkers, however, can be useful in identifying prognostic
factors
 and in selection of patients and stratification factors to be
considered in study designs
20

21. Specific Symptom Endpoints
 Time to progression of cancer symptoms, an endpoint similar to TTP, is a
direct measure of clinical benefit rather than a potential surrogate
 Problems in measuring progression (e.g., missing assessments) also exist in
evaluating time to symptomatic progression
 Because few cancer trials are blinded, assessments can be biased
 delay between tumor progression and the onset of cancer symptoms can occur
 alternative treatments are initiated before achieving the symptom endpoint,
confounding this analysis
 patients may have minimal cancer symptoms
 also, tumor symptoms can be difficult to differentiate from drug toxicity
 Important
 composite symptom endpoint should have components of similar clinical
importance and the results should not be exclusively attributed to one
component
 missing data & infrequent treatment are also confounding factors
21

22. Intent-to-Treat Principle
 All randomized patients
 Exclusions on prespecified baseline criteria permissible
 also known as Modified Intent-to-Treat
 Confusion regarding intent-to-treat population: define and agree upon in
advance based upon desired indication
 Advantages:
 Comparison protected by randomization
 Guards against bias when dropping out is related to outcome
 Can be interpreted as comparison of two strategies
 Failure to take drug is informative
 Reflects the way treatments will perform in population
 More suitable for superiority trials
 Concerns:
 “Difference detecting ability”
22

23. Per Protocol Analyses
Focuses on the outcome data
Addresses what happens to patients who remain on
therapy
Typically excludes patients with missing or problematic
data
More suitable for non-inferiority trials
Statistical concerns:
 Selection bias
 Bias difficult to assess
23

24. Intent to Treat & Per Protocol
Analyses
Both types of analyses are important for approval
Results should be logically consistent
Design protocol and monitor trial to minimize
exclusions
Substantial missing data and poor drug compliance
weaken trial’s ability to demonstrate efficacy
24

25. ITT
PP
OS & PFS – ITT vs PP 25
Sandler et al. 2006. N Engl J Med, 355, 2542-50.

26. Belani et al. (2011), ASCO Annual Meeting
26

27. Decision to Proceed to Phase III or
Terminate
 This is a consideration for IA
 Stopping rules for significant efficacy
 Stopping rules for futility
 Measures taken to minimize bias
 A procedure/method for preparation of data for analysis
 Data has to be centrally pooled, cleaned and locked
 Data analysis - blinded or unblinded?
 Interim results must be submitted to IDMC
 What is the scope of recommendations from IA results? What
should be made known to the Sponsor?
 Safety? Efficacy? Both? Futility? Sample size readjustment for
borderline results?
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28. Decision to Proceed to Phase III or
Terminate..
 Single arm studies
 Futility is better predicted in IA than success
 However, when success/failure response is used
 Summarize success as the proportion of number of totally included
patients
 To proceed for Phase III, it is important to know the norm
(activity of current standard) and that the new treatment is
expected to exceed this
 Example
 The standard treatment for AML is fludarabine + ara-C (50% success)
 Addition of GCSF would be beneficial if Phase II shows ~70%
success
Thall & Simon (1994). Biometrics, 50, 337-349
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29. Concluding Remarks
 Clinical testing of new Oncology products is very sophisticated and
complex
 Cancer clinical data is very complex (censored, skewed, often fraught
with missing data point), therefore, proper hypothesization and statistical
treatment of data are required
 Resource challenges can affect operations and even the study design
 There are many endpoints that are scientifically valid but OS as primary
end point is often preferred by regulatory agencies
 PFS & Tumor assessment trials may need another confirmatory CT
 Endpoints must be demonstrative (directly or indirectly) of clinical
benefit
 Missing data, infrequent treatment, increased type I error and other
confounding factors must be addressed
 Consistent ITT & PP facilitate approval
 Carefully establish “go or no-go” rules and critically examine IA data;
single arm should exceed the “norm” of standard success
 Despite good knowledge in endpoints & trial design, meet & consult
FDA before initiating a pivotal trial.
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30. Thank you Very Much
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