CHALLENGES IN PHASE III CANCER CLINICAL

TRIALSNOT ADEQUATE INFORMATION

FROM PHASE II

Dr. Bhaswat S. ChakrabortySenior Vice President, R&D

Cadila Pharmaceuticals Ltd.

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Presented at the 2nd National Conference (NCIP) on “Emerging Trends in Drug Discovery, Development

and Molecular Targets for Cancer Research” at Nirma Univ., Ahmedabad, India, 24-25 January, 2017

CONTENTS Clinical trial conduct & data

Clinical Development Success & Consequences of Failure

Why examine Failure Reasons

Inadequate Ph II Information Sample size

Single arm studies

Historical control

Problems with Historical Controls

Patient heterogeity

End point consideration

Remedies

Concluding remarks2

Investigational Sites

Product Management

Project Management

Drug & Clinical Trial Development

Extended Picture

IRB Regulatory Documents

Relationship Building

eMails

Partners & Affiliates

Meetings

CROs

Contracts

Knowledge

Information

Safety

Communication

Resource Management

Data Capture Data Management

Multidirectional Flow of Activities, Data and Decisions3

CLINICAL DEVELOPMENT SUCCESS RATE

Of the 14 major disease areas, Likelihood of Approval (LOA):Oncology had the lowest (5.1%)

Hematology had the highest (26.1%)

Sub-indication analysis within Oncology revealed hematological cancers had 2x higher LOA

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Bio-Industry Analysis June 2017

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Consequences of failure can be very dramatic

MOST COMMON REASONS OF PHASE III ONCO TRIAL FAILURE

Lack of efficacy

Lack of Safety

Very rarely Quality

Commercial/Financial/Administrative

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WHY EXAMINE THE CAUSES OF FAILURE? Discoverer or Investigator: difficult personal experience

given non-clinical data promising

Ethical: Why thousands of patients were exposed to a compound that did not provide a possibility for clinical improvement

Cancer is the 2nd leading cause of mortality in the US

Successful development is relevant not only to professionals but to the general public as well

Potentially huge savings in resources7

WHAT DOES THE LITERATURE SAY (RE CAUSES OF FAILURE?)

“Negative” findings are typically not published or are published after a substantial delay

Even when published, crucial elements of the study e.g., statistical design are often missing

Original analysis missing, only a retrospectively-defined analysis provided

to have clues or new direction for future research

Gap between +ve & -ve study publications:, a survey of reported breast cancer Phase 2 studies found

that 80% had positive outcome [Perone F et al. (2003). Lancet 4:305-311]

However, ClinicalTrials.gov can give you some insight

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BASICS OF PHASE III FAILURE

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False positive from Ph II: Phase 2,Test is safe & efficacious in targeted population,while the reverse is true

Wrong design and implementation of the Ph III, Sample size, patient heterogeneity, wrong end-point etc. …

Retzios AD (2009) Bay Clin R&D Services

WRONG INFORMATION FROM PH II In all areas – Efficacy, Safety, Patient population &

sample size, Randomization, Hypotheses, Outcome variables, Levels of α or β, Dose..

Many reasons for inaccuracies all the above areas

Of all phases of CTs, Ph II trials are more likely to give false positives

Any inaccurate information from this phase enhances the possibility of failure in Ph III

Efficacy based Ph II dose ranging study may be required

Toxicity-wise dose ranging study may not make sense 10

Retzios AD (2009) Bay Clin R&D Services

SAMPLE SIZES Sample sizes are usually smaller (N<300) in Ph II

programs

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d is the tolerance interval of difference between the outcome variable of test and control arms; usually kept large e.g., 20-40%

In actual Ph III studies the “clinical-benefit” oriented endpoits e.g., OS show much smaller margins

Often re-examination and underpowered Ph II studies false +ve

“Investigators consistently make overly-optimistic assumptions regarding treatment benefits when designing RCTs.”

Gan HK et al (2012). J Natl Cancer Inst., 104: 590-598

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SINGLE ARM PH II STUDIES SA, Two-stage Ph II studies have been very common in

Onco

Such oversimple design is based on assumptions: tumors are unlikely to regress without pharmacological

intervention although certain tumor types show high spontaneous regression rates

% response for the standard treatment (which constitutes a historical control) can be adequately defined

Ph III success depend heavily of how well the historical controls have been defined and

Ph II conclusions in both stages therein are overoptimistic & underpowered 13

Retzios AD (2009) Bay Clin R&D Services

PROBLEMS WITH HISTORICAL CONTROLS

Historical controls are frowned upon and usually discouraged by regulatory guidance outside Oncology

Historical controls are not appropriate comparator for data collected prospectively because of differences in concomitant treatment

demographics

study entry criteria

time and type of assessments

methodology of measurement

number of other study provisions …14

Retzios AD (2009) Bay Clin R&D Services

WHY MULTI-ARM, RANDOMIZED

DESIGNS WITH ACTIVE OR PLACEBO CONTROL ARE BETTER?

Historical controls are inadequate or non-existent for the newer cytostatic agents

These agents do not result in tumor shrinkage but may have a substantial impact on OS prohibit tumor growth and metastases

but do not result in substantial tumor size reduction during Ph II studies’ short observation period

Since OS takes a number of years of observation, Ph II RCTs of cytostatic agents normally utilize disease progression endpoints

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PATIENT HETEROGENEITY Patient heterogeneity in small sized Ph II trials remains

a major challenge

If relevant covariates (e.g., patient molecular phenotype) are not balanced, a +ve or -ve difference from control may reflect imbalance in these covariates study: weekly docetaxel + trastuzumab vs weekly paclitaxel

plus trastuzumab in NSCLC

randomized patients also stratified on HER-2 protein expression (trastuzumab targets the HER-2/neu receptor)

The study did not reveal any advantages for these treatments, but the approach was valid

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RANDOMIZED DISCONTINUATION DESIGNS Two stage trial

all patients are treated with the test

patients with stable disease are then randomized to either the test or control (placebo or current treatment)

disease progression is assessed

stage 1 ceases when calculated stage 2 randomized sample size is achieved

Essentially, these are enriched designs

The resulting sample is more homogeneous

reduces variance and increases power of thestudy

Problems: the drug effect has been amplified & blinding in stage 2 may be difficult if the active treatment has a certain toxic profile

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END-POINT CONSIDERATIONS

In Ph III, the primary endpoint must be well-defined and show accepted clinical benefit (often OS)

In Ph II, surrogate endpoints (usually pharmacodynamic or disease progression) may be OK but not correspond directly to measurable clinical benefit

Whereas provides strong evidence of pharmacological activity

Ph II endpoints are usually speedier and less costly

usually PFS, objective tumor response, TTP

RECIST or WHO criteria tumor response correlates well with OS for solid tumors &cytotoxic compounds

tumor response does not work for melanoma and renal cell cancer and for cytostatic agents 18

PROBLEMS (& MERITS) OF TTP & PFS

In many cases Ph II PFS and TTP correlate with Ph III OS outcome

Works well for cytostatic anti-cancers

Problems with PFS and TTP

highly influenced by frequency of assessments

Disease progression in period of observation (few mo to a yr) is highly variable among patients

Sometimes it is difficult to assign lack of progression to drug’s pharmacological action

both PFS and TTP are very susceptible to investigator bias

cannot be used in non-randomized, multi-stage trials19

FAULTY CONDUCT OF PH II STUDIES

Many Ph II studies are inadequately conducted

Numerous protocol violations and deviations protocol violations noted in ≥ 20% of enrolled subjects make the study

unreliable

GCP violations are rampant across the globe

Data integrity issues

Sites and investigators are not appropriately trained

Go/no go decisions are often strongly affected by the desire to succeed at any cost PoCs are often Proof of Cleverness

the therapeutic effect is overestimated & consequently, the pivotal studies fail to achieve the desired endpoint 20

COMPREHENSIVE FAILURE TRIGGERS

Drivers of Failure

Examples

Inadequate Basic Science

•Beneficial effects in animal models not reproduced in humans •Poor understanding of target disease biology

Flawed Study Design

•Patient population definition changed from phase –II to phase –III•Phase –II surrogate endpoint not confirmed by Phase-III clinical outcomes

Suboptimal dose selection

•Inadequate dose finding in Phase-II•Poor therapeutic indices

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Parexel

COMPREHENSIVE FAILURE TRIGGERS..

Drivers of Failure

Examples

Flawed data collection and analysis

• Phase-II false positive effects were not replicated in Phase-III•Overoptimistic assumptions on variability and treatment difference•Missing data; attrition bias; rater bias•Wrong statistical tests; other statistical issues

Problems with study operations

•Data integrity issues; GCP violations•Recruitment, dropouts, noncompliance and protocol•Missing data; unintentional unblinding

Other •Insufficient landscape assessment of current standard of care and precedents.

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WELL DESIGNED PH II RCT

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Belani, Chakraborty, Modi & Khamar (2016) Annals of Oncology

ASTRAZENECA’S THE 5R FRAMEWORK

Right Target

•Strong link between target and disease•Differentiated efficacy •Available and predictive biomarkers

Right Tissue

•Adequate bioavailability and tissue exposure•Definition of PD biomarkers•Clear understanding of pre-clinical and clinical PK/PD•Understanding of drug-drug interactions

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Optimize a rational and effective the entire Clinical Development process

ASTRAZENECA’S THE 5R FRAMEWORK..

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•Differentiated and clear safety margins•Understanding of secondary pharmacology risks•Understanding of reactive metabolites, Genotoxicity, dr-dr interactions •Understanding of target liability

Right Patients

•Identification of the most responsive patient population•Definition of risk-benefit for given population

Right Commercial Potential

•Differentiated value proposition versus standard of care•Focus on market access, payer and provider•Personalized healthcare strategy, including diagnostic and biomarkers

Right Safety

OTHER AREAS OF REDUCING

PHASE III FAILURE RISKS

Replacement of the current gold standard, the randomized controlled trial, with real-world evidence

Wearable devices that collect real-time data

Adaptive licensing

Next-generation sequencing and improved understanding of the genetic basis of disease

Basket/master protocols

Phase III failures cannot be eliminated, can only be reduced 26

CONCLUDING REMARKS Well designed, properly conducted Ph II cancer RCTs can

provide a sound basis of go/no go for Ph III

Careful evaluation of historical data, correct design and sample size, appropriate end-point are some of the keys

A good trade-off between completing Ph II in time and obtaining accurate information is required

Planning at Ph II level should include a clear idea as to what needs to be achieved in the pivotal Ph III both in terms of the population to be treated & therapeutic advantage

to be sought

A comprehensive clinical development & data integrity plan helps

Also awareness of the competitive environment and the construction of a target label ae required

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THANK YOU VERY MUCH

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