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Regulatory Review of Higher Phase Clinical Regulatory Review of Higher Phase Clinical TrialsTrials

Dr. Bhaswat S. Chakraborty

Sr. VP, R&D, Cadila Pharmaceuticals

ICMR sponsored and Sat Kaival College of Pharmacy organizedNational Symposium on EMERGING TRENDS IN CLINICAL RESEARCH

29th February, 2008

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Order of the TopicsOrder of the Topics

Clinical Trials– Regulatory phases 1,2,3 & 4

Review of Clinical Trials Data Requirements Study Design Considerations Controls

– Placebo, Active, NI Assay Sensitivity, Multiplicity of Analyses Interim Analysis Intent to Treat Analysis Final Analysis Conclusions

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4

Investigational New DrugInvestigational New Drug

The pharmaceutical industry sometimes provides advice to the FDA prior to submission of an IND

Sponsors, research institutions, and other organizations that take responsibility for developing a drug must show the FDA results of preclinical testing they've done in laboratory animals and what they propose to do for human testing

At this stage, the FDA decides whether it is reasonably safe for the company to move forward with testing the drug in humans

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Phase 1Phase 1

Phase 1 studies are usually conducted in healthy volunteers

The goal here is to determine what the drug's most frequent side effects are and, often, how the drug is metabolized and excreted

The number of subjects typically ranges from 20 to 100

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Early Phase Clinical TrialsEarly Phase Clinical Trials

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Phase 2Phase 2

Phase 2 studies begin if Phase 1 studies don't reveal unacceptable toxicity While the emphasis in Phase 1 is on safety, the emphasis in Phase 2 is on

effectiveness This phase aims to obtain preliminary data on whether the drug works in

people who have a certain disease or condition For controlled trials, patients receiving the drug are compared with similar

patients receiving a different treatment--usually an inactive substance (placebo), or a different drug

Safety continues to be evaluated, and short-term side effects are studied. Typically, the number of subjects in Phase 2 studies ranges from a few dozen to about 300

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Phase 3Phase 3

At the end of Phase 2, the FDA and sponsors try to come to an agreement on how the large-scale studies in Phase 3 should be done

How often the FDA meets with a sponsor varies, but this is one of two most common meeting points prior to submission of a new drug application

The other most common time is pre-NDA, right before a new drug application is submitted

Phase 3 studies begin if evidence of effectiveness is shown in Phase 2 These studies gather more information about safety and effectiveness,

studying different populations and different dosages and using the drug in combination with other drugs

The number of subjects usually ranges from several hundred to about 3,000 people

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Phase 4Phase 4

Postmarketing study commitments are called Phase 4 commitments– studies required of or agreed to by a sponsor

that are conducted after the FDA has approved a product for marketing

The FDA uses postmarketing study commitments to gather additional information about a product's safety, efficacy, or optimal use

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Examples of Regulatory Approvals: USFDAExamples of Regulatory Approvals: USFDA

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Goals of NDA ReviewGoals of NDA Review

Whether the drug is safe and effective in its proposed use(s), and whether the benefits of the drug outweigh the risks.

Whether the drug's proposed labeling (package insert) is appropriate, and what it should contain.

Whether the methods used in manufacturing the drug and the controls used to maintain the drug's quality are adequate to preserve the drug's identity, strength, quality, and purity.

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Drug Review StepsDrug Review Steps

1. Preclinical (animal) testing. 2. An investigational new drug application (IND) outlines what the sponsor of a new

drug proposes for human testing in clinical trials. 3. Phase 1 studies (typically involve 20 to 80 people). 4. Phase 2 studies (typically involve a few dozen to about 300 people). 5. Phase 3 studies (typically involve several hundred to about 3,000 people). 6. The pre-NDA period, just before a new drug application (NDA) is submitted. A

common time for the FDA and drug sponsors to meet. 7. Submission of an NDA is the formal step asking the FDA to consider a drug for

marketing approval. 8. After an NDA is received, the FDA has 60 days to decide whether to file it so it can

be reviewed. 9. If the FDA files the NDA, an FDA review team is assigned to evaluate the sponsor's

research on the drug's safety and effectiveness. 10. The FDA reviews information that goes on a drug's professional labeling (information

on how to use the drug). 11. The FDA inspects the facilities where the drug will be manufactured as part of the

approval process. 12. FDA reviewers will approve the application or find it either "approvable" or "not

approvable."

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Review ProcessReview Process

Once a new drug application is filed– an FDA review team evaluates whether the studies the sponsor submitted show that

the drug is safe and effective for its proposed use Team consists of medical doctors, chemists, statisticians, microbiologists,

pharmacologists, and other experts No drug is absolutely safe; all drugs have side effects

– "Safe" in this sense above means that the benefits of the drug appear to outweigh the risks.

The review team– analyzes study results– looks for possible issues with the application

e.g., weaknesses of the study design or analyses may agree with the sponsor's results and conclusions, or may need additional information

to make a decision Each reviewer prepares a written evaluation containing conclusions and

recommendations about the application These evaluations are then considered by team leaders, division directors, and office

directors, depending on the type of application

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Clinical Trials: Testing Medical Products in HumansClinical Trials: Testing Medical Products in Humans

Clinical studies, test potential treatments in human volunteers to see whether they should be approved for wider use in the general population

– A treatment could be a drug, medical device, or biologic, such as a vaccine, blood product, or gene therapy

– A new treatment may or may not be “better”– Complete and accurate research– Protection and well being of participants

Ethics, consent, audit

– Documentation

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Clinical Trials..Clinical Trials..

Drug studies in humans can begin only after an IND is reviewed by the FDA and a local institutional review board (IRB)

The board is a panel of scientists and non-scientists in hospitals and research institutions that oversees clinical research

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Institutional ReviewInstitutional Review

IRBs approve the clinical trial protocols– the type of people who may participate in the clinical trial– the schedule of tests and procedures– the medications and dosages to be studied– the length of the study– the study's objectives– other details

IRBs make sure the study is – acceptable– participants have given consent– Participants are fully informed of their risks– researchers take appropriate steps to protect patients from

harm

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DataData

There are legal and ethical reasons for reporting all relevant data collected during the drug development process

Some reporting strategies already exist in the 1988 Guidelines, ICH E3 and E9

Electronic Submissions and desktop review capabilities will help all of us make better use of clinical data in NDA’s

There may be better strategies and these should be considered

20Source: MDS, New Zealand

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What does FDA Look for?What does FDA Look for?

FDA approves a drug application based on– Substantial evidence of efficacy & safety from

“adequate and well-controlled investigations”  – A valid comparison to a control– Quantitative assessment of the drug’s effect

(21 CFR 314.126.) 

The design of cancer trials intended to support drug approval is very important

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Adequate and Well-Controlled StudiesAdequate and Well-Controlled Studies

Because the course of most diseases is variable, you need a control group, a group treated just like the test group, except that they don’t get the drug, to distinguish the effect of the drug from spontaneous change, placebo effect, observer expectations

21 CFR 314.126 describes the following controls– Placebo– No treatment– Dose response– Active control

Superiority of non-inferiority

– Historical Placebo, dose response or superiority are usually convincing studies

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Adequate and Well-Controlled Studies..Adequate and Well-Controlled Studies..

Minimization of Bias: a unidirectional tilt favoring one group, i.e., a non-random difference in how test and control group are selected, treated, observed, and analyzed – These are the 4 main places bias can enter

Remedies:– Blinding (patient and observer bias)– Randomization (treatment and control start out equal) – Careful specification of procedures and analyzes in a

protocol to avoid Choosing the most favorable analysis out of many (bias) Having so many analyses that one is favorable by chance

(multiplicity)

Source: RJ Temple, US FDA, Unapproved Drugs Workshop January 2007

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Design ConceptsDesign Concepts

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Purposes of Active Trials Purposes of Active Trials

The purpose of an active control trial could be to demonstrate that a new experimental

treatment is either superior to the control equivalent to the control, or non-inferior to the control superior to a virtual placebo

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Study Design: ApproachesStudy Design: Approaches

Randomised Controlled Trials (RCT) most preferred approach– Demonstrating superiority of the new therapy

Other approaches– Single arm studies (e.g., Phase II)

e.g., when many complete responses were observed or when toxicity was minimal or modest

– Equivalence Trials– No Treatment or Placebo Control Studies– Isolating Drug Effect in Combinations – Studies for Radiotherapy Protectants and Chemotherapy

Protectants

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Randomized Clinical TrialsRandomized Clinical Trials

Gold standard in Phase III

Single centre CT– Primary and secondary indications– Safety profile in patients– Pharmacological / toxicological characteristics

Multi-centre CT– Confirmation of the above– Effect size– Site, care and demographic differences– Epidemiological determination– Complexity– Far superior to meta-analyzed determination of effect

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Placebo Control Equality TrialsPlacebo Control Equality Trials

No anticancer drug treatment in the control arm is unethical Sometimes acceptable

– E.g., in early stage cancer when standard practice is to give no treatment

– Add-on design (also for adjuvants) all patients receive standard treatment plus either no

additional treatment or the experimental drug

– Placebos preferred to no-treatment controls because they permit blinding

– Unless very low toxicity, blinding may not be feasible because of a relatively high rate of recognizable toxicities

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Reasons for Active Control Reasons for Active Control

1. Ethics – For trials involving mortality or serious morbidity outcome, it is unethical to use placebo when

there are available active drugs on the market

2. Assay sensitivity – In trials involving psychotropic drugs, placebo often has large effect. An active control is

sometime used to demonstrate that the trial has assay sensitivity

3. Comparative purpose – To show how the experimental drug compares to another known active drug or a

competitor

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Non-Inferiority TrialsNon-Inferiority Trials

New drug not less effective by a predefined amount, the noninferiority (NI) margin

– NI margin cannot be larger than the effect of the control drug in the new study

– If the new drug is inferior by more than the NI margin, it would have no effect at all

– NI margin is some fraction of (e.g., 50 percent) of the control drug effect

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Drug or Therapy CombinationsDrug or Therapy Combinations

Use the add-on design – Standard + Placebo– Standard + Drug X

Effects seen in early phases of development – Establish the contribution of a drug to a

standard regimen– Particularly if the combination is more effective

than any of the individual components

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What to Measure?What to Measure?

Primary outcome measure: The health parameter measured in all study participants to detect a response to treatment. Conclusions about the effectiveness of treatment should focus on this measurement.

Secondary outcomes measure: Other parameters that are measured in all study participants to help describe the effect of treatment.

Baseline variables: The characteristics of each participant measured at the time of random allocation.

– This information is documented to allow the trial results to be generalised to the appropriate population/s

– Specific characteristics associated with the patient’s response to treatment (such as age and sex) are known as prognostic factors

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What to Measure? E.g., Cancer TrialsWhat to Measure? E.g., Cancer Trials

Time to event end points– Survival– Disease free survival– Progress (of disease) free survival

Objective response rates– Complete– Partial– Stable disease– Progressive disease

Symptom end points Palliation QoL

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Cancer Trials – End PointsCancer Trials – End Points

Endpoint Evidence Assessment Some Advantages Some Disadvantages

Survival Clinical benefit     RCT needed    Blinding not essential 

    Direct measure of benefit    Easily measured    Precisely measured

    Requires larger and longer studies    Potentially affected by crossover therapy    Does not capture symptom benefit    Includes noncancer deaths

Disease-Free Survival (DFS)

Surrogate for accelerated approval or regular approval*

    RCT needed     Blinding preferred

    Considered to be clinical benefit by some    Needs fewer patients and shorter studies than survival

    Not a validated survival surrogate in most settings    Subject to assessment bias    Various definitions exist

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Interim AnalysisInterim Analysis

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Interim analysisInterim analysis

after each new response or group of responses

an interim analysis is performed

enough evidence to stop the trial

or

continue the trial

continuous sequential or group sequential analysis

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Why interim analyses?Why interim analyses?

Ethics: superiority of a treatment

Safety: inferiority of a treatment /

toxicity of a treatment

Economy: = costly therapy

= no clinically relevant difference in effect

between treatments

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False Positives in Interim AnalysesFalse Positives in Interim Analyses

Interim analysis for a trial in non-Hodgkins lymphoma; n=130, IA after enrolment of each 25 patients

Response RateCP

Response RateCVP

Analysis 1 3/14 5/11 1.63

Analysis 2 11/27 13/24 0.92

Analysis 3 18/40 17/36 0.04

Analysis 4 18/54 24/48 3.25 0.05<P<0.1

Analysis 5 23/67 31/59 4.25 0.016<P<0.05

CP=Cytoxan-prednisoneCVP=Cytoxan-vincristine-prednisone

Source: Stuart J. Pocock, Clinical Trials

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Interim Analysis of DataInterim Analysis of Data

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Type 1 error at kth

test is NOT the same as the nominal p value for the kth test

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Considerations for IAConsiderations 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? – To whom the interim results will be submitted?

DSMB Expert Steering Group

– What is the scope of recommendations from IA results? – Safety? Efficacy? Both? Futility? Sample size

readjustment for borderline results?

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Equality DesignsEquality Designs(e.g., 2-Sample, Parallel)(e.g., 2-Sample, Parallel)

H0 : Є = 0 HA : Є ≠ 0

Reject H0 when

p̂ 1— p̂ 2

> z/2

√ p̂ 1(1— p̂ 1)/n1 + p̂ 2(1— p̂ 2)/n2

Where p̂ 1— p̂ 2 are true mean response rates from Test & Control

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Superiority/Non-Inferiority DesignsSuperiority/Non-Inferiority Designs(e.g., 2-Sample, Parallel)(e.g., 2-Sample, Parallel)

H0 : Є ≤ HA : Є > … Superiority

H0 : Є ≥ HA : Є < … Non-Inferiority

Reject H0 when

p̂ 1— p̂ 2 – > z

√ p̂ 1(1— p̂ 1)/n1 + p̂ 2(1— p̂ 2)/n2

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Survival Data – The Kaplan-Meier EstimatorSurvival Data – The Kaplan-Meier Estimator

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ival

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0.0 0.2 0.4 0.6 0.8 1.0

~80% Patient will survive beyond 0.35 years

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Include all Patients: ITTInclude all Patients: ITT

It can be justified to look at data and drop the “outliers”, poor compliers, inappropriately entered patients

It is even plausible and acceptable as an academic principle

But if not rigorously planned, such exclusion can lead to bias

Even when planned, it can lead to imbalances that also introduce bias

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Intent-to-Treat PrincipleIntent-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 realted to outcome

– Can be interpreted as comparison of two strategies– Failure to take drug is informative– Refects the way treatments will perform in population

Concerns:– “Difference detecting ability”

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Per Protocol AnalysesPer Protocol Analyses

Focuses on the outcome data

Addresses what happens to patients who remain on therapy

Typically excludes patients with missing or problematic

data

Statistical concerns:

– Selection bias

– Bias difficult to assess

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Intent to Treat & Per Protocol AnalysesIntent 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

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Missing DataMissing Data

Protocol should specify preferred method for dealing with missing primary endpoint– ITT

e.g., treat missing as failures e.g., assign outcome based on blinded case-by-case

review

– Per Protocol e.g., exclusion of patients with missing endpoint

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Multiple AnalysesMultiple Analyses

The two main problems introduced by multiple analyses are– firstly, the increased probability of detecting

intervention effects where none exist (“false positives” owing to multiple comparisons — type I errors)

– secondly, the limited capability (“power”) of trials to detect a true treatment effect in secondary outcomes if not enough participants are enrolled to show a statistically significant difference in these outcomes (“false negatives” — type II errors)

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Assay Assay SensitivitySensitivity

The critical question is whether a non-inferiority trial, for example, could distinguish the control from placebo and shown an effect of the non-inferiority margin

If it could – the trial is said to have said to have “assay sensitivity”

If a trial a trial has assay sensitivity– then if C-T < M, T had an effect

If the trial did not have assay sensitivity– then even if C-T < M, we have learned nothing

If you don’t know whether the trial had assay sensitivity, finding no difference between C and T means

– Both drugs were effective– Neither drug was effective

Source: RJ Temple, US FDA, Unapproved Drugs Workshop

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Assay Assay Sensitivity: Major Problem in NISensitivity: Major Problem in NI

In a non a non--inferiority trial, the trial itself does not show the study’s ability to distinguish active from inactive therapy. Assay ability to distinguish active from inactive therapy

Assay sensitivity must, therefore, be deduced or assumed, based on

1. historical experience showing sensitivity to drug effects2. a close evaluation of study quality and, particularly

important3. the similarity of the current trial to trials that were able to

distinguish the active control drug from placebo In many symptomatic conditions, such as depression, pain,

allergic rhinitis, IBS, angina, the assumption of assay sensitivity cannot be made

Source: RJ Temple, US FDA, Unapproved Drugs Workshop January 2007

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Data Safety and Monitoring Board (DSMB)Data Safety and Monitoring Board (DSMB)

All trials may not need a DSMB

DSMB Membership– Medical Oncologist, Biostatistician and Ethicist

Statistical expertise is a key constituent of a DSMB

Three Critical Issues

– Risk to participants

– Practicality of Periodic Review of a Trial

– Scientific Validity of the Trial

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ConclusionsConclusions

Randomized Clinical Trilas are very sophisticated and complex

Principal Investigators’, Trial Monitors’and Biostatisticians’ roles are invaluable

Higher Phase (Phases 2, 3) Clinical Trials provide for the main evidence of efficacy and safety

Clinical data is very complex (confounded, censored, skewed, often fraught with missing data point), therefore, proper hypothesization and statistical treatment of data are required

Prospective RCTs are usually the preferred approach for evaluation of new therapies

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ConclusionsConclusions

Clinically meaningful margins must be well defined in Control trials prospectively

– Superiority and non-inferiority margins must not be confused Two or one-sidedness of α should also be prospectively defined Power must be adequate Variance must be analysed using the right model Strategy for dealing with multiple end points must be prespecified

– Too many end points ot tests will increase the false positive (α) error Sometimes (e.g., in equality trials) statistically significant results may not be

medically significant

Data censoring or skewed data must be well defined– E.g., time to event data

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ConclusionsConclusions

Randomisation and blinding offer a robust way to remove bias in end-point estimations

Data must be accurately captured without any bias and analysed by prospectively described methods

Interim analysis should carefully plan ‘ spending’ function and the outcome measure to be analyzed

Final analysis should be done carefully, independently and meaningfully (medical as well as scientific)

Choose clinically relevant delta Design, conduct, and monitor trials to minimize missing data and poor compliance to

drug Analysis

– Both intent-to-treat and per protocol analyses should be conducted– Sensitivity analyses

Outstanding medical and statistical issues must be brought to the fore.

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Thank youThank you

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Order of the TopicsOrder of the Topics

Clinical Trials– Regulatory phases 1,2,3 & 4

Review of Clinical Trials Data Requirements Study Design Considerations Controls

– Placebo, Active, NI Assay Sensitivity, Multiplicity of Analyses Interim Analysis Intent to Treat Analysis Final Analysis Conclusions