CLINICAL TRIALS

INTRODUCTORY CONCEPTS

Dr Purnendu Sekhar Das

1

TOPICS TO BE DISCUSSED

1. Clinical Trials – Definitions, Importance of Trials

2. Role of Clinical trials in Clinical Product Development

3. Different types of Clinical trials and their phases

4. Important Regulations and Guidelines – ICH & GCP

5. Design of a Clinical Trial

6. Randomization and Blinding

7. Data Management in Clinical Trials – Standards (CDISC, SDTM)

8. Overview of Analysis of Clinical Trials

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CLINICAL TRIALS DEFINITIONS AND IMPORTANCE

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WHAT EXACTLY ARE CLINICAL TRIALS?

Clinical trials are scientific investigations that examine and evaluate safety and efficacy of different therapies in human subjects. There are various definitions available as different individuals have tried to which try to capture the essence of clinical trials at different times, e.g.

Meinert (1986) indicates that a clinical trial is a research activity that involves administration of a test treatment to some experimental unit in order to evaluate the treatment.

Piantadosi (1997) simply defined a clinical trial as an experimental testing of medical treatment on human subject.

The Code of Federal Regulations (CFR)* defines a clinical trial as the clinical investigation of a drug that is administered or dispensed to, or used involving one or more human subjects (21 CFR 312.3)*.

Three important key words in these definitions of clinical trials are experimental unit, treatment, and evaluation of the treatment.

4

THE THREE IMPORTANT KEY WORDS

Experimental Unit

An experimental unit is usually referred to as a subject from a targeted population under study. Therefore the experimental unit is usually used to specify the intended study population to which the results of the study are inferred. For example, the intended population could be patients with certain diseases at certain stages or healthy human subjects.

Treatment

In clinical trials a treatment can be a placebo or any combinations of a new pharmaceutical identity (e.g., a compound or drug), a new diet, a surgical procedure, a diagnostic test, a medial device, a health education program, or no treatment. Other examples include surgical excision, radiotherapy, and chemotherapy as a combination of surgical procedure and drug therapy for breast cancer; magnetic resonance imaging (MRI) with a contrast imaging agent as a combination of diagnostic test and a drug for enhancement of the efficacy of a diagnostic test.

Evaluation

In addition to the traditional evaluation of effectiveness and safety of a test treatment, clinical trials are also designed to assess quality of life, pharmacogenomics, and pharmacoeconomics such as cost-minimization, cost-effectiveness, and cost-benefit analyses to human subjects associated with the treatment under study. It is therefore recommended that clinical trials should not only evaluate the effectiveness and safety of the treatment but also assess quality of life, impact of genetic factors, pharmacoeconomics, and outcomes research associated with the treatment.

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21 CFR (CODE OF FEDERAL REGULATIONS) The Code of Federal Regulations (CFR) is the codification of the general and permanent

rules and regulations (sometimes called administrative law) published in the Federal Register by the executive departments and agencies of the Federal Government of the United States.

Title 21 is the portion of the Code of Federal Regulations that governs food and drugs within the United States for the Food and Drug Administration (FDA). It is divided into 3 chapters:

Chapter 1 - Food and Drug Administration, Department of Health and Human Services

Important sections in relation to Clinical Trials are:

50 Protection of human subjects in clinical trials

54 Financial Disclosure by Clinical Investigators

56 Institutional Review Boards that oversee clinical trials

58 Good Laboratory Practices (GLP) for nonclinical studies

312 Investigational New Drug Application

Chapter 2 - Drug Enforcement Administration, Department of Justice

Chapter 3 - Office of National Drug Control Policy

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SPONSORS FOR CLINICAL TRIALS IN THE U.S.

Pharmaceutical and Biotechnology companies – which must prove the safety and effectiveness of their medicines before they can be marketed

National Institutes of Health (NIH) – which are funded by the US Government. The National Cancer Institute (NCI), which is a part of the NIH, sponsors a good portion of the thousands of cancer clinical trials going on at any point of time.

Other government agencies, including parts of the Department of Veterans Affairs and the Department of Defence, also sponsor cancer clinical trials.

University Medical Schools and Hospitals, or any other medical research centers.

Some non-profit organizations and even individual or group of physicians also sometimes sponsor clinical trials.

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SIGNIFICANT HISTORICAL EVENTS FOR CLINICAL TRIALS

YEAR CLINICAL TRIALS REGULATIONS

1906 Pure Food and Drug Act (Dr. Harvey Wiley)

1923 First randomization to experiments (Fisher and Mackenzie)

1931 First randomization of patients to treatments in clinical trials Formation of U.S. Food and Drug Administration

1937 Formation of National Cancer Institute

1938 U.S. Federal Food, Drug and Cosmetic Act

1944 First publication of results from a multicenter trial

1952 Publication of Elementary Medical Statistics FDA makes designation of Prescription Drug or OTC

1962 Amendment to the U.S. Food, Drug, and Cosmetic Act

1966 Mandated creation of the local boards (IRB) for Funding by U.S. Public Health Service

1977 Publications of General Considerations for Clinical Evaluation of Drugs - FDA

1984 Drug Price Competition and Patent Term Restoration Act

1988 Publication of Guidelines for the Format and Content of the Clinical and Statistical Section of an Application

1990 Publication of Good Clinical Practice for Trials on Medicinal Products in the European Community

1997 Publication of Good Clinical Practice (GCP) U.S. FDA Modernization Act

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THE BIGGER LANDSCAPE ROLE IN CLINICAL PRODUCT DEVELOPMENT

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SPONSOR DEFENCE NDA SUBMITTED

CLINICAL PRODUCT DEVELOPMENT - PHASES

PRECLINICAL RESEARCH

CLINICAL RESEARCH

NDA REVIEW

ANIMAL TESTING

SYNTHESIS & PURIFICATION

PHASE 1

PHASE 2

ACCELERATED DEVELOPMENT/REVIEW

RATIONAL DRUG DESIGN

TREATMENT IND

PARALLEL TRACK

PHASE 3

IND SUBMITTED

REVIEW DECISION SPONSOR/FDA MEETINGS ADVISORY COMMITTEES

SHORT TERM

LONG TERM

INSTITUTIONAL

REVIEW BOARDS

LAUNCH

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IMPORTANT TERMS

INVESTIGATIONAL NEW DRUG (IND): A new drug, antibiotic drug, or biological drug that is used in a clinical investigation. It also includes a biological product used in vitro for diagnostic purposes.

INSTITUTIONAL REVIEW BOARD (IRB): 1. A committee of physicians, statisticians, researchers, community advocates, and others that ensures that a clinical trial is ethical and that the rights of study participants are protected. All clinical trials in the U.S. must be approved by an IRB before they begin. 2. Every institution that conducts or supports biomedical or behavioral research involving human participants must, by federal regulation, have an IRB that initially approves and periodically reviews the research in order to protect the rights of human participants. It is similar to the Independent Ethics Committee (IEC) outside the United States.

NEW DRUG APPLICATION (NDA): An application submitted by the manufacturer of a drug to the FDA - after clinical trials have been completed - for a license to market the drug for a specified indication.

TREATMENT IND: IND stands for Investigational New Drug application, which is part of the process to get approval from the FDA for marketing a new prescription drug in the U.S. It makes promising new drugs available to desperately ill participants as early in the drug development process as possible. Treatment INDs are made available to participants before general marketing begins, typically during Phase III studies. To be considered for a treatment IND a participant cannot be eligible to be in the definitive clinical trial.

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RATIONAL DRUG DESIGN

Drugs work by interacting with target molecules (receptors) in our bodies and altering their activities in a way that is beneficial to our health. In some cases, the effect of a drug is to stimulate the activity of its target (an agonist) while in other cases the drug blocks the activity of its target (an antagonist).

Throughout most of the history of medical science, new drugs have been discovered though a process of trial-and-error or simply through sheer luck. As the demand for new and more effective drugs has increased, a new method of drug development called Rational Drug Design has begun to replace the old methods. In rational drug design, biologically active compounds are specifically designed or chosen to work with a particular drug target. Rational drug design often involves the use of molecular design software, which researchers use to create three-dimensional models of drugs and their biological targets. For this reason, the process is also known as computer-aided drug design.

There are two major types of drug design. The first is referred to as ligand-based drug design and the second, structure-based drug design.

Ligand based - Ligand-based drug design (or indirect drug design) relies on knowledge of other molecules that bind to the biological target of interest. These other molecules may be used to derive a pharmacophore model which defines the minimum necessary structural characteristics a molecule must possess in order to bind to the target.

Structure based - Structure-based drug design (or direct drug design) relies on knowledge of the three dimensional structure of the biological target obtained through methods such as x-ray crystallography or NMR spectroscopy.

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EXAMPLE OF AN ANTICANCER DRUG IN ACTION

Mechanism of Action - Imatinib mesylate (Gleevec) in Chronic Myeloid Leukemia

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STRATEGIES OF STRUCTURE-BASED DRUG DESIGN

STRATEGY A STRATEGY B

NO

NO YES

YES YES NO

PHARMACOPHORE** IDENTIFICATION

PHARMACOPHORE

MODIFICATION

POTENTIAL DRUG

FIT FOR RECEPTOR

POTENTIAL DRUG

CHANGE FRAGMENT

LIGAND FRAGMENTS

GROWING

ACTIVE SITE IDENTIFICATION

COMPLETE GROWING

FIT FOR RECEPTOR

**A pharmacophore was first defined by Paul Ehrlich in 1909 as "a molecular framework that carries (phoros) the essential features responsible for a drug’s (=pharmacon's) biological activity" (Ehrlich. Dtsch. Chem. Ges. 1909, 42: p.17) 14

CLASSIFICATION DIFFERENT TYPES AND PHASES

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DIFFERENT TYPES OF CLINICAL TRIALS

Treatment trials test experimental treatments, new combinations of drugs, or new approaches to surgery or radiation therapy.

Prevention trials look for better ways to prevent disease in people who have never had the disease or to prevent a disease from returning. These approaches may include medicines, vaccines, vitamins, minerals, or lifestyle changes.

Diagnostic trials are conducted to find better tests or procedures for diagnosing a particular disease or condition. Diagnostic trials usually include people who have signs or symptoms of the disease or condition being studied.

Screening (Early detection) trials test the best way to detect certain diseases or health conditions.

Quality of Life trials (or Supportive Care trials) explore ways to improve comfort and the quality of life for individuals with a chronic illness.

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DIFFERENT PHASES OF CLINICAL TRIALS

Clinical trials involving new drugs are commonly classified into four phases (I, II, III and IV). Each phase of the drug approval process is treated as a separate clinical trial. If the drug successfully passes through Phases I, II, and III, it will usually be approved by the national regulatory authority for use in the general population. Phase IV are 'post-approval' studies. Before pharmaceutical companies start clinical trials on a drug, they conduct extensive pre-clinical studies.

THE PHASES:

PRE-CLINICAL - It involves in vitro (test tube or cell culture) and in vivo (animal) experiments using wide-ranging doses of the study drug to obtain preliminary efficacy, toxicity and pharmacokinetic information. Such tests assist pharmaceutical companies to decide whether a drug candidate has scientific merit for further development as an investigational new drug (IND).

PHASE I TRIALS: Initial studies to determine the metabolism and pharmacologic actions of drugs in humans, the side effects associated with increasing doses, and to gain early evidence of effectiveness; may include healthy participants and/or patients.

PHASE II TRIALS: Controlled clinical studies conducted to evaluate the effectiveness of the drug for a particular indication or indications in patients with the disease or condition under study and to determine the common short-term side effects and risks.

PHASE III TRIALS: Expanded controlled and uncontrolled trials after preliminary evidence suggesting effectiveness of the drug has been obtained, and are intended to gather additional information to evaluate the overall benefit-risk relationship of the drug and provide and adequate basis for physician labelling.

PHASE IV TRIALS: Post-marketing studies to delineate additional information including the drug's risks, benefits, and optimal use.

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PRE-CLINICAL TRIALS

As described earlier, a preclinical trial involves in vitro (test tube or cell culture) and in vivo (animal) experiments using wide-ranging doses of the study drug to obtain preliminary efficacy, toxicity and pharmacokinetic information.

Steps involved in designing a Pre-Clinical Trial/Study:

Identifying a Drug Target: All drugs target specific points in biochemical pathways. Almost all illnesses except infectious diseases are caused by problems associated with specific biochemical pathways. Identifying the appropriate target step in the biochemical pathway is critical and can determine the chances of success of the prospective drug molecule.

Developing a Bioassay: A bioassay is a “live” system that is devised to measure the effects of a drug. It varies from a cell or tissue culture system to organs or even a whole living being. For example, a zebra fish embryo can be used to observe the effects of drugs on bone density, blood vessel growth, among other systems.

Screening the drug in the Bioassay: This is a screening test done with the bioassay to determine the safety and effectiveness of the molecule. The drug must clear this step.

Establishing effective and toxic doses: This step involves establishing the safe and toxic dose ranges. Future studies take cues from here about the dose ranges to be tested in humans.

Filing for an approval as an IND (Investigational New Drug): After all these steps are cleared the drug is fit for an application to the FDA as an IND.

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PHASE 1 CLINICAL TRIALS

Phase 1 Clinical Trials are the earliest trials in the life of a new drug or treatment. They are usually small trials, recruiting anything up to about 30 patients (mainly healthy volunteers), although often a lot less. These trials are often conducted in an inpatient clinic, where the subject can be observed by full-time staff. The subject who receives the drug is usually observed until several half-lives of the drug have passed.

These trials are designed to obtain the following information:

Safety – Determine the most significant adverse events in human subjects.

Tolerability – The safe dose range is determined by dose escalations and corresponding serial lab tests.

Pharmacokinetics – How the drug molecule is absorbed in the body and its metabolites are distributed and eliminated from the body

Pharmacodynamics – The effects of the drug on the body, i.e. how the effects of the drug vary with the plasma concentration.

Types of Phase 1 trials:

SAD – Single Ascending Dose

MAD – Multiple Ascending Dose

Food Effect – Effects of food substances on the absorption of the drug

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PHASE 2 CLINICAL TRIALS

Phase 2 Clinical Trials (typically Therapeutic Exploratory) are controlled clinical studies conducted to evaluate the effectiveness of the drug for a particular indication or indications in patients with the disease or condition under study and to determine the common short-term side effects and risks.

Once the initial safety of the study drug has been confirmed in Phase I trials, Phase II trials are performed on larger groups (20-300) and are designed to assess how well the drug works, as well as to continue Phase I safety assessments in a larger group of volunteers and patients. Studies in Phase II are typically conducted in a group of patients who are selected by relatively narrow criteria, leading to a relatively homogeneous population and are closely monitored.

An important goal for this phase is to determine the dose(s) and regimen for Phase III trials. Early studies in this phase often utilise dose escalation designs to give an early estimate of dose response and later studies may confirm the dose response relationship for the indication in question by using recognised parallel dose-response designs. Confirmatory dose response studies may be conducted in Phase II or left for Phase III. Doses used in Phase II are usually but not always less than the highest doses used in Phase I.

Additional objectives of clinical trials conducted in Phase II may include evaluation of potential study endpoints, therapeutic regimens (including concomitant medications) and target populations (e.g. mild versus severe disease) for further study in Phase II or III. These objectives may be served by exploratory analyses, examining subsets of data and by including multiple endpoints in trials.

Types: Phase II studies are sometimes divided into Phase IIA and Phase IIB.

Phase IIA is specifically designed to assess dosing requirements (how much drug should be given).

Phase IIB is specifically designed to study efficacy (how well the drug works at the prescribed dose(s)

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PHASE 3 CLINICAL TRIALS

Phase III Clinical Trials usually are considered to begin with the initiation of studies in which the primary objective is to demonstrate, or confirm therapeutic benefit. These trials are, therefore, most typically of Therapeutic Confirmatory type.

Studies in Phase III are designed to confirm the preliminary evidence accumulated in Phase II that a drug is safe and effective for use in the intended indication and recipient population. These studies are intended to provide an adequate basis for marketing approval.

Phase III studies are randomized controlled multicenter trials on large patient groups (300–3,000 or more depending upon the disease/medical condition studied) and are aimed at being the definitive assessment of how effective the drug is, in comparison with current 'gold standard' treatment. Because of their size and comparatively long duration, Phase III trials are the most expensive, time-consuming and difficult trials to design and run, especially in therapies for chronic medical conditions.

It is common practice that certain Phase III trials will continue while the regulatory submission is pending at the appropriate regulatory agency. This allows patients to continue to receive possibly lifesaving drugs until the drug can be obtained by purchase. Other reasons for performing trials at this stage include attempts by the sponsor at "label expansion" (to show the drug works for additional types of patients/diseases beyond the original use for which the drug was approved for marketing), to obtain additional safety data, or to support marketing claims for the drug. Studies in this phase are by some companies categorised as "Phase IIIB studies.“

Once a drug has proved satisfactory after Phase III trials, the trial results are usually combined into a large document containing a comprehensive description of the methods and results of human and animal studies, manufacturing procedures, formulation details, and shelf life. This collection of information makes up the "regulatory submission" that is provided for review to the appropriate regulatory authorities in different countries. They will review the submission, and, it is hoped, give the sponsor approval to market the drug.

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PHASE 4 CLINICAL TRIALS A Phase IV Clinical trial is also known as Post Marketing Surveillance Trial. Phase IV trials

involve the safety surveillance (Pharmacovigilance) and ongoing technical support of a drug after it receives permission to be sold. Phase IV studies may be required by regulatory authorities or may be undertaken by the sponsoring company for competitive (finding a new market for the drug) or other reasons (for example, the drug may not have been tested for interactions with other drugs, or on certain population groups such as pregnant women, who are unlikely to subject themselves to trials).

Phase IV begins after drug approval and these studies are also known as Therapeutic use studies. Therapeutic use studies go beyond the prior demonstration of the drug’s safety, efficacy and dose definition. They are studies that were not considered necessary for approval but are often important for optimising the drug's use.

The main rationale behind conducting Phase IV trials is :

In prior clinical trials, up to Phase 3, patients are selected and limited in number

Conditions of use in trials differ from those in clinical practice

Duration of trials is limited

Information about rare but serious adverse reactions, chronic toxicity, use in special groups (such as children, the elderly or pregnant women) or drug interactions is often not available.

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CORRELATION BETWEEN DEVELOPMENT PHASES AND TYPES OF STUDY

Therapeutic Use

Therapeutic Confirmatory

Therapeutic Exploratory

Human Pharmacology

TYPE PHASE

Phase I Phase II Phase III Phase IV

TIME

FREQUENTLY DONE

SOMETIMES DONE

PR

OG

RE

SS

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IMPORTANT GUIDELINES ICH AND GCP

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IMPORTANT GUIDELINES – ICH

ICH (International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human use) is a unique undertaking that brings together the drug regulatory authorities and the pharmaceutical industry of Europe, Japan and the United States.

Regulatory harmonisation offers many direct benefits to both regulatory authorities and the pharmaceutical industry with beneficial impact for the protection of public health. Key benefits include:

Preventing duplication of clinical trials in humans and minimising the use of animal testing without compromising safety and effectiveness;

Streamlining the regulatory assessment process for new drug applications;

Reducing the development times and resources for drug development.

This regulatory harmonization is achieved by developing guidelines. These guidelines are divided into four categories as follows:

Q – Quality Guidelines: Defining relevant thresholds for impurities testing and a more flexible approach to pharmaceutical quality based on Good Manufacturing Practice (GMP) risk management.

S – Safety Guidelines: ICH has produced a comprehensive set of safety guidelines to uncover potential risks like carcinogenicity, genotoxicity and reproductive toxicity.

E – Efficacy Guidelines: The work carried out by ICH under the Efficacy heading is concerned with the design, conduct, safety and reporting of clinical trials.

M – Multidisciplinary Guidelines: Those are the cross-cutting topics which do not fit uniquely into one of the Quality, Safety and Efficacy categories. It includes the ICH medical terminology (MedDRA) and the Common Technical Document (CTD)

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EFFICACY GUIDELINES

Clinical Safety E1 – E2F

Clinical Study Reports E3

Dose-Response Studies E4

Ethnic Factors E5

Good Clinical Practice E6

Clinical Trials E7 – E11

Guidelines for Clinical Evaluation by Therapeutic Category E12

Clinical Evaluation E14

Pharmacogenomics E15 – E16

Joint Safety/Efficacy Topic M3

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PRINCIPLES OF GCP (GOOD CLINICAL PRACTICE)

Clinical trials should be conducted in accordance with the ethical principles that have their origin in the Declaration of Helsinki, and that are consistent with GCP and the applicable regulatory requirement(s).

Before a trial is initiated, foreseeable risks and inconveniences should be weighed against the anticipated benefit for the individual trial subject and society. A trial should be initiated and continued only if the anticipated benefits justify the risks.

The rights, safety, and well-being of the trial subjects are the most important considerations and should prevail over interests of science and society.

The available nonclinical and clinical information on an investigational product should be adequate to support the proposed clinical trial.

Clinical trials should be scientifically sound, and described in a clear, detailed protocol.

A trial should be conducted in compliance with the protocol that has received prior institutional review board (IRB)/independent ethics committee (IEC) approval/favourable opinion.

The medical care given to, and medical decisions made on behalf of, subjects should always be the responsibility of a qualified physician or, when appropriate, of a qualified dentist.

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PRINCIPLES OF GCP (CONTD.)

Each individual involved in conducting a trial should be qualified by education, training, and experience to perform his or her respective task(s).

Freely given informed consent should be obtained from every subject prior to clinical trial participation.

All clinical trial information should be recorded, handled, and stored in a way that allows its accurate reporting, interpretation and verification.

The confidentiality of records that could identify subjects should be protected, respecting the privacy and confidentiality rules in accordance with the applicable regulatory requirement(s).

Investigational products should be manufactured, handled, and stored in accordance with applicable good manufacturing practice (GMP). They should be used in accordance with the approved protocol.

Systems with procedures that assure the quality of every aspect of the trial should be implemented.

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DESIGN OF STUDIES BASIC CONSIDERATIONS

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DESIGN – BASIC CONSIDERATIONS

The basic considerations that need to be kept in mind while designing a trial are as follows:

Objective of the Trial: The medical questions that need to be answered should be clearly formulated so that necessary resources such as the number of subjects, study duration, study endpoints for evaluation of the study drug, facility/equipment, and clinical personnel can be determined in order to provide an accurate and reliable statistical/clinical inference for addressing these questions. The objectives may be more than one and may be segregated into primary and secondary as demonstrated by the example of Lung Cancer trial below:

Primary Objectives - This is a randomized, parallel-group trial to demonstrate that the one-year survival of the patients with pre-treated advanced (Stage IIIB/IV) non-small-cell lung cancer (NSCLC) receiving the oral investigational drug is not inferior to those receiving intravenous (IV) docetaxel.

Secondary Objectives - Secondary objectives of the trial are to evaluate overall survival, time to progression, response rate, time to response, improvement in quality of life, and qualitative and quantitative toxicities.

Target population and patient selection: In clinical trials a set of eligibility criteria is usually developed to define the target patient population from which qualified (or eligible) patients can be recruited to enrol the studies. Typically a set of eligibility criteria consists of a set of inclusion criteria and a set of exclusion criteria. The set of inclusion criteria is used to roughly outline the target patient population, while the set of exclusion criteria is used to fine-tune the target patient population by removing the expected sources of variability. To be eligible for the intended study, patients must meet all the inclusion criteria. The next slide shows an example of the eligibility criteria required for a trial involving an anti-infective agent.

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ELIGIBILITY CRITERIA FOR ANTI-INFECTIVE AGENTS

A. Inclusion Criteria

1. Hospitalized patients aged 18 years or older.

2. An oral temperature greater than 38.5°C once or greater than 38°C on two or more occasions during a 12-hour period.

3. Fewer than 500 absolute neutrophils (polymorphonuclear and segmented) per mm3, or patients presenting with between 500 and 1000 absolute neutrophils per mm3, whose counts are anticipated to fall below 500 per mm3 within 48 hours because of antecedent therapy.

B. Exclusion Criteria

1. History of hypersensitivity to a cephalosporin or penicillin.

2. Pregnant or breast-feeding.

3. Requiring other systemic antibacterial drugs concomitantly except for intravenous vancomycin.

4. Creatinine clearance 15 mL/min or requiring hemodialysis or peritoneal dialysis.

5. History of positive antibody test for HIV.

6. A severe underlying disease such as meningitis, osteomyelitis, or endocarditis.

7. Patients undergoing bone marrow transplantation or stem cell harvesting and infusion.

8. Any other condition that in the opinion of the investigator(s) would make the patient unsuitable for enrollment.

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DESIGN – BASIC CONSIDERATIONS (contd.)

SELECTION OF CONTROLS: In clinical trials, bias and variability can occur in many ways depending on the experimental conditions. These bias and variability will have an impact on the accuracy and reliability of statistical and clinical inference of the trials. Uncontrolled (or non-comparative) studies are rarely of value in clinical research, since definitive efficacy data are unobtainable and data on adverse events can be difficult to interpret.

FDA requires that adequate well-controlled clinical trials be conducted to provide an unbiased and valid evaluation of the effectiveness and safety of study medicines. The purpose of a well-controlled study is not only to eliminate bias but also to minimize the variability, and consequently to improve the accuracy and reliability of the statistical and clinical inference of the study.

STATISTICAL CONSIDERATIONS: At the planning stage some statistical considerations regarding the manner in which the data will be tabulated and analyzed at the end of the study should be carefully considered. These considerations include the primary and secondary response variables, the criteria for efficacy and safety assessment, sample size estimation, possible interim analysis and data monitoring, and statistical and clinical inference.

OTHER CONSIDERATIONS: In addition to these considerations, some other issues are dependent on individual trials e.g. treatment duration, patient compliance, missing value, and drop outs.

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DIFFERENT DESIGNS OF TRIALS Parallel Group Design: A parallel group design is a complete randomized design in which each patient

receives one and only one treatment in a random fashion. Basically there are two types of parallel group design for comparative clinical trials, namely, group comparison (or parallel-group) designs and matched pairs parallel designs. The simplest group comparison parallel group design is the two-group parallel design which compares two treatments (e.g., a treatment group vs. a control group). Each treatment group usually, but not necessarily, contains approximately the same number of patients.

Run-in Periods

Before patients enter a clinical trial, a run-in (or lead-in) period of placebo, no active treatment, dietary control, or active maintenance therapy (e.g., diuretic and/or digoxin in heart failure studies) is usually employed prior to randomization. The inclusion of a run-in period prior to the active treatment has the following advantages:

1. It acts as a washout period to remove effects of previous therapy.

2. It can be used to obtain baseline data and to evaluate if patient fulfils study entry criteria.

3. It can be used as a training period for patients, investigators, and their staff.

4. It helps in identifying placebo responders.

5. It provides useful information regarding patient compliance.

6. It can be used to estimate and compare the magnitude of possible placebo effects between groups.

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RU

N IN

RA

ND

OM

IZA

TIO

N

CONTROL A

CONTROL B

TEST

PATIENTS

DIFFERENT DESIGNS OF TRIALS - CONTD

Crossover Design: In the crossover design, each subject is randomised to a sequence of two or more treatments, and hence acts as his own control for treatment comparisons. This simple manoeuvre is attractive primarily because it reduces the number of subjects and usually the number of assessments needed to achieve a specific power, sometimes to a marked extent. In the simplest 2×2 crossover design each subject receives each of two treatments in randomised order in two successive treatment periods, often separated by a washout period. The most common extension of this entails comparing n(>2) treatments in n periods, each subject receiving all n treatments. Numerous variations exist, such as designs in which each subject receives a subset of n(>2) treatments, or ones in which treatments are repeated within a subject.

I II

STANDARD TWO-SEQUENCE, TWO-PERIOD CROSSOVER DESIGN

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PATIENTS

RA

ND

OM

IZA

TIO

N

WA

SH

OU

T

PERIOD

TEST

CONTROL TEST

CONTROL SEQUENCE A

SEQUENCE B

DIFFERENT DESIGNS OF TRIALS - CONTD

TITRATION DESIGNS

For phase I safety and tolerance studies, Rodda et al. (1988) classify traditional designs as follows:

1. Rising single-dose design.

2. Rising single-dose crossover design.

3. Alternative-panel rising single-dose design.

4. Alternative-panel rising single-dose crossover design.

5. Parallel-panel rising multiple-dose design.

6. Alternative-panel rising multiple-dose design.

FACTORIAL DESIGNS:

In a factorial design two or more treatments are evaluated simultaneously through the use of varying combinations of the treatments. The simplest example is the 2×2 factorial design in which subjects are randomly allocated to one of the four possible combinations of two treatments, A and B say. These are: A alone; B alone; both A and B; neither A nor B. In many cases this design is used for the specific purpose of examining the interaction of A and B. The statistical test of interaction may lack power to detect an interaction if the sample size was calculated based on the test for main effects. This consideration is important when this design is used for examining the joint effects of A and B, in particular, if the treatments are likely to be used together.

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RANDOMIZATION AND

BLINDING

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RANDOMIZATION

Randomization is a process in which the study subjects, after assessment of eligibility and recruitment, but before the intervention to be studied begins, are randomly allocated to receive one or other of the alternative treatments under study.

Some ethical considerations may arise as some subjects receive the treatment under study while the remaining receive the standard treatment or the placebo. But it is to be noted that before the study data is analyzed, no one knows whether the treatment under investigation is more effective than the standard treatment or less effective compared to the placebo, as the case may be for the individual trial under consideration.

The benefits of randomization are as follows:

It eliminates selection bias .

It eliminates confounding by adjusting for co-variates.

It facilitates blinding of the identity of treatments from investigators, participants, and assessors.

It permits the use of probability theory to express the likelihood that any difference in outcome between treatment groups merely indicates chance.

Different randomization procedures are there like simple randomization, restricted randomization and adaptive randomization.

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CONSORT 2010 FLOW DIAGRAM

38

Enrollment

Allocation

Assessment for eligibility

Excluded

Randomization

Allocated to Intervention Allocated to Intervention

TEST CONTROL

Analyzed

Followed Up

Received Intervention

Analyzed

Followed Up

Received Intervention

Follow-Up

Analysis

Not Analyzed Not Analyzed

Lost to Follow up

Did not receive Did not receive

Lost to Follow up

CONSORT - Consolidated Standards of Reporting Trials

BLINDING / MASKING

Blinding is defined as an experimental condition in which various groups of the individuals involved with the trial are withheld from the knowledge of the treatments assigned to patients and corresponding relevant information. The blinding is also known as masking by some research organizations such as NIH.

The purpose of blinding is to eliminate bias in subjective judgment due to knowledge of the treatment. Although the concept of randomization is to prevent bias from a statistically sound assessment of the study drug, it does not guarantee that there will be no bias caused by subjective judgment in reporting, evaluation, data processing, and statistical analysis due to the knowledge of the identity of the treatments. Since this subjective and judgmental bias is directly or indirectly related to treatment, it can seriously distort statistical inference on the treatment effect. it is therefore imperative to eliminate such bias by blocking the identity of treatments.

Blinding in clinical trials can be classified into four types: open label, single blind, double blind, and triple blind.

An open-label study is a clinical trial in which no blinding is employed.

A single-blind trial is a trial in which only the patient is unaware of his or her treatment assignment.

A double-blind trial is a trial in which neither the patients nor the investigator (study centre) are aware of patient’s treatment assignment.

In addition to the patient’s treatment assignment, the blindness also applies to concealment of the overall results of the trial.

A triple-blind study with respect to blindness can provide the highest degree for the validity of a controlled clinical trial.

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DATA MANAGEMENT ESSENTIALS

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CLINICAL DATA MANAGEMENT - OVERVIEW

CDM (Clinical Data Management) is an integral part of the clinical trial process, which ensures the validity, quality, and integrity of data collected from trial subjects to a database system. CDM delivers a clean and high-quality database for statistical analysis and consequently enables clinical scientists to draw conclusions regarding the effectiveness, safety, and clinical benefit / risk of the drug product under investigation.

The CDM process includes:

Case Report Form (CRF) development

Database development and validation

Data entry, query, and correction

Data quality assurance

Data lock, archive, and transfer.

The CDM process may encounter the following obstacles during the trial:

CDM process may fails to collect useful information for addressing the scientific/clinical questions that the clinical trial intends to answer

CDM process may collect information that is irrelevant to the study objectives of the clinical trials

The quality of the collected data may be poor with missing values and/or inconsistencies across case report forms and/or study sites

To overcome these obstacles, the implementation of good data management practice (GDMP) is necessary. GDMP is a set of standards/procedures for assurance of the validity, quality, and integrity of clinical data collected from trial subjects to a database system. GDMP takes guidance from the ICH-GCP and 21 CFR regulations.

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DEVELOPMENT OF CASE REPORT FORMS

The CDM process begins with the development of case report form (CRF), which takes place at an early stage of protocol development. The CRF should be designed to capture correct information in an effective way. The CRF process includes procedures for handling CRFs and CRF flow and tracking, which is an important factor for the success of the CDM process. The individual protocol will have its own custom made CRF to suit the requirements, but the basic principles are the same.

Madison and Plaunt (2003) recommended that the following principles be considered when designing CRFs for an intended clinical trial:

The CRF should be designed to capture all data required per the study protocol,

The CRF should be designed to collect data elements in standardized format,

Data elements should be captured on the CRF in a fashion that ensures that data are suitable for summarization and analysis,

Data elements planned to be transcribed to the CRF from source documents should be organized and formatted on the CRF to reduce the possibility of transcription error and to facilitate subsequent comparison to source documents,

Ease of completion for the investigator and study coordinator is key to accurate and timely CRF completion,

Redundant data elements within the CRF should be avoided and unnecessary data should not be collected.

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SAMPLE CRF TEMPLATE The CRF form for any study protocol contains several standard sections which correspond to the

different modules of an Electronic Data Capture or Remote Data Capture software. The different sections are as follows:

1. Identifier (Must be included on every page): It includes subject identifier, study identifier, visit type, visit date, investigator signature and date.

2. Subject Enrollment Form (contains demographic data): Date of birth, Gender, Race, Weight and Height, Subject number, date of informed consent signed, date subject started the study.

3. Eligibility Form: Inclusion criteria list – all answers must be YES, Exclusion criteria list – all answers must be NO

4. Subject Randomization Form: Date subject randomized, Subject randomization code

5. Medical History: Medical history of the subject that is relevant to the protocol

6. Physical Examination: Vital signs, and different body systems

7. Clinical Laboratory Data : Those defined by the study protocol

8. Compliance: Pill count at each protocol interval

9. Concomitant medications: All the subjects’ medications taken during the study at each protocol interval

10. Adverse Events: All adverse events during the study including any run-in and follow-up periods

11. Off Study Form: Document subject completion, removal from or drop-out from the study

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DATABASE DEVELOPMENT

As indicated by Grobler et al. (2001), a database should be designed to facilitate data entry and the extraction of data for analysis. Database development includes database design (or setup) and database edit check specifications. In practice, for a given clinical trial, to facilitate data entry and the extraction of data for analysis, a protocol-specific database is set up using standard templates (e.g., modules and format libraries or data dictionaries) where available.

The use of standard templates enhances the efficiency of the database development process and facilitates subsequent aggregation of the data. Once the applicable standard templates are identified, the protocol-specific database can be built by creating the following associated structures of

(1) Data entry screens, which are identical to CRFs;

(2) Test data;

(3) Derived variables;

(4) Data validation routines; and

(5) Audit trail.

For a given clinical study, in some cases, it is not uncommon to have more than one database due to planned interim analyses and/or pharmacokinetic/pharmacodynamic analyses. In practice, a data validation plan is usually developed during the database development process to ensure the validity, quality, and integrity of the data captured from subjects in the clinical trial. Audit trails are required to document any changes that have incurred during the database development process.

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CLINICAL RESEARCH DATA STANDARDS - CDISC

Despite the similarity of data collected for clinical research and patient care, communication between these two classes of systems has remained hindered for a number of reasons. These include slow adoption of technology, a lack of sophistication in some software applications, and integration priorities on the patient care side in which research is often, at best, a secondary consideration. Most significantly, communication is hindered because systems use different standards—most commonly in the United States variations of HL7 version 2 for patient care and CDISC for research—or no standards at all. As a result, data entered in one system cannot be re-used by the other, resulting in substantial amounts of work duplication.

CDISC (Clinical Data Interchange Standards Consortium) is a global, open, multidisciplinary, non-profit organization that has established standards to support the acquisition, exchange, submission and archive of clinical research data and metadata. CDISC standards are vendor-neutral, platform-independent and freely available via the CDISC website.

Study Data Tabulation Model: SDTM is the model developed by the CDISC and it provides a general framework for describing the organization of information collected during human and animal studies.

SDTM Version 3.1.2. is recognized by FDA as a mechanism for the analysis of study data.

The model is built around the concept of observations, which consist of discrete pieces of information collected during a study. Observations normally correspond to rows in a dataset.

These observations are classified as Interventions, Findings, and Events

Each observation can be described by a series of named variables. Each variable, which normally corresponds to a column in a dataset, can be classified according to its Role.

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ANALYSIS OFSTUDYDATA

AN OVERVIEW

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IMPORTANT CONSIDERATIONS When designing a clinical trial the principal features of the eventual statistical analysis of the data

should be described in the statistical section of the protocol. This section should include all the principal features of the proposed confirmatory analysis of the primary variable(s) and the way in which anticipated analysis problems will be handled.

The important considerations for Analysis of the study data are as follows:

Analysis sets: If all subjects randomised into a clinical trial satisfied all entry criteria, followed all trial procedures perfectly with no losses to follow-up, and provided complete data records, then the set of subjects to be included in the analysis would be self-evident. The design and conduct of a trial should aim to approach this ideal as closely as possible, but, in practice, it is doubtful if it can ever be fully achieved. Hence, the statistical section of the protocol should address anticipated problems prospectively in terms of how these affect the subjects and data to be analysed.

Missing Values and Outliers: Missing values represent a potential source of bias in a clinical trial. Hence, every effort should be undertaken to fulfil all the requirements of the protocol concerning the collection and management of data. In reality, however, there will almost always be some missing data. A trial may be regarded as valid, nonetheless, provided the methods of dealing with missing values are sensible, and particularly if those methods are pre-defined in the protocol.

Data Transformation: The decision to transform key variables prior to analysis is best made during the design of the trial on the basis of similar data from earlier clinical trials. Transformations (e.g. square root, logarithm) should be specified in the protocol and a rationale provided, especially for the primary variable(s).

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IMPORTANT CONSIDERATIONS – CONTD. Estimation, Confidence Intervals and Hypothesis Testing: The statistical section of the protocol should specify

the hypotheses that are to be tested and/or the treatment effects which are to be estimated in order to satisfy the primary objectives of the trial. The statistical methods to be used to accomplish these tasks should be described for the primary (and preferably the secondary) variables, and the underlying statistical model should be made clear. Estimates of treatment effects should be accompanied by confidence intervals, whenever possible, and the way in which these will be calculated should be identified.

Adjustment of Significance and Confidence Levels: When multiplicity is present, the usual approach to the analysis of clinical trial data may necessitate an adjustment to the type I error. Multiplicity may arise, for example, from multiple primary variables, multiple comparisons of treatments, repeated evaluation over time and/or interim analyses. Methods to avoid or reduce multiplicity are sometimes preferable when available, such as the identification of the key primary variable (multiple variables), the choice of a critical treatment contrast (multiple comparisons), the use of a summary measure such as ‘area under the curve’ (repeated measures).

Subgroups, Interactions and Covariates: The primary variable(s) is often systematically related to other influences apart from treatment. For example, there may be relationships to covariates such as age and sex, or there may be differences between specific subgroups of subjects such as those treated at the different centres of a multicentre trial. The treatment effect itself may also vary with subgroup or covariate - for example, the effect may decrease with age or may be larger in a particular diagnostic category of subjects. Pre-trial deliberations should identify those covariates and factors expected to have an important influence on the primary variable(s), and should consider how to account for these in the analysis in order to improve precision and to compensate for any lack of balance between treatment groups.

Integrity of Data and Computer Software Validity: The credibility of the numerical results of the analysis depends on the quality and validity of the methods and software (both internally and externally written) used both for data management (data entry, storage, verification, correction and retrieval) and also for processing the data statistically. Data management activities should therefore be based on thorough and effective standard operating procedures.

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STUDY DATA ANALYSIS – METHODS

Graphical Data Analysis: The technical basis of graphical data analysis is simultaneous display of both magnitudes and frequencies of individual data values in order to characterize data distribution. Cross display of multiple graphs by the factors under comparison affords excellent visual contrast for comparison of data distributions. Bar charts are the graph of choice for categorical data. For continuous data, several graphical techniques are available For continuous data, several graphical techniques are available. Picket fence plot and histogram are the graph of choice for direct display of frequencies, box plots show main body and outliers, and cumulative or symmetric cumulative frequency plots are good for comparing multiple distributions on a single graph.

Data Analysis with Summary Measures: Cross tabulation and display of summary measures by the factors under study expedite comparison. Bar charts are good for showing magnitudes, and line-scatter plots are good for showing trends. Commonly used summary measures are the number of observations, mean, median, standard deviation, average deviation, and standard error.

Analysis of Variance (ANOVA): The analysis of variance summarizes data with the mean, and the quality of summarization is measured with the standard error. The major use is simultaneous evaluation of multiple interrelated factors. The basic operation is grouping and curve fitting. When multiple factors are evaluated simultaneously, any specific effect may be quantified with up to three types of measures, depending upon the relationship among the factors.

Nonparametric Analysis: The word, nonparametric, really means no involvement of mathematical distributions. The most commonly performed “nonparametric” analyses are essentially the traditional analysis of variance on transformed data, although, in theory, permutation test, instead of the standard normal distribution or its equivalence, should be used to obtain the p-value for a nonparametric test. Examples of nonparametric analysis are the Wilcoxon, Mann-Whitney, and Kruskal-Wallis tests on ranks.

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ANALYSIS METHODS (CONTD.)

Survival Analysis: The constant flow of time makes survival observations from patients lost in follow-up meaningful. Comparisons of survival time values themselves are not quite meaningful when a considerable number of observations are from the patients lost in follow-up. An appropriate measure for summarizing survival observations is time-specific death or survival rate, which is the ratio of deaths or lives at a specific time point over the number of patients at risk of death. Comparisons of survival information may be made with life tables or Kaplan-Meier plots.

Statistical Sampling and Estimation: Sometimes the size of the entire population to be studied is so large that measuring a particular parameter (say population mean SBP) becomes to time consuming and costly. To deal with this problem researchers can draw a sample of the population at random and then calculate the mean SBP of that population. This parameter becomes an estimate of the population parameter that needs to be measured. The problem for a decision maker is to decide on the basis of the sample data the estimated value of a parameter, such as the population mean, as well as to provide certain ideas concerning errors associated with that estimate.

Statistical Tests of Significance: Tests of significance try to find out whether there is a real relation between two events or the relation appears by chance only. One of the most widely used statistical test of significance is Hypothesis Testing. When a health investigator seeks to understand or explain something, for example the effect of a toxin or a drug, he or she usually formulates his or her research question in the form of a statistical hypothesis or assumption. The hypothesis to be tested is known as the null hypothesis. The sample statistics are analysed and if the results are not consistent with the hypothesis, the null hypothesis is rejected in favour of an alternative hypothesis. The two hypothesis are always constructed in a way that they are mutually exclusive, i.e., when one is true the other must be false.

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