Even very young children perform rudimentary experiments to learn about the world and how things work.
An experiment is a procedure carried out to support or refute a hypothesis, or determine the efficacy or likelihood of something previously untried. Experiments provide insight into cause-and-effect
by demonstrating what outcome occurs when a particular factor is
manipulated. Experiments vary greatly in goal and scale but always rely
on repeatable procedure and logical analysis of the results. There also
exist natural experimental studies.
A child may carry out basic experiments to understand how things
fall to the ground, while teams of scientists may take years of
systematic investigation to advance their understanding of a phenomenon.
Experiments and other types of hands-on activities are very important
to student learning in the science classroom. Experiments can raise test
scores and help a student become more engaged and interested in the
material they are learning, especially when used over time. Experiments can vary from personal and informal natural comparisons
(e.g. tasting a range of chocolates to find a favorite), to highly
controlled (e.g. tests requiring complex apparatus overseen by many
scientists that hope to discover information about subatomic particles).
Uses of experiments vary considerably between the natural and human sciences.
Experiments typically include controls, which are designed to minimize the effects of variables other than the single independent variable. This increases the reliability of the results, often through a comparison between control measurements and the other measurements. Scientific controls are a part of the scientific method. Ideally, all variables
in an experiment are controlled (accounted for by the control
measurements) and none are uncontrolled. In such an experiment, if all
controls work as expected, it is possible to conclude that the
experiment works as intended, and that results are due to the effect of
the tested variables.
Overview
In the scientific method, an experiment is an empirical procedure that arbitrates competing models or hypotheses. Researchers also use experimentation to test existing theories or new hypotheses to support or disprove them.
An experiment usually tests a hypothesis,
which is an expectation about how a particular process or phenomenon
works. However, an experiment may also aim to answer a "what-if"
question, without a specific expectation about what the experiment
reveals, or to confirm prior results. If an experiment is carefully
conducted, the results usually either support or disprove the
hypothesis. According to some philosophies of science, an experiment can never "prove" a hypothesis, it can only add support. On the other hand, an experiment that provides a counterexample can disprove a theory or hypothesis, but a theory can always be salvaged by appropriate ad hoc modifications at the expense of simplicity.
In engineering and the physical sciences,
experiments are a primary component of the scientific method. They are
used to test theories and hypotheses about how physical processes work
under particular conditions (e.g., whether a particular engineering
process can produce a desired chemical compound). Typically, experiments
in these fields focus on replication of identical procedures in hopes of producing identical results in each replication. Random assignment is uncommon.
In medicine and the social sciences,
the prevalence of experimental research varies widely across
disciplines. When used, however, experiments typically follow the form
of the clinical trial,
where experimental units (usually individual human beings) are randomly
assigned to a treatment or control condition where one or more outcomes
are assessed. In contrast to norms in the physical sciences, the focus is typically on the average treatment effect (the difference in outcomes between the treatment and control groups) or another test statistic produced by the experiment. A single study typically does not involve replications of the experiment, but separate studies may be aggregated through systematic review and meta-analysis.
There are various differences in experimental practice in each of the branches of science. For example, agricultural research frequently uses randomized experiments (e.g., to test the comparative effectiveness of different fertilizers), while experimental economics
often involves experimental tests of theorized human behaviors without
relying on random assignment of individuals to treatment and control
conditions.
One of the first methodical approaches to experiments in the modern
sense is visible in the works of the Arab mathematician and scholar Ibn al-Haytham. He conducted his experiments in the field of optics—going back to optical and mathematical problems in the works of Ptolemy—by
controlling his experiments due to factors such as self-criticality,
reliance on visible results of the experiments as well as a criticality
in terms of earlier results. He was one of the first scholars to use an
inductive-experimental method for achieving results. In his Book of Optics he describes the fundamentally new approach to knowledge and research in an experimental sense:
We should, that is, recommence the
inquiry into its principles and premisses, beginning our investigation
with an inspection of the things that exist and a survey of the
conditions of visible objects. We should distinguish the properties of
particulars, and gather by induction what pertains to the eye when
vision takes place and what is found in the manner of sensation to be
uniform, unchanging, manifest and not subject to doubt. After which we
should ascend in our inquiry and reasonings, gradually and orderly,
criticizing premisses and exercising caution in regard to
conclusions—our aim in all that we make subject to inspection and review
being to employ justice, not to follow prejudice, and to take care in
all that we judge and criticize that we seek the truth and not to be
swayed by opinion. We may in this way eventually come to the truth that
gratifies the heart and gradually and carefully reach the end at which
certainty appears; while through criticism and caution we may seize the
truth that dispels disagreement and resolves doubtful matters. For all
that, we are not free from that human turbidity which is in the nature
of man; but we must do our best with what we possess of human power.
From God we derive support in all things.
According to his explanation, a strictly controlled test execution
with a sensibility for the subjectivity and susceptibility of outcomes
due to the nature of man is necessary. Furthermore, a critical view on
the results and outcomes of earlier scholars is necessary:
It is thus the duty of the man who
studies the writings of scientists, if learning the truth is his goal,
to make himself an enemy of all that he reads, and, applying his mind to
the core and margins of its content, attack it from every side. He
should also suspect himself as he performs his critical examination of
it, so that he may avoid falling into either prejudice or leniency.
Thus, a comparison of earlier results with the experimental results
is necessary for an objective experiment—the visible results being more
important. In the end, this may mean that an experimental researcher
must find enough courage to discard traditional opinions or results,
especially if these results are not experimental but results from a
logical/ mental derivation. In this process of critical consideration,
the man himself should not forget that he tends to subjective
opinions—through "prejudices" and "leniency"—and thus has to be critical
about his own way of building hypotheses.
Francis Bacon (1561–1626), an English philosopher and scientist active in the 17th century, became an influential supporter of experimental science in the English renaissance. He disagreed with the method of answering scientific questions by deduction—similar to Ibn al-Haytham—and
described it as follows: "Having first determined the question
according to his will, man then resorts to experience, and bending her
to conformity with his placets, leads her about like a captive in a
procession." Bacon wanted a method that relied on repeatable observations, or
experiments. Notably, he first ordered the scientific method as we
understand it today.
There
remains simple experience; which, if taken as it comes, is called
accident, if sought for, experiment. The true method of experience first
lights the candle [hypothesis], and then by means of the candle shows
the way [arranges and delimits the experiment]; commencing as it does
with experience duly ordered and digested, not bungling or erratic, and
from it deducing axioms [theories], and from established axioms again
new experiments.
In the centuries that followed, people who applied the scientific
method in different areas made important advances and discoveries. For
example, Galileo Galilei
(1564–1642) accurately measured time and experimented to make accurate
measurements and conclusions about the speed of a falling body. Antoine Lavoisier (1743–1794), a French chemist, used experiment to describe new areas, such as combustion and biochemistry and to develop the theory of conservation of mass (matter). Louis Pasteur (1822–1895) used the scientific method to disprove the prevailing theory of spontaneous generation and to develop the germ theory of disease. Because of the importance of controlling potentially confounding variables, the use of well-designed laboratory experiments is preferred when possible.
A considerable amount of progress on the design and analysis of
experiments occurred in the early 20th century, with contributions from
statisticians such as Ronald Fisher (1890–1962), Jerzy Neyman (1894–1981), Oscar Kempthorne (1919–2000), Gertrude Mary Cox (1900–1978), and William Gemmell Cochran (1909–1980), among others.
Types
Experiments
might be categorized according to a number of dimensions, depending
upon professional norms and standards in different fields of study.
In some disciplines (e.g., psychology or political science), a 'true experiment' is a method of social research in which there are two kinds of variables. The independent variable is manipulated by the experimenter, and the dependent variable is measured. The signifying characteristic of a true experiment is that it randomly allocates the subjects to neutralize experimenter bias, and ensures, over a large number of iterations of the experiment, that it controls for all confounding factors.
Depending on the discipline, experiments can be conducted to accomplish different but not mutually exclusive goals: test theories, search for and document phenomena, develop theories, or
advise policymakers. These goals also relate differently to validity concerns.
A controlled experiment often compares the results obtained from experimental samples against control
samples, which are practically identical to the experimental sample
except for the one aspect whose effect is being tested (the independent variable). A good example would be a drug trial. The sample or group receiving the drug would be the experimental group (treatment group); and the one receiving the placebo or regular treatment would be the control one. In many laboratory experiments it is good practice to have several replicate samples for the test being performed and have both a positive control and a negative control.
The results from replicate samples can often be averaged, or if one of
the replicates is obviously inconsistent with the results from the other
samples, it can be discarded as being the result of an experimental
error (some step of the test procedure may have been mistakenly omitted
for that sample). Most often, tests are done in duplicate or triplicate.
A positive control is a procedure similar to the actual experimental
test but is known from previous experience to give a positive result. A
negative control is known to give a negative result. The positive
control confirms that the basic conditions of the experiment were able
to produce a positive result, even if none of the actual experimental
samples produce a positive result. The negative control demonstrates the
base-line result obtained when a test does not produce a measurable
positive result. Most often the value of the negative control is treated
as a "background" value to subtract from the test sample results.
Sometimes the positive control takes the quadrant of a standard curve.
An example that is often used in teaching laboratories is a controlled proteinassay.
Students might be given a fluid sample containing an unknown (to the
student) amount of protein. It is their job to correctly perform a
controlled experiment in which they determine the concentration of
protein in the fluid sample (usually called the "unknown sample"). The
teaching lab would be equipped with a protein standard solution
with a known protein concentration. Students could make several
positive control samples containing various dilutions of the protein
standard. Negative control samples would contain all of the reagents for
the protein assay but no protein. In this example, all samples are
performed in duplicate. The assay is a colorimetric assay in which a spectrophotometer
can measure the amount of protein in samples by detecting a colored
complex formed by the interaction of protein molecules and molecules of
an added dye. In the illustration, the results for the diluted test
samples can be compared to the results of the standard curve (the blue
line in the illustration) to estimate the amount of protein in the
unknown sample.
Controlled experiments can be performed when it is difficult to
exactly control all the conditions in an experiment. In this case, the
experiment begins by creating two or more sample groups that are
probabilistically equivalent, which means that measurements of traits
should be similar among the groups and that the groups should respond in
the same manner if given the same treatment. This equivalency is
determined by statistical methods that take into account the amount of variation between individuals and the number of individuals in each group. In fields such as microbiology and chemistry,
where there is very little variation between individuals and the group
size is easily in the millions, these statistical methods are often
bypassed and simply splitting a solution into equal parts is assumed to
produce identical sample groups.
Once equivalent groups have been formed, the experimenter tries to treat them identically except for the one variable that he or she wishes to isolate. Human experimentation requires special safeguards against outside variables such as the placebo effect. Such experiments are generally double blind,
meaning that neither the volunteer nor the researcher knows which
individuals are in the control group or the experimental group until
after all of the data have been collected. This ensures that any effects
on the volunteer are due to the treatment itself and are not a response
to the knowledge that he is being treated.
In human experiments, researchers may give a subject (person) a stimulus that the subject responds to. The goal of the experiment is to measure the response to the stimulus by a test method.
In the design of experiments, two or more "treatments" are applied to estimate the difference between the mean responses
for the treatments. For example, an experiment on baking bread could
estimate the difference in the responses associated with quantitative
variables, such as the ratio of water to flour, and with qualitative
variables, such as strains of yeast. Experimentation is the step in the scientific method that helps people decide between two or more competing explanations—or hypotheses.
These hypotheses suggest reasons to explain a phenomenon or predict the
results of an action. An example might be the hypothesis that "if I
release this ball, it will fall to the floor": this suggestion can then
be tested by carrying out the experiment of letting go of the ball, and
observing the results. Formally, a hypothesis is compared against its
opposite or null hypothesis
("if I release this ball, it will not fall to the floor"). The null
hypothesis is that there is no explanation or predictive power of the
phenomenon through the reasoning that is being investigated. Once
hypotheses are defined, an experiment can be carried out and the results
analysed to confirm, refute, or define the accuracy of the hypotheses.
The term "experiment" usually implies a controlled experiment, but
sometimes controlled experiments are prohibitively difficult,
impossible, unethical or illegal. In this case researchers resort to
natural experiments or quasi-experiments. Natural experiments rely solely on observations of the variables of the system
under study, rather than manipulation of just one or a few variables as
occurs in controlled experiments. To the degree possible, they attempt
to collect data for the system in such a way that contribution from all
variables can be determined, and where the effects of variation in
certain variables remain approximately constant so that the effects of
other variables can be discerned. The degree to which this is possible
depends on the observed correlation between explanatory variables in the observed data. When these variables are not
well correlated, natural experiments can approach the power of
controlled experiments. Usually, however, there is some correlation
between these variables, which reduces the reliability of natural
experiments relative to what could be concluded if a controlled
experiment were performed. Also, because natural experiments usually
take place in uncontrolled environments, variables from undetected
sources are neither measured nor held constant, and these may produce
illusory correlations in variables under study.
Much research in several science disciplines, including economics, human geography, archaeology, sociology, cultural anthropology, geology, paleontology, ecology, meteorology, and astronomy,
relies on quasi-experiments. For example, in astronomy it is clearly
impossible, when testing the hypothesis "Stars are collapsed clouds of
hydrogen", to start out with a giant cloud of hydrogen, and then perform
the experiment of waiting a few billion years for it to form a star.
However, by observing various clouds of hydrogen in various states of
collapse, and other implications of the hypothesis (for example, the
presence of various spectral emissions from the light of stars), we can
collect data we require to support the hypothesis. An early example of
this type of experiment was the first verification in the 17th century
that light does not travel from place to place instantaneously, but
instead has a measurable speed. Observation of the appearance of the
moons of Jupiter were slightly delayed when Jupiter was farther from
Earth, as opposed to when Jupiter was closer to Earth; and this
phenomenon was used to demonstrate that the difference in the time of
appearance of the moons was consistent with a measurable speed.
Field experiments are so named to distinguish them from laboratory
experiments, which enforce scientific control by testing a hypothesis
in the artificial and highly controlled setting of a laboratory. Often
used in the social sciences, and especially in economic analyses of
education and health interventions, field experiments have the advantage
that outcomes are observed in a natural setting rather than in a
contrived laboratory environment. For this reason, field experiments are
sometimes seen as having higher external validity
than laboratory experiments. However, like natural experiments, field
experiments suffer from the possibility of contamination: experimental
conditions can be controlled with more precision and certainty in the
lab. Yet some phenomena (e.g., voter turnout in an election) cannot be
easily studied in a laboratory.
Observational studies
The black box model for observation (input and output are observables). When there are a feedback with some observer's control, as illustrated, the observation is also an experiment.
An observational study
is used when it is impractical, unethical, cost-prohibitive (or
otherwise inefficient) to fit a physical or social system into a
laboratory setting, to completely control confounding factors, or to
apply random assignment. It can also be used when confounding factors
are either limited or known well enough to analyze the data in light of
them (though this may be rare when social phenomena are under
examination). For an observational science to be valid, the experimenter
must know and account for confounding
factors. In these situations, observational studies have value because
they often suggest hypotheses that can be tested with randomized
experiments or by collecting fresh data.
Fundamentally, however, observational studies are not
experiments. By definition, observational studies lack the manipulation
required for Baconian experiments.
In addition, observational studies (e.g., in biological or social
systems) often involve variables that are difficult to quantify or
control. Observational studies are limited because they lack the
statistical properties of randomized experiments. In a randomized
experiment, the method of randomization specified in the experimental
protocol guides the statistical analysis, which is usually specified
also by the experimental protocol. Without a statistical model that reflects an objective randomization, the statistical analysis relies on a subjective model. Inferences from subjective models are unreliable in theory and practice. In fact, there are several cases where carefully conducted
observational studies consistently give wrong results, that is, where
the results of the observational studies are inconsistent and also
differ from the results of experiments. For example, epidemiological
studies of colon cancer consistently show beneficial correlations with
broccoli consumption, while experiments find no benefit.
A particular problem with observational studies involving human
subjects is the great difficulty attaining fair comparisons between
treatments (or exposures), because such studies are prone to selection bias,
and groups receiving different treatments (exposures) may differ
greatly according to their covariates (age, height, weight, medications,
exercise, nutritional status, ethnicity, family medical history, etc.).
In contrast, randomization implies that for each covariate, the mean
for each group is expected to be the same. For any randomized trial,
some variation from the mean is expected, of course, but the
randomization ensures that the experimental groups have mean values that
are close, due to the central limit theorem and Markov's inequality.
With inadequate randomization or low sample size, the systematic
variation in covariates between the treatment groups (or exposure
groups) makes it difficult to separate the effect of the treatment
(exposure) from the effects of the other covariates, most of which have
not been measured. The mathematical models used to analyze such data
must consider each differing covariate (if measured), and results are
not meaningful if a covariate is neither randomized nor included in the
model.
To avoid conditions that render an experiment far less useful, physicians conducting medical trials—say for U.S. Food and Drug Administration
approval—quantify and randomize the covariates that can be identified.
Researchers attempt to reduce the biases of observational studies with matching methods such as propensity score matching,
which require large populations of subjects and extensive information
on covariates. However, propensity score matching is no longer
recommended as a technique because it can increase, rather than
decrease, bias. Outcomes are also quantified when possible (bone density, the amount of
some cell or substance in the blood, physical strength or endurance,
etc.) and not based on a subject's or a professional observer's opinion.
In this way, the design of an observational study can render the
results more objective and therefore, more convincing.
By placing the distribution of the independent variable(s) under the
control of the researcher, an experiment—particularly when it involves human subjects—introduces
potential ethical considerations, such as balancing benefit and harm,
fairly distributing interventions (e.g., treatments for a disease), and informed consent.
For example, in psychology or health care, it is unethical to provide a
substandard treatment to patients. Therefore, ethical review boards are
supposed to stop clinical trials and other experiments unless a new
treatment is believed to offer benefits as good as current best
practice. It is also generally unethical (and often illegal) to conduct
randomized experiments on the effects of substandard or harmful
treatments, such as the effects of ingesting arsenic on human health. To
understand the effects of such exposures, scientists sometimes use
observational studies to understand the effects of those factors.
Even when experimental research does not directly involve human
subjects, it may still present ethical concerns. For example, the
nuclear bomb experiments conducted by the Manhattan Project
implied the use of nuclear reactions to harm human beings even though
the experiments did not directly involve any human subjects.
A clinical trial participant receives an injection.
Clinical trials are prospective biomedical or behavioral research studies on human participants designed to answer specific questions about biomedical or behavioral interventions, including new treatments (such as novel vaccines, drugs, dietary choices, dietary supplements, and medical devices)
and known interventions that warrant further study and comparison.
Clinical trials generate data on dosage, safety and efficacy. They are conducted only after they have received health authority/ethics committee approval in the country where approval of the therapy is sought. These authorities are responsible for vetting the risk/benefit ratio of the trial—their approval does not mean the therapy is 'safe' or effective, only that the trial may be conducted.
Depending on product type and development stage, investigators initially enroll volunteers or patients into small pilot studies,
and subsequently conduct progressively larger scale comparative
studies. Clinical trials can vary in size and cost, and they can involve
a single research center or multiple centers, in one country or in multiple countries. Clinical study design aims to ensure the scientific validity and reproducibility of the results.
Costs for clinical trials can range into the billions of dollars per approved drug, and the complete trial process to approval may require 7–15 years. The sponsor may be a governmental organization or a pharmaceutical, biotechnology
or medical-device company. Certain functions necessary to the trial,
such as monitoring and lab work, may be managed by an outsourced
partner, such as a contract research organization or a central laboratory. Only 10 percent of all drugs started in human clinical trials become approved drugs.
Overview
Trials of drugs
Some clinical trials involve healthy subjects with no pre-existing medical conditions.
Other clinical trials pertain to people with specific health conditions
who are willing to try an experimental treatment. Pilot experiments are
conducted to gain insights for design of the clinical trial to follow.
There are two goals to testing medical treatments: to learn
whether they work well enough, called "efficacy", or "effectiveness";
and to learn whether they are safe enough, called "safety". Neither is an absolute criterion; both safety and efficacy are
evaluated relative to how the treatment is intended to be used, what
other treatments are available, and the severity of the disease or
condition. The benefits must outweigh the risks.
For example, many drugs to treat cancer have severe side effects that
would not be acceptable for an over-the-counter pain medication, yet the
cancer drugs have been approved since they are used under a physician's
care and are used for a life-threatening condition.
In the US the elderly constitute 14% of the population, while they consume over one-third of drugs. People over 55 (or a similar cutoff age) are often excluded from trials
because their greater health issues and drug use complicate data
interpretation, and because they have different physiological capacity
than younger people. Children and people with unrelated medical
conditions are also frequently excluded. Pregnant women are often excluded due to potential risks to the fetus.
The sponsor designs the trial in coordination with a panel of
expert clinical investigators, including what alternative or existing
treatments to compare to the new drug and what type(s) of patients might
benefit. If the sponsor cannot obtain enough test subjects at one
location investigators at other locations are recruited to join the
study.
During the trial, investigators recruit subjects with the
predetermined characteristics, administer the treatment(s) and collect
data on the subjects' health for a defined time period. Data include
measurements such as vital signs,
concentration of the study drug in the blood or tissues, changes to
symptoms, and whether improvement or worsening of the condition targeted
by the study drug occurs. The researchers send the data to the trial
sponsor, who then analyzes the pooled data using statistical tests.
Examples of clinical trial goals include assessing the safety and relative effectiveness of a medication or device:
On a specific kind of patient
At varying dosages
For a new indication
Evaluation for improved efficacy in treating a condition as compared to the standard therapy for that condition
Evaluation of the study drug or device relative to two or more already approved/common interventions for that condition
While most clinical trials test one alternative to the novel intervention, some expand to three or four and may include a placebo.
Except for small, single-location trials, the design and objectives are specified in a document called a clinical trial protocol.
The protocol is the trial's "operating manual" and ensures all
researchers perform the trial in the same way on similar subjects and
that the data is comparable across all subjects.
As a trial is designed to test hypotheses and rigorously monitor and assess outcomes, it can be seen as an application of the scientific method, specifically the experimental step.
Similarly to drugs, manufacturers of medical devices in the United States are required to conduct clinical trials for premarket approval. Device trials may compare a new device to an established therapy, or
may compare similar devices to each other. An example of the former in
the field of vascular surgery is the Open versus Endovascular Repair (OVER trial) for the treatment of abdominal aortic aneurysm, which compared the older open aortic repair technique to the newer endovascular aneurysm repair device. An example of the latter are clinical trials on mechanical devices used in the management of adult female urinary incontinence.
Trials of procedures
Similarly to drugs, medical or surgical procedures may be subjected to clinical trials, such as comparing different surgical approaches in treatment of fibroids for subfertility. However, when clinical trials are unethical or logistically impossible in the surgical setting, case-controlled studies will be replaced.
Patient and public involvement
Besides
being participants in a clinical trial, members of the public can be
actively collaborate with researchers in designing and conducting clinical research. This is known as patient and public involvement
(PPI). Public involvement involves a working partnership between
patients, caregivers, people with lived experience, and researchers to
shape and influence what is researcher and how. PPI can improve the quality of research and make it more relevant and
accessible. People with current or past experience of illness can
provide a different perspective than professionals and compliment their
knowledge. Through their personal knowledge they can identify research
topics that are relevant and important to those living with an illness
or using a service. They can also help to make the research more
grounded in the needs of the specific communities they are part of.
Public contributors can also ensure that the research is presented in plain language that is clear to the wider society and the specific groups it is most relevant for.
Although early medical experimentation was performed often, the use of a control group to provide an accurate comparison for the demonstration of the intervention's efficacy was generally lacking. For instance, Lady Mary Wortley Montagu, who campaigned for the introduction of inoculation (then called variolation) to prevent smallpox,
arranged for seven prisoners who had been sentenced to death to undergo
variolation in exchange for their life. Although they survived and did
not contract smallpox, there was no control group to assess whether this
result was due to the inoculation or some other factor. Similar
experiments performed by Edward Jenner over his smallpox vaccine were equally conceptually flawed.
The first proper clinical trial was conducted by the Scottish physician James Lind. The disease scurvy, now known to be caused by a Vitamin C
deficiency, would often have terrible effects on the welfare of the
crew of long-distance ocean voyages. In 1740, the catastrophic result of
Anson's circumnavigation attracted much attention in Europe; out of 1900 men, 1400 had died, most of them allegedly from having contracted scurvy. John Woodall, an English military surgeon of the British East India Company, had recommended the consumption of citrus fruit from the 17th century, but their use did not become widespread.
Lind conducted the first systematic clinical trial in 1747. He included a dietary supplement of an acidic quality in the experiment
after two months at sea, when the ship was already afflicted with
scurvy. He divided twelve scorbutic sailors into six groups of two. They
all received the same diet but, in addition, group one was given a
quart of cider daily, group two twenty-five drops of elixir of vitriol (sulfuric acid), group three six spoonfuls of vinegar, group four half a pint of seawater, group five received two oranges and one lemon, and the last group a spicy paste plus a drink of barley water.
The treatment of group five stopped after six days when they ran out of
fruit, but by then one sailor was fit for duty while the other had
almost recovered. Apart from that, only group one also showed some
effect of its treatment. Each year, May 20 is celebrated as Clinical Trials Day in honor of Lind's research.
After 1750 the discipline began to take its modern shape. The English doctor John Haygarth demonstrated the importance of a control group for the correct identification of the placebo effect in his celebrated study of the ineffective remedy called Perkin's tractors. Further work in that direction was carried out by the eminent physician Sir William Gull, 1st Baronet in the 1860s.
Frederick Akbar Mahomed (d. 1884), who worked at Guy's Hospital in London, made substantial contributions to the process of clinical trials, where "he separated chronic nephritis with secondary hypertension from what we now term essential hypertension. He also founded the Collective Investigation Record for the British Medical Association;
this organization collected data from physicians practicing outside the
hospital setting and was the precursor of modern collaborative clinical
trials."
Modern trials
Austin Bradford Hill was a pivotal figure in the modern development of clinical trials.
Ideas of Sir Ronald A. Fisher still play a role in clinical trials. While working for the Rothamsted experimental station in the field of agriculture, Fisher developed his Principles of experimental design in the 1920s as an accurate methodology for the proper design of experiments. Among his major ideas include the importance of randomization—the random assignment of individual elements (eg crops or patients) to different groups for the experiment; replication—to reduce uncertainty, measurements should be repeated and experiments replicated to identify sources of variation; blocking—to
arrange experimental units into groups of units that are similar to
each other, and thus reducing irrelevant sources of variation; use of factorial experiments—efficient at evaluating the effects and possible interactions of several independent factors. Of these, blocking and factorial design are seldom applied in clinical
trials, because the experimental units are human subjects and there is
typically only one independent intervention: the treatment.
The British Medical Research Council officially recognized the importance of clinical trials from the 1930s. The council established the Therapeutic Trials Committee
to advise and assist in the arrangement of properly controlled clinical
trials on new products that seem likely on experimental grounds to have
value in the treatment of disease.
The first randomised curative trial was carried out at the MRC
Tuberculosis Research Unit by Sir Geoffrey Marshall (1887–1982). The
trial, carried out between 1946 and 1947, aimed to test the efficacy of
the chemical streptomycin for curing pulmonary tuberculosis. The trial was both double-blind and placebo-controlled.
The methodology of clinical trials was further developed by Sir Austin Bradford Hill, who had been involved in the streptomycin trials. From the 1920s, Hill applied statistics to medicine, attending the lectures of renowned mathematician Karl Pearson, among others. He became famous for a landmark study carried out in collaboration with Richard Doll on the correlation between smoking and lung cancer. They carried out a case-control study in 1950, which compared lung cancer patients with matched control and also began a sustained long-term prospective study into the broader issue of smoking and health, which involved studying the smoking habits and health of more than 30,000 doctors over a period of several years. His certificate for election to the Royal Society called him "...the
leader in the development in medicine of the precise experimental
methods now used nationally and internationally in the evaluation of new
therapeutic and prophylactic agents."
International clinical trials day is celebrated on 20 May.
The acronyms used in the titling of clinical trials are often contrived, and have been the subject of derision.
Types
Clinical trials are classified by the research objective created by the investigators.
In an observational study, the investigators observe the subjects and measure their outcomes. The researchers do not actively manage the study.
In an interventional study, the investigators give the
research subjects an experimental drug, surgical procedure, use of a
medical device, diagnostic or other intervention to compare the treated
subjects with those receiving no treatment or the standard treatment.
Then the researchers assess how the subjects' health changes.
Trials are classified by their purpose. After approval for human research is granted to the trial sponsor, the U.S. Food and Drug Administration (FDA) organizes and monitors the results of trials according to type:
Prevention trials look for ways to prevent disease in
people who have never had the disease or to prevent a disease from
returning. These approaches may include drugs, vitamins or other micronutrients, vaccines, or lifestyle changes.
Screening trials test for ways to identify certain diseases or health conditions.
Diagnostic trials are conducted to find better tests or procedures for diagnosing a particular disease or condition.
Treatment trials test experimental drugs, new combinations of drugs, or new approaches to surgery or radiation therapy.
Quality of life trials (supportive care trials) evaluate how to improve comfort and quality of care for people with a chronic illness.
Genetic
trials are conducted to assess the prediction accuracy of genetic
disorders making a person more or less likely to develop a disease.
Epidemiological trials have the goal of identifying the general causes, patterns or control of diseases in large numbers of people.
Compassionate use trials or expanded access
trials provide partially tested, unapproved therapeutics to a small
number of patients who have no other realistic options. Usually, this
involves a disease for which no effective therapy has been approved, or a
patient who has already failed all standard treatments and whose health
is too compromised to qualify for participation in randomized clinical
trials. Usually, case-by-case approval must be granted by both the FDA and the pharmaceutical company for such exceptions.
Fixed trials consider existing data only during the trial's design,
do not modify the trial after it begins, and do not assess the results
until the study is completed.
Adaptive clinical trials
use existing data to design the trial, and then use interim results to
modify the trial as it proceeds. Modifications include dosage, sample
size, drug undergoing trial, patient selection criteria and "cocktail"
mix. Adaptive trials often employ a Bayesian experimental design
to assess the trial's progress. In some cases, trials have become an
ongoing process that regularly adds and drops therapies and patient
groups as more information is gained. The aim is to more quickly identify drugs that have a therapeutic
effect and to zero in on patient populations for whom the drug is
appropriate.
Clinical trials are conducted typically in four phases, with each
phase using different numbers of subjects and having a different purpose
to construct focus on identifying a specific effect.
Clinical trials involving new drugs are commonly classified into five
phases. Each phase of the drug approval process is treated as a
separate clinical trial. The drug development process will normally proceed through phases I–IV over many years, frequently involving a decade
or longer. 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 trials are performed after the newly approved drug, diagnostic
or device is marketed, providing assessment about risks, benefits, or
best uses.
Phase 0 trials are optional first-in-human trials. Single
subtherapeutic doses of the study drug or treatment are given to a small
number of subjects (typically 10 to 15) to gather preliminary data on
the agent's pharmacodynamics (what the drug does to the body) and
pharmacokinetics (what the body does to the drugs). For a test drug, the trial documents the absorption, distribution,
metabolization, and clearance (excretion) of the drug, and the drug's
interactions within the body, to confirm that these appear to be as
expected.
Phase I
Screening for safety
Often are first-in-person trials. Testing within a small group of
people (typically 20–80) to evaluate safety, determine safe dosage
ranges, and identify side effects.
Phase II-a is specifically designed to assess dosing requirements (how much drug should be given), while a Phase II-b trial is designed to determine efficacy (100–300 people), assessing how well the drug works at the prescribed dose(s) to
establish a therapeutic dose range and monitor for possible side
effects.
Phase III
Final confirmation of safety and efficacy
Testing with large groups of people (typically 1,000–3,000) to
confirm drug efficacy, evaluate its effectiveness, monitor side effects,
compare it to commonly used treatments, and collect information that
will allow it to be used safely.
Phase IV
Safety studies during sales
Postmarketing studies delineate risks, benefits, and optimal use. As
such, they are ongoing during the drug's lifetime of active medical
use.
A fundamental distinction in evidence-based practice is between observational studies and randomized controlled trials. Types of observational studies in epidemiology, such as the cohort study and the case-control study, provide less compelling evidence than the randomized controlled trial. In observational studies, the investigators retrospectively assess
associations between the treatments given to participants and their
health status, with potential for considerable errors in design and
interpretation.
A randomized controlled trial can provide compelling evidence that the study treatment causes an effect on human health.
Some Phase II and most Phase III drug trials are designed as randomized, double-blind, and placebo-controlled.
Randomized: Each study subject is randomly assigned to receive either the study treatment or a placebo.
Blind: The subjects involved in the study do not know which study
treatment they receive. If the study is double-blind, the researchers
also do not know which treatment a subject receives. This intent is to
prevent researchers from treating the two groups differently. A form of
double-blind study called a "double-dummy" design allows additional
insurance against bias. In this kind of study, all patients are given
both placebo and active doses in alternating periods.
Placebo-controlled: The use of a placebo (fake treatment) allows the
researchers to isolate the effect of the study treatment from the placebo effect.
Clinical studies having small numbers of subjects may be "sponsored"
by single researchers or a small group of researchers, and are designed
to test simple questions or feasibility to expand the research for a
more comprehensive randomized controlled trial.
Clinical studies can be "sponsored" (financed and organized) by
academic institutions, pharmaceutical companies, government entities and
even private groups. Trials are conducted for new drugs, biotechnology,
diagnostic assays or medical devices to determine their safety and
efficacy prior to being submitted for regulatory review that would
determine market approval.
Active control studies
In
cases where giving a placebo to a person suffering from a disease may
be unethical, "active comparator" (also known as "active control")
trials may be conducted instead. In trials with an active control group, subjects are given either the
experimental treatment or a previously approved treatment with known
effectiveness. In other cases, sponsors may conduct an active comparator
trial to establish an efficacy claim relative to the active comparator
instead of the placebo in labeling.
Master protocol
A
master protocol includes multiple substudies, which may have different
objectives and involve coordinated efforts to evaluate one or more
medical products in one or more diseases or conditions within the
overall study structure. Trials that could develop a master protocol
include the umbrella trial (multiple medical products for a single
disease), platform trial
(multiple products for a single disease entering and leaving the
platform), and basket trial (one medical product for multiple diseases
or disease subtypes).
Genetic testing
enables researchers to group patients according to their genetic
profile, deliver drugs based on that profile to that group and compare
the results. Multiple companies can participate, each bringing a
different drug. The first such approach targets squamous cell cancer,
which includes varying genetic disruptions from patient to patient.
Amgen, AstraZeneca and Pfizer are involved, the first time they have
worked together in a late-stage trial. Patients whose genomic profiles
do not match any of the trial drugs receive a drug designed to stimulate
the immune system to attack cancer.
A clinical trial protocol
is a document used to define and manage the trial. It is prepared by a
panel of experts. All study investigators are expected to strictly
observe the protocol.
The protocol describes the scientific rationale, objective(s),
design, methodology, statistical considerations and organization of the
planned trial. Details of the trial are provided in documents referenced
in the protocol, such as an investigator's brochure.
The protocol contains a precise study plan to assure safety and
health of the trial subjects and to provide an exact template for trial
conduct by investigators. This allows data to be combined across all
investigators/sites. The protocol also informs the study administrators
(often a contract research organization).
The format and content of clinical trial protocols sponsored by
pharmaceutical, biotechnology or medical device companies in the United
States, European Union, or Japan have been standardized to follow Good
Clinical Practice guidance issued by the International Conference on Harmonisation (ICH). Regulatory authorities in Canada, China, South Korea, and the UK also follow ICH guidelines. Journals such as Trials, encourage investigators to publish their protocols.
Design features
Informed consent
Example of informed consent document from the PARAMOUNT trial
Clinical trials recruit study subjects to sign a document representing their "informed consent". The document includes details such as its purpose, duration, required
procedures, risks, potential benefits, key contacts and institutional
requirements. The participant then decides whether to sign the document. The document
is not a contract, as the participant can withdraw at any time without
penalty.
Informed consent is a legal process in which a recruit is instructed about key facts before deciding whether to participate. Researchers explain the details of the study in terms the subject can
understand. The information is presented in the subject's native
language. Generally, children cannot autonomously provide informed
consent, but depending on their age and other factors, may be required
to provide informed assent.
Statistical power
In
any clinical trial, the number of subjects, also called the sample
size, has a large impact on the ability to reliably detect and measure
the effects of the intervention. This ability is described as its "power", which must be calculated before initiating a study to figure out if the study is worth its costs. In general, a larger sample size increases the statistical power, also the cost.
The statistical power estimates the ability of a trial to detect a
difference of a particular size (or larger) between the treatment and
control groups. For example, a trial of a lipid-lowering
drug versus placebo with 100 patients in each group might have a power
of 0.90 to detect a difference between placebo and trial groups
receiving dosage of 10 mg/dL or more, but only 0.70 to detect a
difference of 6 mg/dL.
Merely giving a treatment can have nonspecific effects. These are
controlled for by the inclusion of patients who receive only a placebo.
Subjects are assigned randomly
without informing them to which group they belonged. Many trials are
doubled-blinded so that researchers do not know to which group a subject
is assigned.
Assigning a subject to a placebo group can pose an ethical
problem if it violates his or her right to receive the best available
treatment. The Declaration of Helsinki provides guidelines on this issue.
Duration
Timeline of various approval tracks and research phases in the US
Clinical trials are only a small part of the research that goes into
developing a new treatment. Potential drugs, for example, first have to
be discovered, purified, characterized, and tested in labs (in cell and
animal studies) before ever undergoing clinical trials. In all, about
1,000 potential drugs are tested before just one reaches the point of
being tested in a clinical trial. For example, a new cancer drug has, on average, six years of research
behind it before it even makes it to clinical trials. But the major
holdup in making new cancer drugs available is the time it takes to
complete clinical trials themselves. On average, about eight years pass
from the time a cancer drug enters clinical trials until it receives
approval from regulatory agencies for sale to the public. Drugs for other diseases have similar timelines.
Some reasons a clinical trial might last several years:
For chronic conditions such as cancer, it takes months, if not years, to see if a cancer treatment has an effect on a patient.
For drugs that are not expected to have a strong effect (meaning a
large number of patients must be recruited to observe 'any' effect),
recruiting enough patients to test the drug's effectiveness (i.e.,
getting statistical power) can take several years.
Only certain people who have the target disease condition are
eligible to take part in each clinical trial. Researchers who treat
these particular patients must participate in the trial. Then they must
identify the desirable patients and obtain consent from them or their
families to take part in the trial.
A clinical trial might also include an extended post-study follow-up
period from months to years for people who have participated in the
trial, a so-called "extension phase", which aims to identify long-term
impact of the treatment.
The biggest barrier to completing studies is the shortage of
people who take part. All drug and many device trials target a subset of
the population, meaning not everyone can participate. Some drug trials
require patients to have unusual combinations of disease
characteristics. It is a challenge to find the appropriate patients and
obtain their consent, especially when they may receive no direct benefit
(because they are not paid, the study drug is not yet proven to work,
or the patient may receive a placebo). In the case of cancer patients,
fewer than 5% of adults with cancer will participate in drug trials.
According to the Pharmaceutical Research and Manufacturers of America
(PhRMA), about 400 cancer medicines were being tested in clinical trials
in 2005. Not all of these will prove to be useful, but those that are
may be delayed in getting approved because the number of participants is
so low.
For clinical trials involving potential for seasonal influences (such as airborne allergies, seasonal affective disorder, influenza, and skin diseases), the study may be done during a limited part of the year (such as spring for pollen allergies), when the drug can be tested.
Clinical trials that do not involve a new drug usually have a
much shorter duration. (Exceptions are epidemiological studies, such as
the Nurses' Health Study).
Administration
Clinical
trials designed by a local investigator, and (in the US) federally
funded clinical trials, are almost always administered by the researcher
who designed the study and applied for the grant. Small-scale device
studies may be administered by the sponsoring company. Clinical trials
of new drugs are usually administered by a contract research organization
(CRO) hired by the sponsoring company. The sponsor provides the drug
and medical oversight. A CRO is contracted to perform all the
administrative work on a clinical trial. For PhasesII–IV
the CRO recruits participating researchers, trains them, provides them
with supplies, coordinates study administration and data collection,
sets up meetings, monitors the sites for compliance with the clinical
protocol, and ensures the sponsor receives data from every site.
Specialist site management organizations
can also be hired to coordinate with the CRO to ensure rapid IRB/IEC
approval and faster site initiation and patient recruitment. PhaseI
clinical trials of new medicines are often conducted in a specialist
clinical trial clinic, with dedicated pharmacologists, where the
subjects can be observed by full-time staff. These clinics are often run
by a CRO which specialises in these studies.
At a participating site, one or more research assistants (often
nurses) do most of the work in conducting the clinical trial. The
research assistant's job can include some or all of the following:
providing the local institutional review board
(IRB) with the documentation necessary to obtain its permission to
conduct the study, assisting with study start-up, identifying eligible
patients, obtaining consent from them or their families, administering
study treatment(s), collecting and statistically analyzing data,
maintaining and updating data files during followup, and communicating
with the IRB, as well as the sponsor and CRO.
Quality
In
the context of a clinical trial, quality typically refers to the
absence of errors which can impact decision making, both during the
conduct of the trial and in use of the trial results.
Marketing
An
Interactional Justice Model may be used to test the effects of
willingness to talk with a doctor about clinical trial enrollment.[66]
Results found that potential clinical trial candidates were less likely
to enroll in clinical trials if the patient is more willing to talk
with their doctor. The reasoning behind this discovery may be patients
are happy with their current care. Another reason for the negative
relationship between perceived fairness and clinical trial enrollment is
the lack of independence from the care provider. Results found that
there is a positive relationship between a lack of willingness to talk
with their doctor and clinical trial enrollment. Lack of willingness to
talk about clinical trials with current care providers may be due to
patients' independence from the doctor. Patients who are less likely to
talk about clinical trials are more willing to use other sources of
information to gain a better insight of alternative treatments. Clinical
trial enrollment should be motivated to utilize websites and television
advertising to inform the public about clinical trial enrollment.
Information technology
The last decade has seen a proliferation of information technology use in the planning and conduct of clinical trials. Clinical trial management systems
are often used by research sponsors or CROs to help plan and manage the
operational aspects of a clinical trial, particularly with respect to
investigational sites. Advanced analytics for identifying researchers
and research sites with expertise in a given area utilize public and
private information about ongoing research. Web-based electronic data capture (EDC) and clinical data management systems are used in a majority of clinical trials to collect case report data from sites, manage its quality and prepare it for analysis. Interactive voice response
systems are used by sites to register the enrollment of patients using a
phone and to allocate patients to a particular treatment arm (although
phones are being increasingly replaced with web-based (IWRS) tools which
are sometimes part of the EDC system). While patient-reported outcome were often paper based in the past, measurements are increasingly being collected using web portals or hand-held ePRO (or eDiary) devices, sometimes wireless. Statistical software
is used to analyze the collected data and prepare them for regulatory
submission. Access to many of these applications are increasingly
aggregated in web-based clinical trial portals. In 2011, the FDA approved a PhaseI
trial that used telemonitoring, also known as remote patient
monitoring, to collect biometric data in patients' homes and transmit it
electronically to the trial database. This technology provides many
more data points and is far more convenient for patients, because they
have fewer visits to trial sites. As noted below, decentralized clinical
trials are those that do not require patients' physical presence at a
site, and instead rely largely on digital health data collection,
digital informed consent processes, and so on.
A clinical trial produces data that could reveal quantitative differences between two or more interventions; statistical analyses are used to determine whether such differences are true, result from chance, or are the same as no treatment (placebo).Data from a clinical trial accumulate gradually over the trial duration, extending from months to years. Accordingly, results for participants recruited early in the study
become available for analysis while subjects are still being assigned to
treatment groups in the trial. Early analysis may allow the emerging
evidence to assist decisions about whether to stop the study, or to
reassign participants to the more successful segment of the trial. Investigators may also want to stop a trial when data analysis shows no treatment effect.
Clinical trials are closely supervised by appropriate regulatory
authorities. All studies involving a medical or therapeutic intervention
on patients must be approved by a supervising ethics committee before
permission is granted to run the trial. The local ethics committee has
discretion on how it will supervise noninterventional studies
(observational studies or those using already collected data). In the
US, this body is called the Institutional Review Board (IRB); in the EU, they are called Ethics committees.
Most IRBs are located at the local investigator's hospital or
institution, but some sponsors allow the use of a central
(independent/for profit) IRB for investigators who work at smaller
institutions.
To be ethical, researchers must obtain the full and informed consent
of participating human subjects. (One of the IRB's main functions is to
ensure potential patients are adequately informed about the clinical
trial.) If the patient is unable to consent for him/herself, researchers
can seek consent from the patient's legally authorized representative.
In addition, the clinical trial participants must be made aware that
they can withdraw from the clinical trial at any time without any
adverse action taken against them. In California, the state has prioritized the individuals who can serve as the legally authorized representative.
In some US locations, the local IRB must certify researchers and
their staff before they can conduct clinical trials. They must
understand the federal patient privacy (HIPAA)
law and good clinical practice. The International Conference of
Harmonisation Guidelines for Good Clinical Practice is a set of
standards used internationally for the conduct of clinical trials. The
guidelines aim to ensure the "rights, safety and well being of trial
subjects are protected".
The notion of informed consent of participating human subjects
exists in many countries but its precise definition may still vary.
Informed consent is clearly a 'necessary' condition for ethical conduct but does not 'ensure' ethical conduct. In compassionate use
trials the latter becomes a particularly difficult problem. The final
objective is to serve the community of patients or future patients in a
best-possible and most responsible way. See also Expanded access.
However, it may be hard to turn this objective into a well-defined,
quantified, objective function. In some cases this can be done, however,
for instance, for questions of when to stop sequential treatments (see Odds algorithm), and then quantified methods may play an important role.
Ethically balancing the rights of multiple stakeholders may be
difficult. For example, when drug trials fail, the sponsors may have a
duty to tell current and potential investors immediately, which means
both the research staff and the enrolled participants may first hear
about the end of a trial through public business news.
Conflicts of interest and unfavorable studies
In response to specific cases in which unfavorable data from pharmaceutical company-sponsored research were not published, the Pharmaceutical Research and Manufacturers of America
published new guidelines urging companies to report all findings and
limit the financial involvement in drug companies by researchers. The US Congress signed into law a bill which requires PhaseII and PhaseIII clinical trials to be registered by the sponsor on the clinicaltrials.gov website compiled by the National Institutes of Health.
Drug researchers not directly employed by pharmaceutical
companies often seek grants from manufacturers, and manufacturers often
look to academic researchers to conduct studies within networks of
universities and their hospitals, e.g., for translational
cancer research. Similarly, competition for tenured academic positions,
government grants and prestige create conflicts of interest among
academic scientists. According to one study, approximately 75% of articles retracted for
misconduct-related reasons have no declared industry financial support. Seeding trials are particularly controversial.
In the United States, all clinical trials submitted to the FDA as
part of a drug approval process are independently assessed by clinical
experts within the Food and Drug Administration, including inspections of primary data collection at selected clinical trial sites.
In 2001, the editors of 12 major journals issued a joint
editorial, published in each journal, on the control over clinical
trials exerted by sponsors, particularly targeting the use of contracts
which allow sponsors to review the studies prior to publication and
withhold publication. They strengthened editorial restrictions to
counter the effect. The editorial noted that contract research organizations had, by 2000, received 60% of the grants from pharmaceutical companies
in the US. Researchers may be restricted from contributing to the trial
design, accessing the raw data, and interpreting the results.
Despite explicit recommendations by stakeholders of measures to improve the standards of industry-sponsored medical research, in 2013, Tohen
warned of the persistence of a gap in the credibility of conclusions
arising from industry-funded clinical trials, and called for ensuring
strict adherence to ethical standards in industrial collaborations with
academia, in order to avoid further erosion of the public's trust. Issues referred for attention in this respect include potential
observation bias, duration of the observation time for maintenance
studies, the selection of the patient populations, factors that affect
placebo response, and funding sources.
During public health crisis
Conducting
clinical trials of vaccines during epidemics and pandemics is subject
to ethical concerns. For diseases with high mortality rates like Ebola,
assigning individuals to a placebo or control group can be viewed as a
death sentence. In response to ethical concerns regarding clinical
research during epidemics, the National Academy of Medicine authored a report identifying seven ethical and scientific considerations. These considerations are:
Scientific value
Social value
Respect for persons
Community engagement
Concern for participant welfare and interests
A balance towards benefit over risks
Post-trial access to tested therapies that had been withheld during the trial
Pregnant women and children are typically excluded from clinical
trials as vulnerable populations, though the data to support excluding
them is not robust. By excluding them from clinical trials, information
about the safety and effectiveness of therapies for these populations is
often lacking. During the early history of the HIV/AIDS
epidemic, a scientist noted that by excluding these groups from
potentially life-saving treatment, they were being "protected to death".
Projects such as Research Ethics for Vaccines, Epidemics, and New
Technologies (PREVENT) have advocated for the ethical inclusion of
pregnant women in vaccine trials. Inclusion of children in clinical
trials has additional moral considerations, as children lack
decision-making autonomy. Trials in the past had been criticized for
using hospitalized children or orphans; these ethical concerns
effectively stopped future research. In efforts to maintain effective
pediatric care, several European countries and the US have policies to
entice or compel pharmaceutical companies to conduct pediatric trials.
International guidance recommends ethical pediatric trials by limiting
harm, considering varied risks, and taking into account the complexities
of pediatric care.
Safety
Responsibility
for the safety of the subjects in a clinical trial is shared between
the sponsor, the local site investigators (if different from the
sponsor), the various IRBs that supervise the study, and (in some cases,
if the study involves a marketable drug or device), the regulatory
agency for the country where the drug or device will be sold.
A systematic concurrent safety review is frequently employed to
assure research participant safety. The conduct and on-going review is
designed to be proportional to the risk of the trial. Typically this
role is filled by a Data and Safety Committee, an externally appointed Medical Safety Monitor, an Independent Safety Officer, or for small or low-risk studies the principal investigator.
For safety reasons, many clinical trials of drugs are designed to exclude women of childbearing age, pregnant women, or
women who become pregnant during the study. In some cases, the male
partners of these women are also excluded or required to take birth
control measures.
Sponsor
Throughout
the clinical trial, the sponsor is responsible for accurately informing
the local site investigators of the true historical safety record of
the drug, device or other medical treatments to be tested, and of any
potential interactions of the study treatment(s) with already approved
treatments. This allows the local investigators to make an informed
judgment on whether to participate in the study or not. The sponsor is
also responsible for monitoring
the results of the study as they come in from the various sites as the
trial proceeds. In larger clinical trials, a sponsor will use the
services of a data monitoring committee
(DMC, known in the US as a data safety monitoring board). This
independent group of clinicians and statisticians meets periodically to
review the unblinded
data the sponsor has received so far. The DMC has the power to
recommend termination of the study based on their review, for example if
the study treatment is causing more deaths than the standard treatment,
or seems to be causing unexpected and study-related serious adverse events. The sponsor is responsible for collecting adverse event
reports from all site investigators in the study, and for informing all
the investigators of the sponsor's judgment as to whether these adverse
events were related or not related to the study treatment.
The sponsor and the local site investigators are jointly responsible for writing a site-specific informed consent
that accurately informs the potential subjects of the true risks and
potential benefits of participating in the study, while at the same time
presenting the material as briefly as possible and in ordinary
language. FDA regulations state that participating in clinical trials is
voluntary, with the subject having the right not to participate or to
end participation at any time.
Local site investigators
The ethical principle of primum non-nocere
("first, do no harm") guides the trial, and if an investigator believes
the study treatment may be harming subjects in the study, the
investigator can stop participating at any time. On the other hand,
investigators often have a financial interest in recruiting subjects,
and could act unethically to obtain and maintain their participation.
The local investigators are responsible for conducting the study
according to the study protocol, and supervising the study staff
throughout the duration of the study. The local investigator or his/her
study staff are also responsible for ensuring the potential subjects in
the study understand the risks and potential benefits of participating
in the study. In other words, they (or their legally authorized
representatives) must give truly informed consent.
Local investigators are responsible for reviewing all adverse
event reports sent by the sponsor. These adverse event reports contain
the opinions of both the investigator (at the site where the adverse
event occurred) and the sponsor, regarding the relationship of the
adverse event to the study treatments. Local investigators also are
responsible for making an independent judgment of these reports, and
promptly informing the local IRB of all serious and study
treatment-related adverse events.
When a local investigator is the sponsor, there may not be formal
adverse event reports, but study staff at all locations are responsible
for informing the coordinating investigator of anything unexpected. The
local investigator is responsible for being truthful to the local IRB
in all communications relating to the study.
Institutional review boards (IRBs)
Approval by an Institutional Review Board (IRB), or Independent Ethics Committee
(IEC), is necessary before all but the most informal research can
begin. In commercial clinical trials, the study protocol is not approved
by an IRB before the sponsor recruits sites to conduct the trial.
However, the study protocol and procedures have been tailored to fit
generic IRB submission requirements. In this case, and where there is no
independent sponsor, each local site investigator submits the study
protocol, the consent(s), the data collection forms, and supporting
documentation to the local IRB. Universities and most hospitals have
in-house IRBs. Other researchers (such as in walk-in clinics) use
independent IRBs.
The IRB scrutinizes the study both for medical safety and for
protection of the patients involved in the study, before it allows the
researcher to begin the study. It may require changes in study
procedures or in the explanations given to the patient. A required
yearly "continuing review" report from the investigator updates the IRB
on the progress of the study and any new safety information related to
the study.
Regulatory agencies
In the US, the FDA can audit
the files of local site investigators after they have finished
participating in a study, to see if they were correctly following study
procedures. This audit may be random, or for cause (because the
investigator is suspected of fraudulent data). Avoiding an audit is an
incentive for investigators to follow study procedures. A 'covered
clinical study' refers to a trial submitted to the FDA as part of a
marketing application (for example, as part of an NDA or 510(k)), about which the FDA may require disclosure of financial interest of the clinical investigator
in the outcome of the study. For example, the applicant must disclose
whether an investigator owns equity in the sponsor, or owns proprietary
interest in the product under investigation. The FDA defines a covered
study as "...any study of a drug,
biological product or device in humans submitted in a marketing
application or reclassification petition that the applicant or FDA
relies on to establish that the product is effective (including studies
that show equivalence to an effective product) or any study in which a
single investigator makes a significant contribution to the
demonstration of safety."
Alternatively, many American pharmaceutical companies have moved
some clinical trials overseas. Benefits of conducting trials abroad
include lower costs (in some countries) and the ability to run larger
trials in shorter timeframes, whereas a potential disadvantage exists in
lower-quality trial management. Different countries have different regulatory requirements and
enforcement abilities. An estimated 40% of all clinical trials now take
place in Asia, Eastern Europe, and Central and South America. "There is
no compulsory registration system for clinical trials in these countries
and many do not follow European directives in their operations", says
Jacob Sijtsma of the Netherlands-based WEMOS, an advocacy health
organisation tracking clinical trials in developing countries.
Beginning in the 1980s, harmonization of clinical trial protocols
was shown as feasible across countries of the European Union. At the
same time, coordination between Europe, Japan and the United States led
to a joint regulatory-industry initiative on international harmonization
named after 1990 as the International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH). Currently, most clinical trial programs follow ICH guidelines, aimed at
"ensuring that good quality, safe and effective medicines are developed
and registered in the most efficient and cost-effective manner. These
activities are pursued in the interest of the consumer and public
health, to prevent unnecessary duplication of clinical trials in humans
and to minimize the use of animal testing without compromising the
regulatory obligations of safety and effectiveness."
Aggregation of safety data during clinical development
Aggregating
safety data across clinical trials during drug development is important
because trials are generally designed to focus on determining how well
the drug works. The safety data collected and aggregated across multiple
trials as the drug is developed allows the sponsor, investigators and
regulatory agencies to monitor the aggregate safety profile of
experimental medicines as they are developed. The value of assessing
aggregate safety data is: a) decisions based on aggregate safety
assessment during development of the medicine can be made throughout the
medicine's development and b) it sets up the sponsor and regulators
well for assessing the medicine's safety after the drug is approved.
Economics
Clinical
trial costs vary depending on trial phase, type of trial, and disease
studied. A study of clinical trials conducted in the United States from
2004 to 2012 found the average cost of PhaseI
trials to be between $1.4 million and $6.6 million, depending on the
type of disease. Phase II trials ranged from $7 million to $20 million,
and PhaseIII trials from $11 million to $53 million.
Sponsor
The
cost of a study depends on many factors, especially the number of sites
conducting the study, the number of patients involved, and whether the
study treatment is already approved for medical use.
The expenses incurred by a pharmaceutical company in administering a Phase III orIV clinical trial may include, among others:
production of the drug(s) or device(s) being evaluated
staff salaries for the designers and administrators of the trial
payments to the contract research organization, the site management organization (if used) and any outside consultants
payments to local researchers and their staff for their time and
effort in recruiting test subjects and collecting data for the sponsor
the cost of study materials and the charges incurred to ship them
communication with the local researchers, including on-site
monitoring by the CRO before and (in some cases) multiple times during
the study
one or more investigator training meetings
expense incurred by the local researchers, such as pharmacy fees, IRB fees and postage
any payments to subjects enrolled in the trial
the expense of treating a test subject who develops a medical condition caused by the study drug
These expenses are incurred over several years.
In the US, sponsors may receive a 50 percent tax credit for clinical trials conducted on drugs being developed for the treatment of orphan diseases. National health agencies, such as the US National Institutes of Health,
offer grants to investigators who design clinical trials that attempt
to answer research questions of interest to the agency. In these cases,
the investigator who writes the grant and administers the study acts as
the sponsor, and coordinates data collection from any other sites. These
other sites may or may not be paid for participating in the study,
depending on the amount of the grant and the amount of effort expected
from them. Using internet resources can, in some cases, reduce the
economic burden.
Investigators
Investigators
are often compensated for their work in clinical trials. These amounts
can be small, just covering a partial salary for research assistants and
the cost of any supplies (usually the case with national health agency
studies), or be substantial and include "overhead" that allows the
investigator to pay the research staff during times between clinical
trials.
Subjects
Participants
in Phase I drug trials do not gain any direct health benefit from
taking part. They are generally paid a fee for their time, with payments
regulated and not related to any risk involved. Motivations of healthy
volunteers is not limited to financial reward and may include other
motivations such as contributing to science and others. In later phase trials, subjects may not be paid to ensure their
motivation for participating with potential for a health benefit or
contributing to medical knowledge. Small payments may be made for
study-related expenses such as travel or as compensation for their time
in providing follow-up information about their health after the trial
treatment ends.
Phase 0 and Phase I drug trials seek healthy volunteers. Most other
clinical trials seek patients who have a specific disease or medical
condition. The diversity observed in society should be reflected in
clinical trials through the appropriate inclusion of ethnic minority populations. Patient recruitment or participant recruitment plays a significant role in the activities and responsibilities of sites conducting clinical trials.
All volunteers being considered for a trial are required to
undertake a medical screening. Requirements differ according to the
trial needs, but typically volunteers would be screened in a medical laboratory for:
Measurement of the electrical activity of the heart (ECG)
Measurement of blood pressure, heart rate, and body temperature
Blood sampling
Urine sampling
Weight and height measurement
Drug abuse testing
Pregnancy testing
It has been observed that participants in clinical trials are disproportionately white.Often, minorities are not informed about clinical trials. One recent systematic review of the literature found that
race/ethnicity as well as sex were not well-represented nor at times
even tracked as participants in a large number of clinical trials of
hearing loss management in adults. This may reduce the validity of findings in respect of non-white patients by not adequately representing the larger populations.
Locating trials
Depending
on the kind of participants required, sponsors of clinical trials, or
contract research organizations working on their behalf, try to find
sites with qualified personnel as well as access to patients who could
participate in the trial. Working with those sites, they may use various
recruitment strategies, including patient databases, newspaper and
radio advertisements, flyers, posters in places the patients might go
(such as doctor's offices), and personal recruitment of patients by
investigators.
Volunteers with specific conditions or diseases have additional
online resources to help them locate clinical trials. For example, the
Fox Trial Finder connects Parkinson's disease trials around the world to volunteers who have a specific set of criteria such as location, age, and symptoms. Other disease-specific services exist for volunteers to find trials related to their condition. Volunteers may search directly on ClinicalTrials.gov to locate trials using a registry run by the U.S. National Institutes of Health and National Library of Medicine.
There also is software that allows clinicians to find trial options for
an individual patient based on data such as genomic data.
Research
Eli Lilly pharmaceutical company recruiting participants at the Indiana State Fair
The risk information seeking and processing (RISP) model analyzes
social implications that affect attitudes and decision making pertaining
to clinical trials. People who hold a higher stake or interest in the treatment provided in
a clinical trial showed a greater likelihood of seeking information
about clinical trials. Cancer patients reported more optimistic
attitudes towards clinical trials than the general population. Having a
more optimistic outlook on clinical trials also leads to greater
likelihood of enrolling.
Matching
Matching
involves a systematic comparison of a patient's clinical and
demographic information against the eligibility criteria of various
trials. Methods include:
Manual: Healthcare providers or clinical trial coordinators
manually review patient records and available trial criteria to identify
potential matches. This might also include manually searching in clinical trial databases.
Electronic health records
(EHR). Some systems integrate with EHRs to automatically flag patients
that may be eligible for trials based on their medical data. These
systems may leverage machine learning, artificial intelligence or precision medicine methods to more effectively match patients to trials. These methods are faced with the challenge of overcoming the limitations of EHR records such as omissions and logging errors.
Direct-to-patient services: Resources are specialized to support
patients in finding clinical trials through online platforms, hotlines,
and personalized support.
Decentralized trials
Although
trials are commonly conducted at major medical centers, some
participants are excluded due to the distance and expenses required for
travel, leading to hardship, disadvantage, and inequity for
participants, especially those in rural and underserved communities.
Therefore, the concept of a "decentralized clinical trial" that
minimizes or eliminates the need for patients to travel to sites, is now more widespread, a capability improved by telehealth and wearable technologies.
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