types of clinical study designs

1. TYPES OF
CLINICAL
STUDY DESIGNS
BY:-VIKAS AAGRAHARI
PHARM-D 4TH YR

2. Introduction
Clinical study types and designs are terms which represent the way in which
clinical trials are structured and formulated.
Since we all know that clinical research is an extremely complex topic and not everything
can be explained in a simple way, here we’ll focus only on some of the most basic types
of clinical study types and designs which involve human subjects or participants.
First of all, you should know that the most basic grouping of study designs is
experimental (treatment) studies and observational studies.
As we can suppose from the names, in an observational study, researchers have less
control over subjects and they’re just observing what happens to subjects, while in
experimental studies, researchers are using different methods (such as randomization)
to place subjects in separate groups. This gives experimental studies much more
validity than observational studies.
In this guide, we’ll talk about the 2 possible types of studies, as well as
different study designs within.
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3. • Types of Studies:
• 1:-Parallel
• 2:-Crossover
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4. Parallel Study
For a better and simplified explanation, let’s imagine we have two groups of patients -
GROUP 1 and GROUP 2, and two different treatments - TREATMENT A and
TREATMENT B.
In a parallel study, the structure is as follows:
TreatmentA
Treatment B
Group 1
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Group 2

5. Parallel Study
Throughout the whole duration of the study, GROUP 1 will receive only TREATMENT
A, and GROUP 2 will receive only TREATMENT B! None of the groups will receive any
other treatment but the one they were given at the beginning of the study!
TREATMENT A and TREATMENT
B
can either be two different active
drugs, or one active drug and one
placebo, or even two different
doses of the same drug. In any
case, if the first group started
with placebo, they will continue
with only placebo and nothing
else! Parallel studies are also
called non-crossover studies.
- progressive diseases;
- life-threatening conditions;
- acute conditions;
- ‘’Carry-over’’ treatments;
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- harder to enroll;
- needs more patients;

6. Crossover Study
For a better and simplified explanation, let’s imagine we have two groups of patients -
GROUP 1 and GROUP 2, and two different treatments - TREATMENT A and
TREATMENT B.
In a crossover study, the structure is as follows:
TreatmentA
Treatment B
Group 1
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Group 2

7. Crossover Study
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Contrary to parallel studies, in a crossover study, GROUP 1 might start with
TREATMENT A but then at a certain point be given TREATMENT B, while GROUP 2
might start with TREATMENT B but then be given TREATMENT A.
In between two different treatments, there’s usually a so-called wash-out period, in order to avoid a
‘’carryover effect’’.
So, in crossover studies, a study subject (participant) will be given a number of different treatments (at least
two). That’s why it’s called a crossover study - GROUP 1 that starts with TREATMENT A crosses to
TREATMENT B. This means that each subject will serve as both the treatment and the control group!
Concerning the IP (investigational product or drug), the same applies as with parallel studies. One
treatment might be the actual active drug while the other can be a placebo, and there can also be a third
treatment (another active drug that will serve for comparison).

8. Crossover Study
Crossover studies are beneficial for some conditions while not suitable for others. Below, you’ll be
able to see the benefits and warnings of crossover studies.
- chronic conditions;
- controlled conditions;
- non-life-threatening conditions;
- Phase I and II Studies;
- easier to enroll;
- needs less patients;
- progressive diseases;
- life-threatening conditions;
- acute conditions;
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9. Study Designs

10. Study Designs
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Meta-analysis
Randomized controlled trial (RCT)
Cohort study
Case-control study
Case series
Cross-sectional
Designs according to
their data validity, from
the lowest up to the
highest

11. Meta-analysis
This type of study is conducted with the aim to gain a better and closer estimate to the reality. We all know
that every study design can have a certain error, which is why meta-analysis combines these multiple
studies together, in order to draw a better and more accurate conclusion.
Even though a meta-analysis can easily be ranked the highest on a validity scale, this doesn’t mean that there
isn’t any space for errors. After all, meta-analysis combines multiple studies together, so if those studies have
a lot of errors individually, then the meta-analysis will also have errors.
Meta-analysis is actually a statistical process which
takes and combines the results of various different
individual studies in order to reach a single conclusion.
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12. 12
Randomized-controlled trial (RCT)
RCT is nowadays the ‘’gold standard’’ of experimental (treatment)
studies. RCTs are considered to have high validity because of the
fact that they’re experimental and controlled studies which means
that it’s much easier to isolate separate circumstances and come
to a better (more valid) conclusion. These studies include
randomization and double-blind, which gives even more validity
to the RCT study design.
The process of randomization which makes these studies so
good means to randomly place subjects to one of two (or more)
groups. One of these groups will receive the IP (investigational
product), while the other will receive placebo (or a different
mainstream treatment). This process minimizes selection bias.
The point of such studies is to compare the outcomes and results
of the IP group with the control group.
Experimental
Controlled
Randomized

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Cohort Study
A cohort study is basically following a group of similar people that
have certain differing factors. These people will all have similar
features, but some of them will have exposure to certain factors (or
be affected by a condition) and some won’t. So researchers will
follow this group of people over time and then compare the results
and determine how certain factors affected the subjects.
Cohort studies can be prospective (what we explained above) and
retrospective - the opposite. In retrospective cohort studies,
researchers compare the past records of two similar groups of
people who differ by some characteristics.
An example for a cohort study would be a group of female doctors,
half of whom are smokers and the other half non- smokers, or a
group of middle-aged truck drivers, some of which are smokers and
some non-smokers.

14. Case-control Study
Case-control studies are the opposite of cohort studies. In this
type of studies, the researchers begin with the outcome. This
means that first, they find a group of participants affected by a
certain condition and next, they try to find a similar group of
people that share the same exposures and features with the
first group but are not affected by the condition (control
group).
To sum up, both groups have had the same exposure, but one
group was affected by it while the other one wasn’t. As
we can see, case-control studies are retrospective studies.
Exposure
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NO SIDE EFFECTS
SIDE EFFECTS

15. Case-series
A case series study design is again an observational study but
of a really small size that doesn’t entail a control group.
Basically, a case series is only reviewing the medical records
of a small number of individuals. This is all done in order to
see the outcomes of these patients. A case series study ranks
low on the validity scale.
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16. 16
Cross-sectional
DETERMINING PREVALENCE
In a cross-sectional study, researchers are trying to evaluate and measure the
prevalence of a specific exposure versus the prevalence of a specific health
outcome simultaneously (at the same time). In other words, they’re comparing
the number of people who are exposed with the number of people who are
affected by that exposure at one specific point. Even though this study is easy to
do and it doesn’t require a lot of resources, its validity is questioned because of
all the other factors that are involved. With this type of study, it’s really hard to
connect the exposure as the primary culprit of a health condition.
Even though these studies have a huge space for errors, they can be
useful in a more general situation.
For example, it can be easy to notice a city with huge prevalence of the risk
factor which also has a huge prevalence of people affected by the expected
health outcome. In this case, we can clearly see the connection between
the risk factor (exposure) and the health outcome.

17. CONCLUSION
As a final word, all of these clinical study types and designs have
their own place in the clinical research world. Even though one study
design might not possess enough accuracy for a certain trial, it might
be good for another type of trial. The way in which study types and
designs are chosen depends on the nature of the study as well
as the desired outcomes. Finally, we hope that we’ve managed to
help you understand the difference between a parallel and a
crossover study, and gave you enough information to differentiate
study designs in a clear and simplified way. 17

18. Thank you!