Clinical Trial and Observational Studies

1. Clinical Trial Design
By :
Harshita Sharma
Ritika

2. Contents
• Introduction
• Need of Clinical trial design
• Designing clinical Trial
• Types Of Designs
• Uncontrolled Trials
• Controlled Trials
• Randomized Control Trials
• Adaptive Design
• Non-Randomized Trials
• Considerations And Choice
• Various Key Documents
• References

3. Clinical Trial Design
• The delivery of an intervention whether drug, a dietary change, a
lifestyle change, or a psychological therapy session counts as an
intervention and hence must be dealt as a clinical trial.
• Clinical trial design is an important aspect of interventional trials that
serves to optimize, ergonomize and economize the clinical trial conduct.
• The purpose of the clinical trial is assessment of efficacy, safety, or risk
benefit ratio. Goal may be superiority, non inferiority, or equivalence.
‑
• A well conducted study with a good design based on a robust
‑
hypothesis evolved from clinical practice goes a long way in facilitating
the implementation of the best tenets of evidence based practice.
‑

4. Need Of Clinical Trial Design
• Clinical trials are a fundamental component of medical research and serve
as the main route to obtain evidence of the safety and efficacy of a
treatment before its approval.
• Properly designed clinical trials ensure that patients are treated safely and
that the scientific objectives of the trial can be achieved in an efficient
manner, so that current and future patients can benefit from the trial
results.
• Judicious use of important trial design elements, such as interim monitoring
and the choice of appropriate end points, can ensure that trials definitively
answer their scientific objectives as quickly as possible, be that changing
clinical practice or screening a new treatment for further development.

5. DESIGNING CLINICAL TRIAL
• Process of designing and carrying out clinical research can be divided mainly into
two parts:
• The first part is to deal with processes required in planning the study before data
collection begins.
• The second part deals with the execution steps carried out in data collection,
analysis, and publication.
• Ideally, the clinical investigator should be aware of and address all of these steps
in the design phase to ensure the feasibility and success of the clinical trial
project.
Planning Execution

6. Planning Steps
Develop Hypothesis for Research
• A strong research hypothesis addresses a significant question in the field. It should be
based on experience, literature review, and expert discussions. The hypothesis must
drive the study, not just existing methods or data.
Define the Objectives and Establish Priorities
• Clearly listing and prioritizing objectives ensures focus and resource efficiency. Writing
objectives helps avoid confusion and prevents overloading the study. Fewer, well-
defined objectives lead to more conclusive results.
Define the Variables Needed
• Identifying key variables (dependent, independent, and extraneous) structures the
study. Properly defining variables ensures accurate measurement and analysis. Clear
variable categorization improves data quality and study outcomes.

7. Define the Study Population
• The study population should represent the target group for valid results. Inclusion and exclusion criteria
must be precise to maintain study integrity. Proper selection ensures findings can be generalized to a
broader audience.
Finalize the Objectives into Testable Hypothesis
• Objectives must be refined into a testable hypothesis for statistical analysis. Null and alternative
hypotheses define expected variable relationships. A structured hypothesis strengthens research clarity
and direction.
Predict Error and Bias
• Bias and errors can distort study findings and must be anticipated. Randomization and blinding help
reduce selection, information, and confounding biases. Controlling bias ensures accurate, credible
research results.
Selection of Appropriate Study Design
• The study design must align with research objectives and resources. Common designs include
descriptive, observational, analytical, and experimental. A well-chosen design enhances study validity
and reliability.
Determination of Sample Size
• An optimal sample size balances accuracy and resource constraints. Too small a sample risks statistical
errors, while too large increases costs. Consulting a statistician helps determine the right sample size.

8. Execution Steps
Data Collection Process
• Accurate data collection ensures reliable measurements and study validity. Pre-testing tools and
validation against a "gold standard" improve accuracy. Structured data forms minimize errors and
enhance consistency.
Data Entry and Management
• Using statistical software ensures correct data entry and minimizes errors. Regular validation and
monitoring prevent misclassification or inconsistencies. Collaboration with statisticians improves
data structure and usability.
Statistical Analysis and Interpretation
• Choosing the right statistical test depends on variable types and study design. Analyzing data with
appropriate statistical methods ensures valid conclusions. P-values and confidence intervals
determine result significance.
Publication
• Publishing research in scientific journals ensures knowledge dissemination. Adhering to journal
guidelines and structuring content increases acceptance. A well-written paper enhances
credibility and research impact.

9. Types Of Clinical Trial Design

10. Uncontrolled Trials
• This design incorporates no control arm. It is usually
utilized to determine pharmacokinetic properties of a
new drug (Phase 1 trials).
• Uncontrolled trials are known to produce greater mean
effect estimates than a controlled trial, thereby
inflating the expectations from the intervention.
• There is a threat of inherent bias and results are
considered less valid than RCT.
• Another issue is use of this design in spontaneously
resolving maladies that might again overstate the
effect.
EXAMPLE :
In immunotherapy in warts, it is imperative to avoid an
uncontrolled study. Warts can be self resolving and hence
‑
the efficacy of immunotherapy as opposed to the
self resolution compromises the validity of the results
‑

11. Controlled Trials
a. Placebo Concurrent Control
Uses an inert substance resembling the active drug to differentiate true intervention effects from other factors.
Suitable when no effective treatment exists and for minimal risk, short-term studies. Unethical if delaying
treatment causes permanent harm.
b. “No Treatment” Concurrent Control
No intervention in the control arm. Requires objective endpoints but risks observer bias and difficulty in
blinding.
c. Active Treatment Concurrent Control
Compares a new drug to a standard drug or a combination therapy. Demonstrates equivalence, non-inferiority,
or superiority. Ethical when approved drugs exist, as per the Declaration of Helsinki.
d. Dose-Comparison Concurrent Control
Different doses of the same treatment are compared to assess dose-response relationships. May include active
and placebo groups. Inefficient if the drug's therapeutic range is unknown.
e. Historical Control (External & Non-Concurrent)
Uses past patient data or prior standard treatments as controls. Useful for rare conditions but lacks
randomization and blinding. Differences in baseline characteristics and evolving co-interventions limit
comparability.

12. Randomized Clinical Trials (RCT)
• In randomized controlled trials, trial participants are
randomly assigned to either treatment or control arms. The
process of randomly assigning a trial participant to treatment
or control arms is called “randomization”.
• Different tools can be used to randomize (closed envelopes,
computer generated sequences, random numbers).
• There are two components to randomization: the generation
of a random sequence and the implementation of that
random sequence, ideally in a way that keeps participants
unaware of the sequence (allocation concealment).
• Randomization removes potential for systematic error or bias.
The biggest upside of an RCT is the balancing of both the
known and unknown confounding factors which leads to
wrong conclusions.

13. Types Of RCT Designs
Parallel Group Trial Design –
• The most commonly used study
design where subjects are
randomized into separate study arms,
each receiving a different
intervention.
• Participants remain in their assigned
arm throughout the study. This
design allows simultaneous
experiments in multiple groups
across locations but requires
preventing contamination through
unplanned co-interventions or cross-
overs.
Cross-Over Design –
• Each patient receives both interventions in a
randomized order, serving as their own control.
• Requires a smaller sample size and balances
covariates between treatment and control
arms.
• Requires a chronic, stable disease and non-
irreversible drug effects. Includes an adequate
washout period before switching interventions.
• Used in bioequivalence and biosimilar studies
but has a longer follow-up duration and risk of
patient dropout, compromising study power.

14. Types Of RCT Designs
Factorial Design (2 × 2 Design) –
• Evaluates two or more interventions in various
combinations within a single study, reducing
sample size by almost 50%.
• Patients are divided into four groups: (i)
treatment A + placebo, (ii) treatment B +
placebo, (iii) both treatments A and B, and (iv)
placebo only.
• Not suited for rare diseases with possible
treatment interactions.
• Limitations include complex protocols, statistical
challenges, and difficulty in recruitment.
• Incomplete factorial designs exclude the
placebo-only arm when non-intervention is
unethical.
Randomized Withdrawal Design
(Enrichment Enrollment Randomized
Withdrawal – EERW) –
• Begins with an open-label phase where all participants
receive the intervention. Non-responders are dropped, and
responders are randomized to either continue treatment
or switch to placebo.
• The outcome is usually symptom relapse. Increases
statistical power, reduces placebo exposure, and
determines optimal treatment duration.
• Ethical advantages include ensuring minimal time on
placebo.
• Limitations include missing data due to withdrawals,
carryover effects, restricted external validity, and
overestimation of treatment effects.
• Only suitable for chronic, stable diseases with an
appropriate enrichment phase duration.

15. Limitations of RCT
• Randomized clinical trials serve as the standard for clinical research and have contributed
immensely to advances in patient care.
• Nevertheless, several shortcomings of randomized clinical trials have been noted, including the need
for a large sample size and long study duration, the lack of power to evaluate efficacy overall or in
important subgroups, and cost.
• These and other limitations have been widely acknowledged as limiting medical innovation.
Adaptive trial design has been proposed as a means to increase the efficiency of randomized clinical
trials, potentially benefiting trial participants and future patients while reducing costs and
enhancing the likelihood of finding a true benefit, if one exists, of the therapy being studied.
Standard Trials: Traditionally, clinical trials have been run in three steps:
• 1. The trial is designed. 2. The trial is conducted as prescribed by the design. 3. Once the data are
ready, they are analysed according to a pre-specified analysis plan
This practice is straightforward, but clearly inflexible as it does not include options for changes that
may become desirable or necessary during the course of the trial.

16. Adaptive Clinical Trial
• Adaptive designs (ADs) provide an alternative. They have been described as
‘planning to be flexible’ , ‘driving with one’s eyes open’ or ‘taking out insurance’
against assumptions. They add a review–adapt loop to the linear design–
conduct–analysis sequence.
• Adaptive designs are applicable to both exploratory and confirmatory clinical
trials. Adaptive designs for exploratory clinical trials deal mainly with finding safe
and effective doses or with dose–response modeling.
• The emphasis is on strategies that will assign a larger proportion of the
participants to treatment groups that are performing well, reduce the number of
participants in treatment groups that are performing poorly, and investigate a
dose range that is larger than ranges in corresponding trials with nonadaptive
designs, in order to select effective doses for the confirmatory stage of
investigation.

19. Non-Randomized Control Trial
A non-randomized clinical trial (NRCT) is a type of study where participants are allocated to
different intervention groups without randomization. Instead, assignment may be based on
factors such as physician discretion, patient choice, or predefined criteria (Harris et al., 2006).
Key Characteristics of NRCTs
1.Absence of Randomization – Participants are assigned to groups using non-random methods,
which can introduce selection bias (Reeves et al., 2017).
2.Higher Risk of Bias – Since patients are not randomly assigned, differences in baseline
characteristics may influence the results, requiring careful statistical adjustments (Sedgwick,
2014).
3.More Feasible Than RCTs – NRCTs are often more practical when randomization is not
possible due to ethical or logistical concerns (Concato et al., 2000).
4.Comparative Effectiveness – These trials are commonly used in real-world settings to assess
the effectiveness of new interventions compared to standard care (Anglemyer et al., 2014).

20. Types of NRCTs
•Quasi-Experimental Studies – Groups are assigned based on
convenience or other non-random criteria.
•Cohort Studies – Patients receiving an intervention are compared with a
control group, either prospectively or retrospectively.
•Before-and-After Studies – Outcomes are measured before and after an
intervention in the same group of patients.
•Case-Control Studies – Individuals with a condition (cases) are compared
to those without it (controls) to identify potential effects of an intervention.

21. Advantages Limitations
•Ethical Feasibility – Useful
when randomization is impractical
or unethical, such as in palliative
care or cancer research.
•Real-World Applicability –
Findings may be more
generalizable to clinical practice
than RCTs.
•Lower Cost & Faster
Execution – Less resource-
intensive than RCTs
•Selection Bias – Differences
between groups may influence
outcomes.
•Confounding Variables – Other
factors may contribute to the
observed effects, making causal
inference difficult.
•Limited Internal Validity –
Compared to RCTs, NRCTs
provide weaker evidence for
causality.

22. Considerations And Choice
The design and conduct of any type of clinical
trial requires three important considerations:
1. Study must examine valuable and important
biomedical research questions
2. It must be designed and based on a rigorous
methodology that can answer a specific
research question and
3. Must be based on a set of strong ethical
principles to minimize the risk to trial
participants.
The choice of an appropriate study design depends on
the following factors and considerations:
i. Ability of study design to answer the primary research
question
ii. Whether the trial is studying a potential new treatment for a
condition for which an established, effective treatment already
exists
iii. Whether the disease for which new treatment is sought is
severe or life threatening
iv. The probability and magnitude of risk to the participants
v. The probability and magnitude of likely benefit to the
participant
vi. The population to be studied - its size, availability and
accessibility. Because the choice of study design for any
particular trial will depend on these

23. Various Key Documents
• In clinical research, adherence to Good Clinical Practice (GCP) guidelines is essential to
ensure the safety, rights, and well-being of participants, as well as the credibility of data.
Several key documents and ethical codes guide the conduct of clinical trials, particularly in
the context of Indian regulations.
1. Good Clinical Practice (GCP) Guidelines:
• International Council for Harmonisation (ICH) GCP Guidelines: The ICH E6(R2) guideline
provides a unified standard for designing, conducting, recording, and reporting clinical
trials involving human subjects. Compliance ensures that the rights, safety, and well-being
of trial participants are protected, and that the clinical trial data are credible.
• Indian GCP Guidelines (CDSCO Guidelines): The Central Drugs Standard Control
Organization (CDSCO) has established GCP guidelines tailored to the Indian context. These
guidelines align with international standards while addressing local regulatory
requirements and ethical considerations.

24. 2. New Drug Application (NDA), Abbreviated New Drug Application
(ANDA), and Marketing Authorization Application (MAA):
• NDA: A comprehensive document submitted to regulatory authorities
seeking approval to market a new pharmaceutical product. It includes
data from preclinical and clinical studies demonstrating the drug's
safety and efficacy.
• ANDA: An application for the approval of a generic drug, demonstrating
that it is bioequivalent to a previously approved brand-name drug.
• MAA: A submission to regulatory agencies in regions like the European
Union, seeking authorization to market a new medicinal product.

25. 3. Ethical Guidelines:
• ICMR's National Ethical Guidelines for Biomedical and Health Research
Involving Human Participants: Developed by the Indian Council of Medical
Research (ICMR), these guidelines provide a framework for the ethical conduct
of biomedical and health research in India. They emphasize principles such as
respect for persons, beneficence, non-maleficence, and justice.
• Schedule Y: Part of the Drugs and Cosmetics Rules in India, Schedule Y outlines
the requirements for clinical trials, including permissions, responsibilities, and
documentation necessary for conducting studies involving new drugs.
• Declaration of Helsinki: A set of ethical principles developed by the World
Medical Association to guide medical research involving human subjects. It
emphasizes the necessity of informed consent and the importance of
conducting research that benefits society.

26. Observational Studies in Clinical Research
and Pharmacovigilance
Understanding Their Role, Types, and Impact

27. Source: https://lo.unisa.edu.au/mod/book/view.php?id=646428

28. Use medical products(Drugs, Devices)
Compare a new treatment to an
existing treatment /placebo
Find out if the new treatment is
helpful, harmful or not different from
available
Interventional VS Observational
No Intervention
Compare and observe groups that
already exists without influencing
them
Aim to get more information about
populations, diseases or behaviour

29. What are Observational Studies:
A type of study in which individuals are observed
or certain outcomes are measured. No attempt is
made to affect the outcome (for example, no
treatment is given).

30. Efficacy study (clinical
trials)
Effectiveness study
(observational studies)
Question Does the intervention work
under ideal circumstances?
Does the intervention work
in real-life practice?
Setting Resource-intensive ‘ideal
setting’
Real-life everyday clinical
setting
Population Highly selected,
homogeneous population;
several exclusion criteria
Heterogeneous population;
few to no exclusion criteria
Providers Highly experienced and
trained
Representative usual
providers
Intervention Strictly enforced and
standardized; no
concurrent interventions
Applied with flexibility;
concurrent interventions
and cross-over permitted

31. Importance in Clinical Research and Pharmacovigilance
 Higher External Validity: More representative of the general patient
population than RCTs.
 Large Sample Size: Enables inclusion of diverse patient groups,
including those underrepresented in RCTs.
 Effectiveness in General Population: Provides real-world evidence on
how new therapies perform in routine clinical practice.
 Identification of Treatment Toxicity: Highlights potential adverse
effects that may not be evident in controlled RCT environments.

32.  Bridging the Gap Between RCTs and Clinical Practice: Helps assess
the real-world applicability of RCT findings.
 Guiding Physician Decision-Making: Addresses physician reluctance
to adopt new treatments without real-world data.
 Policy and Healthcare Improvements: Helps policymakers evaluate
and refine treatment strategies for better patient outcomes.
 Addressing Unanswered Clinical Questions: Provides insights into
treatment benefits and risks in situations where RCTs are not feasible.

33. Role of Observational Studies in Clinical Research
• Long-Term Treatment Insights: Provide data on long-term outcomes,
pattern of diseases, toxicity, adherence, and treatment switching in real-
world settings.
• Age and Patient Demographics: Highlight differences in age distribution
between trial participants and general patient populations.
• Treatment Adherence and Discontinuation: Reveal factors influencing
adherence and the impact of side effects on treatment continuation.
• Comparative Outcomes: Show disparities between clinical trial results and
real-world patient responses.

34. •Identification of Unmet Needs: Help detect gaps in monitoring, such as inadequate
response assessments and treatment adjustments.
•Safety and Toxicity Assessment: Investigate long-term and late-onset adverse
effects of therapies.
•Healthcare Disparities and Socioeconomic Factors: Uncover variations in access to
treatment, survival rates, and adherence across different populations and regions.
•Real-World Effectiveness: Assess how treatments perform outside the controlled
environment of RCTs.
•Impact of Socioeconomic and Geographic Factors: Examine how factors like
infrastructure, education, and political climate influence patient outcomes.

35. Types of Observational Studies
A. Cohort Study
B. Case- Control Study
C. Cross- Sectional Study
D. Ecological Study

36. •Cohort Studies: A cohort study is a type of epidemiological study in which a
group of people with a common characteristic is followed over time to find
how many reach a certain health outcome of interest (disease, condition,
event, death, or a change in health status or behavior).
•A cohort is defined as a group of persons, usually 100 or more in size, who
share a common characteristic, e.g. smokers, workers in a lead smelter, people
born in the same year etc.
•Example: Studying long-term effects of a drug on patients
A.) Cohort Studies

37. Types of Cohort Studies
1.) Prospective/Concurrent Cohort: . When the baseline exposure is assessed at
the beginning of the study and the cohort is followed into the future is a
prospective cohort study.
2.) Retrospective/Historical Cohort: When the baseline exposure is assessed at
some point in the past through historical records, e.g. health records for a cohort of
factory workers may provide exposure and outcome information up to the present.

38. 3.) Case - Control nested with a cohort: A smaller
group is chosen for deeper look, it includes genotyping,
collection tissue sample and many other factors
4.) Case - Cohort: Its similar to case control but the
participants are evaluated for the risk outcomes at any
time before the first outcome.
10.15406/bbij.2017.05.00124
Source:

39. Source: https://deakin.libguides.com/quantitative-study-designs/cohortstudies

40. Steps of cohort study
1. Establishing the cohort
2. Following the cohort
3. Evaluating the result

41. A. Establishing the cohort
• A cohort study can be based on age, location, exposure to a certain
working environment, or some other common characteristic as
chosen by the investigator. For e.g. smokers vs. nonsmokers.
• Identification of individual in baseline for their exposures of interest
(through interviews, questionnaires, bioassays, medical records, etc.).
• Subjects with the outcome of interest at baseline are excluded.

42. B. Following the cohort
• The cohort is then followed over time for new occurrences of the
outcome. Observations are recorded.
C. Evaluation of the results
Risk (also called Cumulative
Incidence or Incidence Proportion)
The risk ratio can be calculated , which gives a relative measure
of the increase or decrease in incidence between the exposed
and unexposed groups.
= new occurrences of the outcome /
population-at-risk at baseline

43. Formulas for Rates and difference calculation
So exposure may be a risk factor or preventive factor in the
development of the outcome of interest. When exposure is
preventive , the risk ratio or rate ratio will be less then one.
Concluding cohort studies , they are found to be helpful for
establishing cause and effect relationship.

44. Example:

45. B.) Case-Control Studies
•In case-control studies the patient with
disease is questioned and examined, based
on that conclusions are drawn to reveal
characteristics or factors that predisposed
the patient to the disease.
•Example: Investigating rare adverse effects
of a drug
Source: https://deakin.libguides.com/quantitative-study-designs/cohortstudies

46. Design of Case control Study
1. Selection of Case: A Case person in the population or study group identified
having a particular health condition. The Selection of cases must be random.
2. Selection of control: A Control is healthy individual for comparison with case,
Controls must be ideally matching with the cases by various attributes taken to
study such as age, sex, race etc. A control should be take from hospital, general
population, family and random to reduce biasness.
3. Observation
4. Analysis

47. Interpretation : Smokers having 4 times higher chance to develop lung cancer
when compared with non smokers

48. C.) Cross Sectional Study
Cross – Sectional studies are
observational studies that analyse
data from a population at a single
point in time. They are often used
to measure the prevalence of
health outcomes, understand
determinants of health, and
describe features of population.
Source: https://microbenotes.com/cross-sectional-study/

49. Descriptive vs analytical studies
• Cross-sectional studies can be used for both analytical and
descriptive purposes:
• An analytical study tries to answer how or why a certain outcome
might occur.
• A descriptive study only summarizes said outcome using
descriptive statistics.

50. Design
1. The investigator measures both outcome and
exposure simultaneously.
2. Participants are selected based on predefined
inclusion and exclusion criteria.
3. Comparison with other study designs:
4. Case–control studies: Participants are selected
based on outcome status.
5. Cohort studies: Participants are selected based
on exposure status.
6. Study process: After participant selection, the
investigator assesses both exposure and outcome.
7. The investigator can analyze associations between
variables.
Source: https://doi.org/10.4103/0019-5154.182410

52. Source: https://doi.org/10.4103/0019-5154.182410

53. Ecological study
• Ecologic studies are studies in which
the unit of observation is a group, not
separate individuals, for one or more
study variables. For example, exposure
and risk factors are known only at the
group level, such as the average air
pollution concentration in different
cities. Source: https://www.researchgate.net/figure/Community-and-cellular-ecology-Classically-ecological-studie
consider-interactions-at_fig1_284797101

54. Types
A.) Geographical: This type of study compares one geography with another by
assessing the health of the population of each. Exposures for geographies may also be
measured and included in analysis as well as other potential confounding variables
such as demographic and socioeconomic information.
B.) Longitudinal: A population is monitored to assess changes in disease over time.
Again, confounding factors are often included in analysis.
C.) Migration: Data of migrant populations are collected and analyzed. The unit of
interest is neither time nor place, but population type.

55. D.) Cross-sectional ecologic studies
Compare aggregate exposures and outcomes over the same time period.
Example: Comparing bladder cancer mortality rates in cities with different
drinking water sources.
E.) Time-trend ecologic studies
Compare variations in aggregate exposures and outcomes over time within
the same community.
Example: Investigating whether hospital admissions for cardiac disease in
Los Angeles increase on high carbon monoxide days.
F.) Solely descriptive ecologic studies
Investigate disease or risk factor differences:
Between communities at the same time.
Within the same community over time.

56. Role of Observational Studies in Pharmacovigilance
•Post-Marketing Surveillance (PMS): The major causative drug groups
were antimicrobials (45.46%), nonsteroidal anti-inflammatory drugs
(NSAIDs) (20.87%) and anti-epileptic drugs (14.57%). Commonly
implicated drugs were sulfa (13.32%), β-lactams (8.96%) and
carbamazepine (6.65%).
•Detection of Adverse Drug Reactions (ADRs): The WHO defines Adverse
Drug Reactions (ADRs) as unintended, harmful effects of drugs at normal
doses. ADRs contribute significantly to morbidity and mortality worldwide.

57. •Real-world Safety & Effectiveness Monitoring
•Examples: Rofecoxib (Vioxx) withdrawal ,it revealed an increased relative risk
for serious cardiovascular events, including heart attacks and strokes, beginning
after 18 months of treatment among patients taking rofecoxib that was about
twice that of patients taking placebo. The results for the first 18 months of the
study did not show any increased risk.

58. Regulatory Guidelines and Ethical Considerations
1.) ICH-GCP & WHO Guidelines
• ICH-GCP Guidelines
• Ensure ethical integrity and scientific rigor in clinical research.
• Emphasize participant rights, safety, and confidentiality.
• Require informed consent for observational studies involving patient
data.
• Define responsibilities of investigators, sponsors, and regulatory
authorities in ADR reporting.
• WHO Guidelines on Pharmacovigilance
• Advocate for robust ADR monitoring and reporting systems globally.
• Encourage healthcare professionals and patients to report ADRs.
• Provide recommendations for risk assessment and mitigation.

59. 2.) GDPR & Patient Data Privacy
• GDPR Principles in Pharmacovigilance
• Lawful Processing: ADR data collection must have a legitimate basis, such
as patient consent or legal obligations.
• Data Minimization: Only essential patient information should be collected.
• Anonymization & Confidentiality: Personal identifiers should be removed
unless necessary.
• Right to Access & Erasure: Patients have the right to access and request
deletion of their data.
• Impact on Pharmacovigilance
• Companies and healthcare institutions must implement secure data storage
and processing measures.
• Transparency in data collection for ADR monitoring is essential to maintain
public trust.

60. 3.) Ethical Issues in Observational Research
• Informed Consent:
• Even though observational studies may not involve direct treatment
interventions, participants must be informed about data collection and usage.
• Confidentiality & Data Protection
• Vulnerable Populations:
• Special ethical considerations apply when including children, elderly patients, or
individuals with cognitive impairments in pharmacovigilance studies.

61. Conclusion
Observational studies are vital for pharmacovigilance but face
challenges like selection bias, lack of randomization, and data
limitations. While these issues impact reliability, advanced statistical
methods and improved reporting can enhance accuracy. Despite
limitations, they remain essential for assessing drug safety and
improving patient outcomes.

62. References – Part 1
• Fundamentals of Clinical Trials, 4th
Edition
• Basic Principles of Clinical Research and Methodology, SK Gupta
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• https://pmc.ncbi.nlm.nih.gov/articles/PMC5372399/

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