Signal detection and assessment in clinical trials are critical processes aimed at identifying potential safety concerns related to investigational drugs or medical interventions. During these trials, vast amounts of data are collected, and the challenge lies in distinguishing meaningful signals from background noise. Rigorous signal detection methods, often employing advanced statistical analyses and data mining techniques, are applied to detect patterns of adverse events or unexpected outcomes. Once signals are detected, they are meticulously assessed to determine their clinical relevance and potential causality. The evaluation involves examining factors such as temporal relationships, dose-response relationships, and consistency across studies. An effective signal detection and assessment process is essential for ensuring the safety and efficacy of new treatments, allowing researchers and regulatory authorities to take prompt actions when necessary, and ultimately, safeguarding the well-being of patients participating in clinical trials.

1. Dr. Pragya Prasanna
PhD
Student ID Here
10/18/2022
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Signal detection and their assessment
in clinical trials

2. Introduction
Signal detection in pharmacovigilance is the process of actively searching for and
identifying safety signals from a wide variety of data sources.
It is a vital and complex process and important aspect of pharmacovigilance which
ensures that the patients receive safe drugs.
It is mainly the detection of ADRs either from clinical trials data, or from post marketing
data.
At present, it is based on detecting type B adverse effects and unusual type A adverse
effects.
Signal assessment is mainly performed by using Upsala Monitoring scale & Naranjo
scale of probability to analyze the cause and effect analysis.
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3. Sources of Signal
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Sources
of
Signal
Clinical trials
Pre-clinical
studies
Case control
studies; cohort
studies;
Meta-analysis
Spontaneous
reporting;
Prescription
Event
monitoring

4. Signal detection:
• Spontaneous Reporting System
• Prescription Event Monitoring
• Registries (disease and drug registries)
• Periodic Safety Update Report (PSUR)
• Signal Generation by Trigger Tool
• Comparative Observational Studies
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5. Signal Assessment
• Quality Assessment
• Seriousness of Adverse Event
• Coding of Adverse Drug Reactions
• Collation
• Vigiflow (India)
• AERS (USA) (Adverse Event Reporting System)
• Eudravigilance (Europe)
• Canada Vigilance (Canada)
• Argus Safety Database
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Country wise data bases and adverse
drug reaction (ADR) form

7. CAUSE AND EFFECT ANALYSIS
• Several methods that can be used to make a causality assessment of
ADR reports are:
• Literature (9 points of consideration – Morges, Switzerland, 1981),
Probability calculation (Bayes’ Theorem).
• Aetiological – Diagnostic Systems (Bénchiou’s group method), French
• imputation systems, the European ABO Systems, the US Reasonable
Possibility Systems, the Naranjo’’s ADR Probability Scale, WHO
Causality Categories, Jones’ algorithm, Yale algorithm, Karch and
Lasagna algorithm, Begaud algorithm.
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8. WHO-UMC causality categories
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9. Naranjo’s classification criteria
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10. Title
• (Text here)
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11. Future perspectives
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❖ Active surveillance is necessary to receive information about the safety of the drugs at an
early stage.
❖ Develop new methods which are able to sort out questions like
1) Strength of causal relationship between the drug exposure and its outcomes with
greater clarity.
2) Methods able to gather information in a timely manner for active post-marketing
surveillance
❖ Identify new safety signals without delay.
❖ Concentrate on patient group as a major source of information. (Since, the patient is highly
informed about his disease and also wants to participate actively in his treatment)

12. ThankYou!
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