AGGREGATE REPORTING IN PHARMACOVIGILANCE

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Aggregate reporting in pharmacovigilance refers to the process of collecting and analyzing data from multiple sources, such as clinical trials, post-marketing surveillance, and spontaneous adverse event reporting, to identify patterns or trends in the safety of a drug or medical product. The goal of aggregate reporting is to provide a comprehensive and accurate overview of the safety profile of a drug or medical product, and to identify any potential safety concerns. Aggregate reports are typically required by regulatory authorities as part of the pharmacovigilance requirements for drug and medical product approval and post-marketing surveillance. These reports are also used by manufacturers to monitor the safety of their products and to make decisions regarding product labeling and risk management. The most common types of aggregate reports in pharmacovigilance include periodic safety update reports (PSURs), which provide a comprehensive overview of the safety profile of a drug or medical product over a specified time period, and signal detection reports, which identify potential safety signals or concerns based on analysis of adverse event data. The process of aggregate reporting typically involves the collection and analysis of data from multiple sources, including clinical trials, post-marketing surveillance, and spontaneous adverse event reporting. This data is then analyzed using statistical methods to identify patterns or trends in the safety of the drug or medical product. The results of this analysis are then compiled into a comprehensive report, which includes a summary of the safety profile of the drug or medical product, any identified safety concerns, and recommendations for further monitoring or risk management.

Healthcare

Welcome
AGGREGATE REPORTING IN PHARMACOVIGILANCE
RUKHAYYA
PHARM.D
CSRPL_STD_IND_HYD_ONL/CL
S_014/012023
5/5/2023
www.clinosol.com | follow us on social media
@clinosolresearch
1

Index
• INTRODUCTION
• IMPORTANCE OFAGGREGATE REPORTING
• TYPES OF AGGREGATE REPORTING
• KEY TERMINOLOGIES AND SUBMISSION SCHEDULES
• VALUE CHAIN AND ACTIVITIES
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IMPORTANCE OF AGGREGATE REPORTING
Why aggregate reporting is important?
Though the Individual case safety reports were submitted on
expedited basis to regulatory authorities, detailed analysis
and evaluation of benefit/risk ratio of a drug is not possible
at this level. Therefore periodically reviewing safety reports
received cumulatively worldwide, becomes highly significant
to analyze the benefit/risk balance of the product. These
reports need special diligence and attention to detail on the
one hand, overview and a sense of what is essential on the
other hand.
Assessment Aims
Standardized Balanced benefit-risk assessment
• Authorization or Renewal
• Relate safety evaluation with exposure
• Identify New safety concerns
• Changes to the RSI
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TYPES OF AGGREGATE REPORTS:
• Types of aggregate reports:
• Pre-marketing report:
• IND annual reports
• Clinical study reports (CSR)
• Development Safety Update Report (DSUR)
• Annual safety reports (ASRs) in Europe
Post-marketing report:
• Periodic Benefit Risk Evaluation Report (PBRER)/Periodic Safety Update Report(PSUR)
• Periodic Adverse Drug Experience Report (PADER)
.• NDA and ANDA annual reports
• Addendum to clinical overviews (ACO)
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KEY TERMINOLOGIES AND SUBMISSION
SCHEDULES
Development International Birth Date(DIBD) - The date
authorization is obtained to conduct clinical trials in any
country
• International Birth date (IBD) - The date of the first
marketing authorization, the EU birth date is the date of the
first authorization in Europe
• Data Lock Point (DLP)- The cut off date for data to be
included in theDSUR
• Reference Safety Information (RSI) -A document
containing a cumulative list of all the adverse events
observed.
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VALUE CHAIN AND ACTIVITIES
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Thank You!
www.clinosol.com
(India | Canada)
9121151622/623/624
info@clinosol.com
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@clinosolresearch
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Precision medicine, with its focus on tailoring medical interventions to individual characteristics, benefits significantly from the integration of machine learning (ML) algorithms for predictive analytics. These algorithms analyze complex datasets, identify patterns, and generate predictions that inform personalized treatment strategies. This article explores the diverse applications of ML in precision medicine, highlighting the key algorithms driving predictive analytics in this transformative field.

Innovations in Liquid Biopsies for Precision Cancer Diagnosis

ClinosolIndia

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