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Real-World Data Approaches for Early Detection of Potential Safety and Effectiveness Signals for Generic Substitution: A Metoprolol Extended-Release Case Study.

Author: BrownJoshua D, HenriksenCarl, SchmidtStephan, VozmedianoValvanera

Journal ArticleAn article published in an academic or professional journal that reports original research or scholarly analysis.
Research Support, N.I.H., ExtramuralResearch funding provided by the NIH to external research institutions and researchers.

Overview

A multipronged approach, utilizing real-world spontaneous adverse event reports and administrative health care data, was used to monitor generic drug formulations for potential bioequivalence failures. Using metoprolol succinate extended release as a case example, the study identified increased adverse event reporting system signals related to product quality and clinical events potentially associated with high or low variability in drug levels. Compared to amlodipine-benazepril, metoprolol succinate had lower utilization, more prescriptions written as dispense as written, and higher switching and discontinuation rates. The 90-day period immediately after generic entry provided stronger signal capture. This framework can be implemented to actively monitor new generic formulations.
Paper Details　
Original Abstract of the Article :
Real-world spontaneous adverse event reports and administrative health care data were utilized as one part of a multipronged approach to verify surveillance signals related to generic drug formulations. This study used metoprolol succinate extended release as a historic case example from which to de...See full text at original site
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引用元：
https://doi.org/10.1002/jcph.1436

データ提供：米国国立医学図書館（NLM）

Real-World Data for Generic Drug Surveillance: A Case Study of Metoprolol Extended-Release

This study explores the use of real-world data to monitor the safety and effectiveness of generic drugs. The researchers utilized both spontaneous adverse event reports and administrative health care data to investigate the performance of generic metoprolol succinate extended-release, a medication used for treating hypertension. This study employed a [research methodology] approach to analyze real-world data and identify potential safety signals associated with generic drug formulations. The researchers discovered that generic metoprolol was associated with higher rates of certain adverse events and that the timing of generic entry appeared to influence the incidence of these events. The study concluded that utilizing real-world data can be valuable for actively monitoring generic formulations and identifying potential bioequivalence failures.

Real-World Data: A Hidden Oasis of Insights

This research is like discovering a hidden oasis of knowledge in the vast desert of generic drug surveillance. The study highlights the potential of real-world data to provide valuable insights into the safety and effectiveness of generic medications. This discovery offers a new path for monitoring generic drug formulations and ensuring their quality and effectiveness.

Navigating the Landscape of Generics: A Journey of Informed Decisions

Navigating the landscape of generic medications requires careful consideration and informed decision-making. This research underscores the importance of actively monitoring generic drug formulations and utilizing real-world data to identify potential issues. By embracing a data-driven approach, we can make more informed choices about the medications we take and ensure their safety and effectiveness. It's like discovering a hidden map in the desert of generic drug surveillance, guiding us towards better understanding and safer choices.

Dr.Camel's Conclusion

This study underscores the value of real-world data in monitoring generic drug formulations. The findings suggest that actively utilizing real-world data can provide valuable insights into potential bioequivalence failures and ensure the safety and effectiveness of generic medications. It's like discovering a hidden oasis of knowledge in the vast desert of pharmaceutical research, enabling us to make more informed decisions about the medications we take and ensure a safe and effective journey towards better health.
Date :
  1. Date Completed 2020-07-27
  2. Date Revised 2020-07-27
Further Info :

Pubmed ID

31087552

DOI: Digital Object Identifier

10.1002/jcph.1436

SNS
PICO Info
in preparation
Languages

English

Positive IndicatorAn AI analysis index that serves as a benchmark for how positive the results of the study are. Note that it is a benchmark and requires careful interpretation and consideration of different perspectives.

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