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Why Are We Still Creating Individual Case Safety Reports?

Mariette Boerstoel Streefland1

  • 1Alexion Pharmaceuticals, Inc..

Clinical Therapeutics
|November 14, 2018
PubMed
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Pharmacovigilance, or drug safety monitoring, has historically lagged behind other industries. Urgent changes are needed to adapt to new technologies and data availability.

Keywords:
adverse event reportingcase processingdrug safetydrug safety profilesindividual case safety reportsinformation technologypharmacovigilance

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Area of Science:

  • Pharmacovigilance and drug safety monitoring.
  • Health informatics and regulatory science.

Background:

  • Pharmacovigilance has historically been slow-moving and reactive.
  • The field's progress is hindered by a focus on administrative tasks and regulatory adherence for individual case safety reports (ICSRs).
  • Current pharmacovigilance practices are increasingly outdated in the face of technological advancements and data abundance.

Purpose of the Study:

  • To evaluate the continued relevance of traditional ICSR creation and distribution.
  • To explore the necessity for urgent and drastic changes in pharmacovigilance.
  • To assess the potential of artificial intelligence and machine learning in modernizing drug safety systems.

Main Methods:

  • The abstract does not specify methods but discusses the historical context and current challenges in pharmacovigilance.
  • It poses critical questions regarding the adaptability of existing processes.
  • It highlights the contrast between pharmacovigilance and other industries leveraging advanced technologies.

Main Results:

  • Pharmacovigilance is characterized by slow adaptation and a focus on administrative processes.
  • The field is at a critical juncture, necessitating significant transformation.
  • Other industries have successfully integrated AI and machine learning, highlighting a gap.

Conclusions:

  • Traditional methods of ICSR creation and distribution may no longer be suitable for state-of-the-art safety systems.
  • Urgent and rigorous changes are essential for pharmacovigilance to remain relevant.
  • Adoption of technologies like AI and deep machine learning is crucial for future progress.