PulseExploreJournal ClubResearchersJournals
Instagram
HomeJournal ClubExplore
Synapse
⌘+K
Synapse
September 10, 2025GSC Biological and Pharmaceutical SciencesOpen Access

Harnessing predictive analytics for proactive drug safety monitoring: Trends in regulatory reporting, recalls and adverse event detection

View Full Paper
Ask AI
Bookmark
Share

Authors

CKCaleb Kadiri

Discussion

Loading...

Member takes

Overview

This analysis reviews predictive analytics tools to improve drug safety outcomes, suggesting proactive strategies in regulatory reporting and adverse event detection.

Key Points

  • Proactive drug safety monitoring significantly improves the detection of adverse events and reduces recalls.
  • Predictive analytics tools facilitate near-real-time identification of safety signals across various datasets.
  • Regulatory agencies like the FDA and EMA play crucial roles in ensuring algorithm accountability in drug safety.
  • The integration of predictive analytics can reduce the economic burden of drug-related harm while enhancing post-market surveillance.

Cite This Study

Caleb Kadiri (2022) studied this question.

synapsesocial.com/papers/68c244b1b210217d647acc49https://doi.org/10.30574/gscbps.2022.18.2.0027
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Pharmacovigilance: Emerging trends, ongoing challenges, AI and future outlook in pharmacovigilance2025 · 2 citations
  2. 2Artificial intelligence in pharmacovigilance: a narrative review and practical experience with an expert-defined Bayesian network tool2025 · 26 citations
  3. 3In situ development of an artificial intelligence (AI) model for early detection of adverse drug reactions (ADRs) to ensure drug safety2025
  4. 4Artificial intelligence in pharmacovigilance: advancing drug safety monitoring and regulatory integration2025 · 40 citations
  5. 5Rethinking drug safety signal detection and causality assessment in the age of AI: the risks of incomplete data and biased insights2025 · 8 citations