Synapse
⌘+K
Synapse
PulseExploreJournal ClubResearchersJournals
Instagram
HomeJournal ClubExplore
September 17, 2025Frontiers in Drug Safety and RegulationOpen Access

Rethinking drug safety signal detection and causality assessment in the age of AI: the risks of incomplete data and biased insights

View Full Paper
Ask AI
Bookmark
Share

Authors

PCPriyanka ChhikaraTHTarek A. Hammad

Discussion

Loading...

Member takes

Overview

Observational analysis identifies risks in drug safety signal detection in marginalized communities, highlighting the need for complete data.

Key Points

  • AI tools may miss critical safety signals due to biased or incomplete data, especially in marginalized populations.
  • Disparities in clinical recommendations were noted based on sociodemographic characteristics, impacting drug safety assessments.
  • Effective drug safety signal detection relies on diverse and complete real-world data for accurate risk identification.
  • Addressing biases in AI modeling will require systematic audits and improvements in healthcare data documentation practices.

Cite This Study

Chhikara et al. (2025) studied this question.

synapsesocial.com/papers/68d43c79713b0b5dfea7bd09https://doi.org/10.3389/fdsfr.2025.1678074
View Full Paper
Ask AI
Bookmark
Share