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Quantitative data mining in signal detection: the Singapore experience.

Cheng Leng Chan1,2, Sally Soh1, Siew Har Tan1

  • 1Health Products Regulation Group, Health Sciences Authority, Singapore, Singapore.

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Quantitative data mining (QDM) triage significantly improves drug safety signal detection by reducing the number of adverse event reports needing review. This method enhances efficiency and avoids missing critical safety signals.

Keywords:
QDM triageSPRTSpontaneous reportsquantitative data mining (QDM)sequential probability ratio testsignal detectionsignals of disproportionate reporting

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Area of Science:

  • Pharmacovigilance
  • Drug Safety
  • Regulatory Science

Background:

  • The Health Sciences Authority (HSA) in Singapore handles approximately 20,000 adverse event (AE) reports annually.
  • Current safety signal detection relies on manual review and weekly discussions.
  • The need for efficient methods to manage large volumes of AE data is critical.

Purpose of the Study:

  • To evaluate the effectiveness of quantitative data mining (QDM) methods in improving drug safety signal detection.
  • To compare QDM triage strategies against traditional manual review processes.
  • To assess if QDM can enhance the efficiency of pharmacovigilance workflows.

Main Methods:

  • A QDM triage strategy was developed to pre-filter signals of disproportionate reporting (SDRs).
  • The strategy was compared against manual reviews over a 6-month period.
  • QDM triage was integrated into the manual review workflow for two subsequent 6-month periods.

Main Results:

  • Incorporating QDM triage reduced the number of drug-AE pairs for evaluation by 20% to 30%.
  • The Sequential Probability Ratio Test (SPRT) method showed high concordance with human manual signal detection.
  • QDM triage streamlined the review process while maintaining signal detection capabilities.

Conclusions:

  • QDM triage offers a more efficient approach to drug safety signal detection.
  • Integrating QDM into manual reviews enhances pharmacovigilance efficiency without compromising safety.
  • This approach helps in avoiding the omission of crucial drug safety signals.