Tom Z. Hui* Pages 124 - 130 ( 7 )
Background: Efficiency and accuracy for signal detection and evaluation activities are integral components of routine Pharmacovigilance (PV) practices. However, an Individual Case Safety Report (ICSR) may consist of a variety of confounders such as Concomitant Medications (CM), Past Medical History (PMH), and concurrent medical conditions that influence a safety officer’s evaluation of a potential Adverse Event (AE). Limited pharmacovigilance systems are currently available as a tool designed to enhance the efficiency and accuracy of signal detection and management.Objective: To introduce a systemic approach to make critical safety information readily available for users in order to discern possible interferences from CM and make informed decisions on the signal evaluation process – saving time while improving quality. Methods: Oracle Empirica Signal software was utilized to extract cases with CM that are Known Implicating Medications (KIM) for each AE according to public regulatory information from drug labels – FDA Structured Product Labeling (SPL) or EMA Summary of Product Characteristics (SPC). SAS Enterprise Guide was used to further process the data generated from Oracle Empirica Signal software. Results: For any target drug being evaluated for safety purposes, a KIM reference table can be generated, which summarizes all potential causality contributions from CMs. Conclusion: In addition to providing standalone KIM table as reference, adoption of this concept and automation may also be fully integrated into commercial signal detection and management software packages for easy use and accessibility and may even lead to reduced False Positive rate in signal detection within the PV space.
Patient safety, drug safety, pharmacovigilance, adverse event, adverse reaction, signal detection, clinical trial, postmarketing surveillance.
Global Patient Safety Evaluation, Takeda Pharmaceuticals, Cambridge, MA