Cross-National Pharmacovigilance Data Pooling Accelerates Drug Safety Signal Detection: Evidence from Change-Point Analysis of Australia’s DAEN and the US FAERS

Cross-National Pharmacovigilance Data Pooling Accelerates Drug Safety Signal Detection: Evidence from Change-Point Analysis of Australia’s DAEN and the US FAERS | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 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Data may be preliminary. 12 May 2026 V1 Latest version Share on Cross-National Pharmacovigilance Data Pooling Accelerates Drug Safety Signal Detection: Evidence from Change-Point Analysis of Australia’s DAEN and the US FAERS Author : Hayden Farquhar 0009-0002-6226-440X [email protected] Authors Info & Affiliations https://doi.org/10.22541/authorea.15003056/v1 18 views 9 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Aim: To test whether change-point detection (CPD) identifies drug safety signals earlier than standard disproportionality analysis, and whether pooling data from two national databases improves detection timing. Methods: An ensemble of three CPD algorithms — PELT, CUSUM, and Bayesian Online Change Point Detection (BOCPD) — was applied to quarterly drug-specific adverse event reporting proportions in Australia’s DAEN (664,747 reports, 2004-2025). Rolling Proportional Reporting Ratio (PRR) served as comparator. Performance was validated against 32 TGA regulatory actions, 40 curated reference associations, and OMOP/EU-ADR reference standards (111 positive controls, 87 negative controls). Parallel time series were constructed in FAERS for all 32 TGA pairs. The protocol was pre-registered on the Open Science Framework. Results: Twenty of 23 confirmed CPD detections preceded TGA regulatory action (87%), with a median lead time of 12.0 quarters. For established drugs developing new adverse events, CPD outpaced rolling PRR by a median of 5.0 quarters (Wilcoxon p=0.003). PRR was faster for newly marketed drugs. Sensitivity reached 74% (Tier A) and 95% (Tier B); specificity was 89%. Pooling DAEN and FAERS brought detection forward by a median of 8.0 quarters over DAEN alone (p<0.0001), concentrated among weak signals (15.0 vs 4.0 quarters for below- vs above-median EBGM). The detection-to-action gap widened over the study period (Spearman rho=0.78, p<0.0001). Conclusion: CPD complements disproportionality analysis, with the greatest advantage for late-emerging adverse events in established drugs. Cross-national data pooling substantially accelerates detection for weak signals. These results support integrating temporal change-point monitoring and cross-database data sharing into pharmacovigilance operations. Supplementary Material File (readus_pv_checklist.docx) readus_pv_checklist Download 26.44 KB File (supplementary_material_bjcp.docx) supplementary_material_bjcp Download 1.72 MB Information & Authors Information Version history V1 Version 1 12 May 2026 Collection British Journal of Clinical Pharmacology Authors Affiliations Hayden Farquhar 0009-0002-6226-440X [email protected] Independent Researcher, Finley, Australia View all articles by this author Metrics & Citations Metrics Article Usage 18 views 9 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Hayden Farquhar. Cross-National Pharmacovigilance Data Pooling Accelerates Drug Safety Signal Detection: Evidence from Change-Point Analysis of Australia’s DAEN and the US FAERS. Authorea . 12 May 2026. DOI: https://doi.org/10.22541/authorea.15003056/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. 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