Frontiers in pharmacology · 2026
A manufacturer-aware cross-system benchmark for pediatric pharmacovigilance signal concordance.
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Shi Jinwan, Xia Jieting, Li Huanqiong, Zhang Shuyan, Shi Bowen
Аннотация
INTRODUCTION: Pediatric adverse drug reactions are difficult to evaluate after approval because pediatric trial evidence is limited and spontaneous-report systems differ in product naming, event coding, seriousness fields, and duplicate submissions.
METHODS: We developed a manufacturer-aware benchmark for pediatric pharmacovigilance signal concordance using the FDA Adverse Event Reporting System (FAERS)/AERS as the source system, Canada Vigilance as a cross-system reporting-signal comparator, and JADER for descriptive third-country context. Active ingredients and five clinically adjudicated serious endpoint families were harmonized before detectable manufacturer cross-filing was screened.
RESULTS: The supervised benchmark contained 628 drug-endpoint-period rows: 147 manufacturer-screened Canada Vigilance reporting-signal positives and 481 Canada Vigilance co-report-absent comparators. An endpoint-conditioned FAERS co-reporting comparator achieved an area under the precision-recall curve (AUPRC) of 0.753. Elastic-net logistic regression reached 0.767, and a LightGBM comparator reached 0.774, but clustered paired-difference intervals versus the conditioned co-report comparator included zero. In 30 repeated drug-held-out partitions, chemical structure increased the mean AUPRC from 0.764 to 0.796, but the corresponding increment was -0.003 under unseen-scaffold partitions; target and pathway indicators produced no further material increase. Future-period support was concentrated in anaphylaxis: 40 drug pairs remained after manufacturer screening, including 37 with FAERS source exposure, and four of five FAERS scores ranked supported pairs above permutation expectations.
DISCUSSION: Clinical label specificity, detectable duplicate screening, and fair source-signal comparators materially influenced model evaluation. The resulting resource provides a reproducible reference for pediatric signal triage and for testing whether new pharmacological features or models add information beyond established reporting statistics.
METHODS: We developed a manufacturer-aware benchmark for pediatric pharmacovigilance signal concordance using the FDA Adverse Event Reporting System (FAERS)/AERS as the source system, Canada Vigilance as a cross-system reporting-signal comparator, and JADER for descriptive third-country context. Active ingredients and five clinically adjudicated serious endpoint families were harmonized before detectable manufacturer cross-filing was screened.
RESULTS: The supervised benchmark contained 628 drug-endpoint-period rows: 147 manufacturer-screened Canada Vigilance reporting-signal positives and 481 Canada Vigilance co-report-absent comparators. An endpoint-conditioned FAERS co-reporting comparator achieved an area under the precision-recall curve (AUPRC) of 0.753. Elastic-net logistic regression reached 0.767, and a LightGBM comparator reached 0.774, but clustered paired-difference intervals versus the conditioned co-report comparator included zero. In 30 repeated drug-held-out partitions, chemical structure increased the mean AUPRC from 0.764 to 0.796, but the corresponding increment was -0.003 under unseen-scaffold partitions; target and pathway indicators produced no further material increase. Future-period support was concentrated in anaphylaxis: 40 drug pairs remained after manufacturer screening, including 37 with FAERS source exposure, and four of five FAERS scores ranked supported pairs above permutation expectations.
DISCUSSION: Clinical label specificity, detectable duplicate screening, and fair source-signal comparators materially influenced model evaluation. The resulting resource provides a reproducible reference for pediatric signal triage and for testing whether new pharmacological features or models add information beyond established reporting statistics.