From Pharmacovigilance Signals to Mechanistic Phenotypes: Integrating ADMET, PK/PD, and Network Context to Interpret Antiviral Safety in Pregnancy

<b>Background:</b> Antiviral therapies are widely used during pregnancy and are generally considered safe, pregnancy-specific severe safety signals continue to be observed in post-marketing pharmacovigilance data. These signals are rarely interpreted within an integrated mechanistic framework. <b>Methods:</b> We analysed pregnancy-related EudraVigilance reports (2015-2025) using a previously network-based pharmacovigilance framework. Established ADR clusters were treated as fixed phenotypes and integrated with in silico ADMET liabilities, literature-derived pregnancy pharmacokinetic/pharmacodynamic (PK/PD) parameters, polypharmacy and co-medication network metrics, and exploratory statistical, machine-learning, and exposure-liability analyses for mechanistic prioritisation. <b>Results:</b> Phenotype membership explained 22.3% of the variance in composite ADMET risk (intraclass correlation coefficient = 0.223; <i>p</i> < 0.001), and all tested ADMET parameters differed significantly across phenotypes (FDR-adjusted <i>p</i> < 10^-10). One phenotype showed pronounced enrichment, with 13 antivirals over-represented. Polypharmacy strongly modified seriousness, with odds of serious outcomes increasing by ~5% per additional co-reported active drug (OR 1.05, 95% CI 1.04-1.05). A composite mechanistic vulnerability index showed moderate concordance with empirical burden (Spearman's ρ = 0.65), while regimen-level prioritisation of drug-drug interactions (DDIs) identified no high-priority combinations. <b>Conclusions:</b> Pregnancy-related antiviral ADRs cluster into reproducible phenotypes driven by mechanistic liability and system-level complexity, supporting mechanistically informed prioritisation and targeted pharmacometric follow-up.