Adverse drugs effects (ADEs) in children are common and may result in disability and death. However, current pediatric drug safety methods have not gone beyond event surveillance to identify and evaluate potential biological mechanisms. Children undergo an evolutionarily conserved and physiologically dynamic process of growth and maturation that can alter pharmacokinetics and pharmacodynamics. Our hypothesis is that temporal patterns of drug event reporting are reflective of dynamic mechanisms from child growth and development. We generated a database of 460,837 pediatric ADEs using generalized additive models (GAMs) that we have previously shown identify dynamic risk estimates of adverse drug events. We identified 19,438 significant drug-event risks where drug risks corresponded with physiological development throughout childhood. Our results identified known pediatric drug effects and risk dynamics across child development that were not known previously. For example, we identified significant risk dynamics of montelukast-induced psychiatric disorders, including enriched risk (Odds Ratio 8.77 [2.51, 46.94]) within the second year of life. We developed a data-driven time-series clustering approach resulting in up to 95.2% precision and 97.8% sensitivity for categorizing risk dynamics across development stages for all ADEs including known but previously development-agnostic pediatric drug effects. We found that our real-world evidence may contain biologically-relevant underpinnings as well, where risk dynamics of CYP enzyme substrates were dependent on the enzyme's expression across childhood. We curated this database for the research community to enable, for the first time, evaluation of real-world hypotheses of adverse drug effects across child growth and development.
A Database of Pediatric Drug Effects to Evaluate Ontogenic Mechanisms From Child Growth and Development
