A database of pediatric drug effects to evaluate ontogenic mechanisms from child growth and development
Nicholas P Giangreco1, Nicholas P Tatonetti1
1Departments of Systems Biology and Biomedical Informatics, Columbia University, 622 W. 168(th) Street, New York, NY 10032, USA.
Insights
New methods improve pediatric drug safety monitoring by analyzing adverse events across development. This helps identify risks and understand how children
Area of Science:
- Pediatric Pharmacology
- Pharmacovigilance
- Computational Biology
Background:
- Adverse drug effects (ADEs) in children are a significant concern, leading to disability and death.
- Assessing pediatric drug safety is complex due to developmental changes affecting drug response.
- Existing safety-signal detection methods do not adequately address these developmental dynamics.
Purpose of the Study:
- To develop and validate a novel method for identifying drug safety signals in pediatric populations.
- To account for developmental changes in children when evaluating drug safety.
Main Methods:
- Developed disproportionality generalized additive models (dGAMs) to detect safety signals across pediatric development stages.
- Applied dGAMs to a large database of pediatric adverse event reports (264,453 reports).
- Integrated pediatric enzyme expression data, including pharmacogenes like CYP2C18 and CYP27B1.
Main Results:
- Identified 19,438 pediatric ADE signals associated with development.
- Validated identified signals against a reference set of pediatric ADEs.
- Observed developmental dynamics in ADE signals, e.g., montelukast-induced psychiatric disorders peaking in the second year of life.
- Found associations between pharmacogenes with dynamic childhood expression and pediatric ADEs.
Conclusions:
- The dGAMs approach effectively identifies pediatric drug safety signals considering developmental changes.
- Curated the KidSIDES database and developed the Pediatric Drug Safety portal (PDSportal) for community use.
- Facilitates improved evaluation of drug safety signals throughout childhood.
Background:
Adverse drug effects (ADEs) in children are common and may result in disability and death, necessitating post-marketing monitoring of their use. Evaluating drug safety is especially challenging in children due to the processes of growth and maturation, which can alter how children respond to treatment. Current drug safety-signal-detection methods do not account for these dynamics.
Methods:
We recently developed a method called disproportionality generalized additive models (dGAMs) to better identify safety signals for drugs across child-development stages.
Findings:
We used dGAMs on a database of 264,453 pediatric adverse-event reports and found 19,438 ADEs signals associated with development and validated these signals against a small reference set of pediatric ADEs. Using our approach, we can hypothesize on the ontogenic dynamics of ADE signals, such as that montelukast-induced psychiatric disorders appear most significant in the second year of life. Additionally, we integrated pediatric enzyme expression data and found that pharmacogenes with dynamic childhood expression, such as CYP2C18 and CYP27B1, are associated with pediatric ADEs.
Conclusions:
We curated KidSIDES, a database of pediatric drug safety signals, for the research community and developed the Pediatric Drug Safety portal (PDSportal) to facilitate evaluation of drug safety signals across childhood growth and development.
Funding:
This study was supported by grants from the National Institutes of Health (NIH).
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