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A Database of Pediatric Drug Effects to Evaluate Ontogenic Mechanisms From Child Growth and Development

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54 Pages Posted: 3 Aug 2021 Publication Status: Under Review

See all articles by Nicholas P. Giangreco

Nicholas P. Giangreco

Columbia University - Departments of Systems Biology and Biomedical Informatics

Nicholas P. Tatonetti

Columbia University - Departments of Systems Biology and Biomedical Informatics

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Abstract

Adverse drugs effects (ADEs) in children are common and may result in disability and death. However, methodologies do not surpass event surveillance to identify and evaluate potential dynamic mechanisms from child growth and development. We generated a database of 460,837 pediatric ADEs using generalized additive models (GAMs) previously shown to identify dynamic risk estimates of adverse drug events 1 . We identified 19,438 significant drug-event risks including known pediatric drug effects exhibiting risk dynamics across child development, such as montelukast-induced psychiatric disorders within the second year of life (Odds Ratio 8.77 [2.51, 46.94]). A data-driven time-series clustering approach resulted in up to 95.2% precision and 97.8% sensitivity for categorizing risk dynamics. We found that our real-world evidence may contain biologically-relevant underpinnings. 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.

Keywords: Child Development, Data Mining, Pharmacology, Precision Medicine, Adverse Drug Events

Suggested Citation

Giangreco, Nicholas P. and Tatonetti, Nicholas P., A Database of Pediatric Drug Effects to Evaluate Ontogenic Mechanisms From Child Growth and Development. Available at SSRN: https://ssrn.com/abstract=3898786 or http://dx.doi.org/10.2139/ssrn.3898786
This version of the paper has not been formally peer reviewed.

Nicholas P. Giangreco

Columbia University - Departments of Systems Biology and Biomedical Informatics ( email )

3022 Broadway
New York, NY 10027
United States

Nicholas P. Tatonetti (Contact Author)

Columbia University - Departments of Systems Biology and Biomedical Informatics ( email )

622 W. 168th Street
Presbyterian Building 20th Floor
New York, NY 10032
United States

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