ReviewBritish journal of clinical pharmacology2022
No population left behind: Improving paediatric drug safety using informatics and systems biology.
Review in British journal of clinical pharmacology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- Three-dimensional printing as a transformative platform for patient-centric pediatric drug delivery: technologies, formulation strategies and clinical translation.Daru : journal of Faculty of Pharmacy, Tehran University of Medical Sciences · 2026Review
- Machine learning prediction of pediatric adverse drug reactions using consensus-derived scarce data.Communications chemistry · 2025Article
- LEVERAGING UNSTRUCTURED DATA IN ELECTRONIC HEALTH RECORDS TO DETECT ADVERSE EVENTS FROM PEDIATRIC DRUG USE - A SCOPING REVIEW.medRxiv : the preprint server for health sciences · 2025Article
- A Review of 3D Printing Technology in Pharmaceutics: Technology and Applications, Now and Future.Pharmaceutics · 2023Review
- A database of pediatric drug effects to evaluate ontogenic mechanisms from child growth and development.Med (New York, N.Y.) · 2022Article
- No population left behind: Improving paediatric drug safety using informatics and systems biology.British journal of clinical pharmacology · 2022Review
- Signal Detection of Pediatric Drug-Induced Coagulopathy Using Routine Electronic Health Records.Frontiers in pharmacology · 2022Article
- Evaluating risk detection methods to uncover ontogenic-mediated adverse drug effect mechanisms in children.BioData mining · 2021Article
- Drug Safety in Translational Paediatric Research: Practical Points to Consider for Paediatric Safety Profiling and Protocol Development: A Scoping Review.Pharmaceutics · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Adverse drugs effects (ADEs) in children are common and may result in disability and death. The current paediatric drug safety landscape, including clinical trials, is limited as it rarely includes children and relies on extrapolation from adults. Children are not small adults but go through an evolutionarily conserved and physiologically dynamic process of growth and maturation. Novel quantitative approaches, integrating observations from clinical trials and drug safety databases with dynamic mechanisms, can be used to systematically identify ADEs unique to childhood. In this perspective, we discuss three critical research directions using systems biology methodologies and novel informatics to improve paediatric drug safety, namely child versus adult drug safety profiles, age-dependent drug toxicities and genetic susceptibility of ADEs across childhood. We argue that a data-driven framework that leverages observational data, biomedical knowledge and systems biology modelling will reveal previously unknown mechanisms of pediatric adverse drug events and lead to improved paediatric drug safety.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.