Antibiotic dosing in children in Europe: can we grade the evidence from pharmacokinetic/pharmacodynamic studies - and when is enough data enough?

Purpose of review Antibiotics are prescribed more frequently to children than any other class of medication. Analysis of the evidence behind antimicrobial dosing regimes is imperative to improve clinical outcomes, minimize antimicrobial resistance development, and to identify priority research areas for the future. This review aims to promote debate amongst paediatricians, pharmacologists, and pharmacists about how to improve antimicrobial prescribing by considering methods to develop and disseminate optimal dosage information. Recent findings There has been increasing use of population analyses to understand pharmacokinetic/pharmacodynamic (PK/PD) parameters in children. Nonlinear mixed effects modelling is widely accepted to be the method of choice for analyses of PK/PD data. However, communicating the quality of PK/PD studies is an equally important factor to allow clinicians to gauge the robustness of the evidence. The possibility of grading PK/PD studies is discussed, along with using systematic reviews and PK/PD meta-analysis for generating high-quality evidence. Many doses in existing formularies (including the British National Formulary for Children) are based on outdated evidence. The need to update formularies to account for new evidence, population changes (e. g. obesity), and changing patterns of resistance requires a more systematic evaluation of antimicrobial PK/PD relationships in children. The possibility of e-formularies with links directly to the evidence should be considered and regulators must also play a role in supporting the re-evaluation of off-patent dosing guidelines. Summary Advancing our understanding of the evidence behind paediatric antimicrobial therapeutic regimens is essential to improve both clinical outcomes and patient safety. Using a combination of international collaboration, electronic communication, and PK/PD modelling techniques, we can now define the gaps in our knowledge base and develop the techniques to answer them.