Optimizing Antibiotic Drug Therapy in Pediatrics: Current State and Future Needs

J Clin Pharmacol. 2018 Oct:58 Suppl 10:S108-S122. doi: 10.1002/jcph.1128.

Abstract

The selection of the right antibiotic and right dose necessitates clinicians understand the contribution of pharmacokinetic variability stemming from age-related physiologic maturation and the pharmacodynamics to optimize drug exposure for clinical response. The complexity of selecting the right dose arises from the multiplicity of pediatric age groups, from premature neonates to adolescents. Body size and age (which relate to organ function) must be incorporated to optimize antibiotic dosing in this vulnerable population. In the effort to optimize and individualize drug dosing regimens, clinical pharmacometrics that incorporate population-based pharmacokinetic modeling, Bayesian estimation, and Monte Carlo simulations are utilized as a quantitative approach to understanding and predicting the pharmacology and clinical and microbiologic efficacy of antibiotics. In addition, opportunistic study designs and alternative blood sampling strategies can serve as practical approaches to ensure successful conduct of pediatric studies. This review article examines relevant literature on optimization of antibiotic pharmacotherapy in pediatric populations published within the last decade. Specific pediatric antibiotic data, including beta-lactam antibiotics, aminoglycosides, and vancomycin, are critically evaluated.

Keywords: Bayesian methods; Monte Carlo simulation; Pharmacokinetic; aminoglycosides; antibiotics; antimicrobials; beta-lactams; ceftaroline; neonates; opportunistic study; pediatrics; pharmacodynamic; vancomycin.

Publication types

  • Research Support, N.I.H., Extramural
  • Review

MeSH terms

  • Anti-Bacterial Agents / pharmacokinetics
  • Anti-Bacterial Agents / pharmacology
  • Anti-Bacterial Agents / therapeutic use*
  • Bacterial Infections / drug therapy*
  • Bacterial Infections / metabolism
  • Bayes Theorem
  • Child
  • Child Development
  • Humans
  • Models, Biological
  • Monte Carlo Method
  • Pediatrics*
  • Pharmacology, Clinical

Substances

  • Anti-Bacterial Agents