Optimizing drug development of anti-cancer drugs in children using modelling and simulation

Johan G.C. Van Hasselt*, Natasha K.A. van Eijkelenburg, Jos H. Beijnen, Jan H.M. Schellens, Alwin D.R. Huitema

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

18 Citations (Scopus)

Abstract

Modelling and simulation (M&S)-based approaches have been proposed to support paediatric drug development in order to design and analyze clinical studies efficiently. Development of anti-cancer drugs in the paediatric population is particularly challenging due to ethical and practical constraints. We aimed to review the application of M&S in the development of anti-cancer drugs in the paediatric population, and to identify where M&S-based approaches could provide additional support in paediatric drug development of anti-cancer drugs. A structured literature search on PubMed was performed. The majority of identified M&S-based studies aimed to use population PK modelling approaches to identify determinants of inter-individual variability, in order to optimize dosing regimens and to develop therapeutic drug monitoring strategies. Prospective applications of M&S approaches for PK-bridging studies have scarcely been reported for paediatric oncology. Based on recent developments of M&S in drug development there are several opportunities where M&S could support more informative bridging between children and adults, and increase efficiency of the design and analysis of paediatric clinical trials, which should ultimately lead to further optimization of drug treatment strategies in this population.

Original languageEnglish
Pages (from-to)30-47
Number of pages18
JournalBritish Journal of Clinical Pharmacology
Volume76
Issue number1
DOIs
Publication statusPublished - 1 Jul 2013

Keywords

  • Anti-cancer drugs
  • Chemotherapy
  • Modelling
  • Paediatric drug development
  • Paediatric oncology
  • Pharmacokinetics

Fingerprint

Dive into the research topics of 'Optimizing drug development of anti-cancer drugs in children using modelling and simulation'. Together they form a unique fingerprint.

Cite this