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Pharmacokinetic-Pharmacodynamic Modeling in Pediatric Drug Development, and the Importance of Standardized Scaling of Clearance
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. UCL, UCL Great Ormond St Inst Child Heath, Infect Inflammat & Rheumatol Sect, London, England.ORCID iD: 0000-0003-2935-0090
UCL, UCL Great Ormond St Inst Child Heath, Infect Inflammat & Rheumatol Sect, London, England;St Georges Univ London, Inst Infect & Immun, Paediat Infect Dis Res Grp, London, England;St Georges Univ Hosp NHS Fdn Trust, London, England.
St Georges Univ London, Inst Infect & Immun, Paediat Infect Dis Res Grp, London, England;St Georges Univ Hosp NHS Fdn Trust, London, England.
UCL, UCL Great Ormond St Inst Child Heath, Infect Inflammat & Rheumatol Sect, London, England;St Georges Univ London, Inst Infect & Immun, Paediat Infect Dis Res Grp, London, England.
2019 (English)In: Clinical Pharmacokinetics, ISSN 0312-5963, E-ISSN 1179-1926, Vol. 58, no 1, p. 39-52Article, review/survey (Refereed) Published
Abstract [en]

Pharmacokinetic/pharmacodynamic (PKPD) modeling is important in the design and conduct of clinical pharmacology research in children. During drug development, PKPD modeling and simulation should underpin rational trial design and facilitate extrapolation to investigate efficacy and safety. The application of PKPD modeling to optimize dosing recommendations and therapeutic drug monitoring is also increasing, and PKPD model-based dose individualization will become a core feature of personalized medicine. Following extensive progress on pediatric PK modeling, a greater emphasis now needs to be placed on PD modeling to understand age-related changes in drug effects. This paper discusses the principles of PKPD modeling in the context of pediatric drug development, summarizing how important PK parameters, such as clearance (CL), are scaled with size and age, and highlights a standardized method for CL scaling in children. One standard scaling method would facilitate comparison of PK parameters across multiple studies, thus increasing the utility of existing PK models and facilitating optimal design of new studies.

Place, publisher, year, edition, pages
ADIS INT LTD , 2019. Vol. 58, no 1, p. 39-52
National Category
Pharmaceutical Sciences
Identifiers
URN: urn:nbn:se:uu:diva-374865DOI: 10.1007/s40262-018-0659-0ISI: 000455370400003PubMedID: 29675639OAI: oai:DiVA.org:uu-374865DiVA, id: diva2:1284283
Funder
EU, FP7, Seventh Framework Programme, 261060
Note

Correction in: Clinical Pharmacokinetics, vol. 58, issue 1, pages 139.

DOI: 10.1007/s40262-018-0723-9

Available from: 2019-01-31 Created: 2019-01-31 Last updated: 2019-01-31Bibliographically approved

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