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Simultaneous optimal experimental design on dose and sample times
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. (Farmakometri)
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. (Farmakometri)
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. (Farmakometri)
2009 (English)In: Journal of Pharmacokinetics and Pharmacodynamics, ISSN 1567-567X, E-ISSN 1573-8744, Vol. 36, no 2, p. 125-145Article in journal (Refereed) Published
Abstract [en]

Optimal experimental design can be used for optimizing new pharmacokinetic (PK)-pharmacodynamic (PD) studies to increase the parameter precision. Several methods for optimizing non-linear mixed effect models has been proposed previously but the impact of optimizing other continuous design parameters, e.g. the dose, has not been investigated to a large extent. Moreover, the optimization method (sequential or simultaneous) for optimizing several continuous design parameters can have an impact on the optimal design. In the sequential approach the time and dose where optimized in sequence and in the simultaneous approach the dose and time points where optimized at the same time. To investigate the sequential approach and the simultaneous approach; three different PK-PD models where considered. In most of the cases the optimization method did change the optimal design and furthermore the precision was improved with the simultaneous approach.

Place, publisher, year, edition, pages
2009. Vol. 36, no 2, p. 125-145
Keywords [en]
Optimal design, simultaneous optimization, dose optimization, pharmacometrics
National Category
Pharmaceutical Sciences
Identifiers
URN: urn:nbn:se:uu:diva-122156DOI: 10.1007/s10928-009-9114-zISI: 000265825000002PubMedID: 19319484OAI: oai:DiVA.org:uu-122156DiVA, id: diva2:308515
Available from: 2010-04-06 Created: 2010-04-06 Last updated: 2018-01-12Bibliographically approved
In thesis
1. Practical Optimal Experimental Design in Drug Development and Drug Treatment using Nonlinear Mixed Effects Models
Open this publication in new window or tab >>Practical Optimal Experimental Design in Drug Development and Drug Treatment using Nonlinear Mixed Effects Models
2011 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The cost of releasing a new drug on the market has increased rapidly in the last decade. The reasons for this increase vary with the drug, but the need to make correct decisions earlier in the drug development process and to maximize the information gained throughout the process is evident.

Optimal experimental design (OD) describes the procedure of maximizing relevant information in drug development and drug treatment processes. While various optimization criteria can be considered in OD, the most common is to optimize the unknown model parameters for an upcoming study. To date, OD has mainly been used to optimize the independent variables, e.g. sample times, but it can be used for any design variable in a study.

This thesis addresses the OD of multiple continuous or discrete design variables for nonlinear mixed effects models. The methodology for optimizing and the optimization of different types of models with either continuous or discrete data are presented and the benefits of OD for such models are shown. A software tool for optimizing these models in parallel is developed and three OD examples are demonstrated: 1) optimization of an intravenous glucose tolerance test resulting in a reduction in the number of samples by a third, 2) optimization of drug compound screening experiments resulting in the estimation of nonlinear kinetics and 3) an individual dose-finding study for the treatment of children with ciclosporin before kidney transplantation resulting in a reduction in the number of blood samples to ~27% of the original number and an 83% reduction in the study duration.

This thesis uses examples and methodology to show that studies in drug development and drug treatment can be optimized using nonlinear mixed effects OD. This provides a tool than can lower the cost and increase the overall efficiency of drug development and drug treatment.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2011. p. 74
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, ISSN 1651-6192 ; 149
Keywords
Pharmacometrics, optimal design, nonlinear mixed effects models, robust design, optimizing drug development, population models
National Category
Pharmaceutical Sciences
Research subject
Pharmacokinetics and Drug Therapy
Identifiers
urn:nbn:se:uu:diva-160481 (URN)978-91-554-8202-2 (ISBN)
Public defence
2011-12-09, B21, Biomedicinskt Centrum, Husargatan 3, Uppsala, 13:15 (English)
Opponent
Supervisors
Available from: 2011-11-18 Created: 2011-10-24 Last updated: 2018-01-12Bibliographically approved

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Karlsson, Mats O.Hooker, Andrew C.

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