Practical Optimal Experimental Design in Drug Development and Drug Treatment using Nonlinear Mixed Effects Models

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Practical Optimal Experimental Design in Drug Development and Drug Treatment using Nonlinear Mixed Effects Models

Nyberg, Joakim, 1978- (författare): Uppsala universitet,Institutionen för farmaceutisk biovetenskap

Hooker, Andrew C., doktor (preses): Uppsala universitet,Institutionen för farmaceutisk biovetenskap

Karlsson, Mats O., professor (preses): Uppsala universitet,Institutionen för farmaceutisk biovetenskap

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Leonov, Sergei, doktor (opponent): Director Biometrics, Vertex Pharmaceuticals

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ISBN 9789155482022
Uppsala : Acta Universitatis Upsaliensis, 2011
Engelska 74 s.
Serie: Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, 1651-6192 ; 149

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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)

Abstract Ämnesord

Stäng

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.

Ämnesord

MEDICIN OCH HÄLSOVETENSKAP -- Medicinska och farmaceutiska grundvetenskaper -- Farmaceutiska vetenskaper (hsv//swe)
MEDICAL AND HEALTH SCIENCES -- Basic Medicine -- Pharmaceutical Sciences (hsv//eng)

Nyckelord

Pharmacometrics
optimal design
nonlinear mixed effects models
robust design
optimizing drug development
population models
Pharmacokinetics and Drug Therapy
Farmakokinetik och läkemedelsterapi

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