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A rational approach for selection of optimal covariate-based dosing strategies
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences, Division of Pharmacokinetics and Drug Therapy.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences, Division of Pharmacokinetics and Drug Therapy.
2003 (English)In: Clinical Pharmacology and Therapeutics, ISSN 0009-9236, E-ISSN 1532-6519, Vol. 73, no 1, 7-19 p.Article in journal (Refereed) Published
Abstract [en]


At present, there is no rational approach for choosing a dosing strategy for individualization based on a covariate. An approach to use in establishment of an a priori dosing strategy for individualization is presented. Factors influencing the choice of such a dosing strategy are identified.


The approach requires definition of the following: target variable, seriousness of deviations from the target (ie, risk function), population model, covariate distributions, and constraints. Minimizing the total risk yields an optimal dosing strategy, estimated as dose sizes for different subpopulations and covariate cutoff values at which doses are increased or decreased. The method was illustrated with the use of simulated and real drug examples for the situation in which clearance is related to creatinine clearance.


The estimated optimal cutoff(s) paralleled the median creatinine clearance in the population. The extent of variability in clearance explained by creatinine clearance was the main factor influencing the optimal ratios between adjacent dose sizes. An optimal dosing strategy was possible to estimate for the real drug.


The method is simple to perform, although one difficulty lies in defining the target variable and risk function. Our results imply that commonly used constraints in dosing strategies based on renal function (ie, dose ratio of 2 and predetermined cutoffs) are nonoptimal in the sense we propose. Because an optimal dosing strategy may not be practical to use, the therapeutic cost that would result with any constraint can be assessed by comparison of the outcome after the desired and the optimal strategy.

Place, publisher, year, edition, pages
2003. Vol. 73, no 1, 7-19 p.
National Category
Medical and Health Sciences
URN: urn:nbn:se:uu:diva-91732DOI: 10.1067/mcp.2003.2PubMedID: 12545139OAI: oai:DiVA.org:uu-91732DiVA: diva2:164561
Available from: 2004-04-26 Created: 2004-04-26 Last updated: 2011-10-06Bibliographically approved
In thesis
1. Estimation of Dosing Strategies for Individualisation
Open this publication in new window or tab >>Estimation of Dosing Strategies for Individualisation
2004 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

To increase the proportion of patients with successful drug treatment, dose individualisation on the basis of one or several patient characteristics, a priori individualisation, and/or on the basis of feedback observations from the patient following an initial dose, a posteriori individualisation, is an option. Efficient tools in optimising individualised dosing strategies are population models describing pharmacokinetics (PK) and the relation between pharmacokinetics and pharmacodynamics (PK/PD).

Methods for estimating optimal dosing strategies, with a discrete number of doses, for dose individualisation a priori and a posteriori were developed and explored using simulated data. The methods required definitions of (i) the therapeutic target, i.e. the value of the target variable and a risk function quantifying the seriousness of deviation from the target, (ii) a population PK/PD model relating dose input to the target variable in the patients to be treated, and (iii) distributions of relevant patient factors. Optimal dosing strategies, in terms of dose sizes and individualisation conditions, were estimated by minimising the overall risk. Factors influencing the optimal dosing strategies were identified. Consideration of those will have implications for study design, data collection, population model development and target definition.

A dosing strategy for a priori individualisation was estimated for NXY-059, a drug under development. Applying the estimated dosing strategy in a clinical study resulted in reasonable agreement between observed and expected outcome, supporting the developed methodology.

Estimation of a dosing strategy for a posteriori individualisation for oxybutynin, a drug marketed for the treatment of overactive bladder, illustrated the implementation of the method when defining the therapeutic target in terms of utility and responder probability, that is, as a combination of the desired and adverse effects.

The proposed approach provides an estimate of the maximal benefit expected from individualisation and, if individualisation is considered clinically superior, the optimal conditions for individualisation. The main application for the methods is in drug development where the methods can be generally employed in the establishment of dosing strategies for individualisation with relevant extensions regarding population model complexity and individualisation conditions.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2004. 62 p.
Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, ISSN 0282-7484 ; 312
Pharmaceutical biosciences, Dosing strategy, Individualisation, Pharmacokinetic, Pharmacodynamic, Modeling, NONMEM, Decision making, Farmaceutisk biovetenskap
National Category
Pharmaceutical Sciences
urn:nbn:se:uu:diva-4255 (URN)91-554-5960-9 (ISBN)
Public defence
2004-05-19, Room B21, BMC, Husargatan 3, Uppsala, 09:15
Available from: 2004-04-26 Created: 2004-04-26Bibliographically approved

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