A pragmatic approach to the design of population pharmacokinetic studies |
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Authors: | Amit Roy Ene I. Ette |
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Affiliation: | 1Strategic Modeling and Simulation, Bristol-Myers Squibb, 08543 Princeton, NJ ;2Department of Clinical Pharmacology, Vertex Pharmaceuticals, 130 Waverly St., 02139 Cambridge, MA |
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Abstract: | The publication of a seminal article on nonlinear mixed-effect modeling led to a revolution in pharmacokinetics (PKs) with the introduction of the population approach. Since then, interest in obtaining accurate and precise estimates of population PK parameters has led to work on population PK study design that extended previous work on optimal sampling designs for individual PK parameter estimation. The issues and developments in the design of population PK studies are reviewed as a prelude to investigating, via simulation, the performance of 2 approaches (population Fisher information matrix D-optimal design and informative block [profile] randomized [IBR] design) for designing population PK studies. The results of our simulation study indicate that the designs based on the 2 approaches yielded efficient parameter estimates. The designs based on the 2 approaches performed similarly, and in some cases designs based on the IBR approach were slightly better. The ease with which the IBR designs can be generated makes them preferable in drug development, where pragmatism and time are of great consideration. We, therefore, refer to the IBR designs as pragmatic designs. Pragmatic designs that achieve high efficiency in the estimation parameters should be used in the design of population PK studies, and simulation should be used to determine the efficiency of the designs. |
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Keywords: | population pharmacokinetic sampling design D-optimality informative block randomized design population Fisher information matrix D-optimal design |
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