Literature DB >> 11587494

Modeling and stimulation for clinical trial design involving a categorical response: a phase II case study with naratriptan.

I Nestorov1, G Graham, S Duffull, L Aarons, E Fuseau, P Coates.   

Abstract

PURPOSE: The overall aim of the present study was to investigate retrospectively the feasibility and utility of model-based clinical trial simulation as applied to the clinical development of naratriptan with effect measured on a categorical scale.
METHODS: A PK-PD model for naratriptan was developed by using information gathered from previous naratriptan and sumatriptan preclinical and clinical trials. The phase IIa naratriptan data were used to check the PK-PD model in its ability to describe future data. A further PK-PD model was developed by using the phase IIa naratriptan data, and a phase IIb trial was designed by simulation with the use of Matlab. The design resulting from clinical trial simulation was compared with that derived by using D-optimal design.
RESULTS: The PK-PD model showed reasonable agreement with the data observed in the phase IIa naratriptan clinical trial. Clinical trial simulation resulted in a design with four or five arms at 0 mg, 2.5 and/or 5 mg, 10 mg, and 20 mg, PD measurements to be taken at 0, 2, and 4 or 6 h and at least 150 patients per arm. A sub-D-optimal design resulted in two dosing arms at 0 and 10 mg and PD measurements to be taken at 1 and 2 h.
CONCLUSIONS: Clinical trial simulation is a useful tool for the quantitative assessment of the influence of the controllable factors and is the only tool for the quantitative assessment of the uncontrollable factors on the power of a clinical trial.

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Year:  2001        PMID: 11587494     DOI: 10.1023/a:1010943430471

Source DB:  PubMed          Journal:  Pharm Res        ISSN: 0724-8741            Impact factor:   4.200


  12 in total

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  15 in total

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Review 9.  Penetration of antibacterials into bone: pharmacokinetic, pharmacodynamic and bioanalytical considerations.

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Review 10.  Facilitation of drug evaluation in children by population methods and modelling.

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