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Trial Treatment Length Optimization With an Emphasis on Disease Progression Studies

From the Division of Pharmacokinetics and Drug Therapy, Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden.

Optimal design has been used in the past mainly to optimize sampling schedules for clinical trials. Optimization on design variables other than sampling times has been published in the literature only once before. This study shows, as an example, optimization on the length of treatment periods to obtain reliable estimates of drug effects on longterm disease progression studies. Disease progression studies are high in cost, effort, and time; therefore, optimization of treatment length is highly recommended to avoid failure or loss of information. Results are provided for different drug effects (eg, protective and symptomatic) and for different lengths of studies and sampling schedules. The merits of extending the total study length versus inclusion of more samples per participants are investigated. The authors demonstrate that if no observations are taken during the washout period, a trial can lose up to 40% of its efficiency. Furthermore, when optimization of treatment length is performed using multiple possible drug effect models simultaneously, these studies show high power in discriminating between different drug effect models.

Key Words: optimal design • disease progression studies • clinical trial design • pharmacometrics

Address for reprints: Stefanie Hennig, Division of Pharmacokinetics and Drug Therapy, Department of Pharmaceutical Biosciences, Uppsala University, Box 591, SE 751 24 Uppsala, Sweden; e-mail: stefanie.hennig{at}farmbio.uu.se.

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