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Optimizing Dose-Finding Studies for Drug Combinations Based on Exposure-Response Models.

Theodoros Papathanasiou1,2, Anders Strathe3, Rune Viig Overgaard3

  • 1Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark. tpap@novonordisk.com.

The AAPS Journal
|July 31, 2019
PubMed
Summary
This summary is machine-generated.

Optimal designs significantly enhance drug combination studies by improving dose selection efficiency and accuracy. This method increases the probability of identifying the best dose combination compared to typical trial designs.

Keywords:
Dose allocationDrug combinationsExposure-response analysesOptimal designResponse surface

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Area of Science:

  • Pharmacology
  • Clinical Trial Design
  • Biostatistics

Background:

  • Combination pharmacological treatments are explored for enhanced clinical benefits, particularly synergistic interactions.
  • Dose selection in combination drug development is challenging due to numerous possible dose combinations.

Purpose of the Study:

  • To evaluate the value of optimal design methods in guiding dose allocation for drug combination dose-finding studies.
  • To compare optimal designs against typical drug-combination trial designs.

Main Methods:

  • Utilized local [D(s)-optimality] and global [ED(s)-optimality] designs to maximize precision of model parameters in exposure-response (E-R) surfaces.
  • Employed a compound criterion [D(s)/V-optimality] to optimize precision of model predictions within specific E-R surface regions.

Main Results:

  • Optimal designs yielded unbiased estimates and substantially improved result accuracy over typical designs.
  • Achieved up to 7832% improvement in efficiency and 96.6% in overall parameter precision.
  • Increased the probability of accurately identifying the optimal dose-combination from 71% to 91% using the compound criterion.

Conclusions:

  • Optimal design methodology, combined with E-R analyses, is a valuable tool for dose allocation in combination drug studies.
  • This approach enhances the precision and efficiency of dose-finding studies for drug combinations.