Feasibility of Exposure-Response Analyses for Clinical Dose-Ranging Studies of Drug Combinations
| Autor: | Trine Meldgaard Lund, Andrew C. Hooker, Anders Strathe, Theodoros Papathanasiou, Rune Viig Overgaard |
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| Rok vydání: | 2018 |
| Předmět: |
Stochastic Processes
Dose-Response Relationship Drug Estimation theory Computer science Clinical study design Reproducibility of Results Pharmaceutical Science 030226 pharmacology & pharmacy Drug Combinations 03 medical and health sciences Identification (information) Clinical Trials Phase II as Topic 0302 clinical medicine Research Design Sample size determination Sample Size 030220 oncology & carcinogenesis Pharmacodynamics Statistics Clinical endpoint Feasibility Studies Humans Reliability (statistics) Selection (genetic algorithm) |
| Zdroj: | The AAPS Journal. 20 |
| ISSN: | 1550-7416 |
| DOI: | 10.1208/s12248-018-0226-5 |
| Popis: | The exposure-response relationship of combinatory drug effects can be quantitatively described using pharmacodynamic interaction models, which can be used for the selection of optimal dose combinations. The aim of this simulation study was to evaluate the reliability of parameter estimates and the probability for accurate dose identification for various underlying exposure-response profiles, under a number of different phase II designs. An efficacy variable driven by the combined exposure of two theoretical compounds was simulated and model parameters were estimated using two different models, one estimating all parameters and one assuming that adequate previous knowledge for one drug is readily available. Estimation of all pharmacodynamic parameters under a realistic, in terms of sample size and study design, phase II trial, proved to be challenging. Inaccurate estimates were found in all exposure-response scenarios, except for situations where no pharmacodynamic interaction was present, with the drug potency and interaction parameters being the hardest to estimate. When previous knowledge of the exposure-response relationship of one of the monocomponents is available, such information should be utilized, as it enabled relevant improvements in parameter estimation and in correct dose identification. No general trends for classification of the performance of the tested study designs across different scenarios could be identified. This study shows that pharmacodynamic interactions models can be used for the exposure-response analysis of clinical endpoints especially when accompanied by appropriate dose selection in regard to the expected drug potencies and appropriate trial size and if information regarding the exposure-response profile of one monocomponent is available. |
| Databáze: | OpenAIRE |
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