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首页> 外文期刊>The Journal of Clinical Pharmacology: Official Journal of the American College of Clinical Pharmacology >Using multiple drug exposure levels to optimize power in pharmacogenetic trials.
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Using multiple drug exposure levels to optimize power in pharmacogenetic trials.

机译:在药物遗传学试验中使用多种药物暴露水平来优化功效。

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摘要

Large-scale pharmacogenetic trials testing tens to hundreds of thousands of single-nucleotide polymorphisms (SNPs) will become possible in the near future given rapidly decreasing costs of genotyping. Devising optimal designs for these trials will be a significant challenge. The author demonstrates how the level of drug exposure may strongly affect the power to detect true associations between genetic polymorphisms and drug response. An analytic model of drug response is described that is used to simulate pharmacogenetic trials. Analytical and numerical sensitivity analyses are performed on the model to demonstrate possible exposure-sensitivity behaviors. This model shows that the power to detect an association can be a nonlinear, nonmonotonic function of drug exposure. This model is further investigated using two clinical trial designs. The conclusion is that trial designs that use more than one drug exposure or dose will have an increased likelihood of discovering statistically significant pharmacogenetic associations.
机译:由于基因分型成本的迅速下降,在不久的将来测试成千上万的单核苷酸多态性(SNP)的大规模药物遗传学试验将成为可能。为这些试验设计最佳设计将是一项重大挑战。作者证明了药物暴露水平可能如何强烈影响检测基因多态性与药物反应之间真正关联的能力。描述了一种用于模拟药物遗传学试验的药物反应分析模型。在模型上进行了分析和数值敏感性分析,以证明可能的暴露敏感性行为。该模型表明,检测关联的能力可能是药物暴露的非线性,非单调函数。使用两个临床试验设计进一步研究了该模型。结论是,使用不止一种药物暴露量或剂量的试验设计将更有可能发现具有统计学意义的药物遗传学关联。

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