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Cardiovascular safety assessments in the conscious telemetered dog: Utilisation of super-intervals to enhance statistical power

机译:有意识的遥测犬的心血管安全评估:利用超间隔提高统计功效

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Introduction: ICH S7A and S7B guidelines recommend the use of conscious animals for assessment of non-clinical cardiovascular safety of new chemical entities prior to testing in humans. Protocol design and data analysis techniques can affect the quality of the data produced and can therefore ultimately influence the clinical management of cardiovascular risk. It is therefore essential to have an understanding of the magnitude of changes detectable and the clinical relevance of these changes. This paper describes the utilisation of "super-intervals" to analyse and interpret data obtained from our conscious telemetered dog cardiovascular safety protocol and reports the statistical power achieved to detect changes in various cardiovascular parameters. MethodsCardiovascular data from 18 dog telemetry studies were used to calculate the statistical power to detect changes in cardiovascular parameters. Each study followed a test compound versus vehicle cross-over experimental design with 24. h monitoring (n = 4). 1 min mean raw data from each individual animal was compressed into 15 min mean data for each dose group for visualisation. Larger summary periods, or "super-intervals", were then selected to best represent any observed cardiovascular effects whilst taking into account the pharmacokinetic profile of the drug e.g. intervals of 1 to 6, 7 to 14 and 14 to 22. h post-dose. ResultsWith this methodology and study design we predict, using the median percentile that our studies have 80% power to detect the following changes: HR (±10. bpm), LV + dP/dt max (±375 mm Hg/s), MBP (± 5 mm Hg) and QTc (± 4 ms). DiscussionSuper-intervals are a simple way to handle the high degree of natural variability seen with any ambulatory cardiovascular assessment and, in our hands, result in highly statistically powered studies. The ability of this model to detect cardiovascular changes of small, but biologically relevant, magnitude enables confident decision making around the cardiovascular safety of new chemical entities.
机译:简介:ICH S7A和S7B指南建议在进行人体测试之前,使用有意识的动物评估新化学实体的非临床心血管安全性。协议设计和数据分析技术可能会影响所生成数据的质量,因此最终会影响心血管风险的临床管理。因此,必须了解可检测到的变化的幅度以及这些变化的临床相关性。本文介绍了利用“超间隔”来分析和解释从我们的有意识遥测犬心血管安全协议中获得的数据,并报告了检测各种心血管参数变化所获得的统计能力。方法采用18项狗遥测研究的心血管数据来计算检测心血管参数变化的统计能力。每项研究均遵循测试化合物与车辆交叉实验设计,并进行24小时监控(n = 4)。将来自每只动物的1分钟平均原始数据压缩为每个剂量组的15分钟平均数据以进行可视化。然后选择较大的摘要期或“超间隔”,以最好地代表观察到的任何心血管作用,同时考虑到药物的药代动力学特征,例如:给药后1至6、7至14和14至22小时的间隔。结果使用这种方法和研究设计,我们使用中位数百分比预测我们的研究具有80%的能力来检测以下变化:HR(±10。bpm),LV + dP / dt max(±375 mm Hg / s),MBP (±5毫米汞柱)和QTc(±4毫秒)。讨论超级间隔是处理任何动态心血管评估所见的高度自然变异性的简单方法,并且在我们手中,可以进行高度统计的研究。该模型能够检测出很小但与生物学相关的心血管变化,从而能够围绕新化学实体的心血管安全性做出可靠的决策。

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