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Complex Bayesian Modeling Workflows Encoding and Execution Made Easy With a Novel WinBUGS Plugin of the Drug Disease Model Resources Interoperability Framework

机译:使用药物疾病模型资源互操作性框架的新型WinBUGS插件,轻松进行复杂的贝叶斯建模工作流编码和执行

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The Drug Disease Model Resources (DDMoRe) Interoperability Framework (IOF) enables pharmacometric model encoding and execution via Model Description Language (MDL) and R language, through the ddmore package. Through its components and converter plugins, the IOF can execute pharmacometric tasks using different target tools, starting from a single MDL‐encoded model. In this article, we present the WinBUGS plugin and show how its integration in the IOF enables an easy implementation of complex Bayesian workflows. We selected a published diabetes‐linked study as a real‐world example, in which two inter‐related models are used to estimate insulin secretion rate in response to a glucose stimulus from intravenous glucose tolerance test (IVGTT) data. This model was implemented following different approaches to propagate uncertainty, via diverse IOF target tools (NONMEM, WinBUGS, PsN, and Xpose). The developed software supports a plethora of pharmacokinetic/pharmacodynamic (PK/PD) modeling features. It provides solutions to reproducibility and interoperability issues in Bayesian modeling, and facilitates the difficult encoding of complex PK/PD models in WinBUGS.
机译:药物疾病模型资源(DDMoRe)互操作性框架(IOF)通过ddmore软件包通过模型描述语言(MDL)和R语言启用药理模型编码和执行。通过其组件和转换器插件,IOF可以从单个MDL编码模型开始,使用不同的目标工具执行药理任务。在本文中,我们介绍了WinBUGS插件,并演示了如何将其集成到IOF中以轻松实现复杂的贝叶斯工作流程。我们选择了一个已发表的与糖尿病相关的研究作为真实示例,其中两个相互关联的模型用于根据静脉葡萄糖耐量试验(IVGTT)数据对葡萄糖刺激做出的胰岛素分泌率估算。该模型是通过不同的IOF目标工具(NONMEM,WinBUGS,PsN和Xpose)采用以下方法传播不确定性的。开发的软件支持大量的药代动力学/药效学(PK / PD)建模功能。它为贝叶斯建模中的可重复性和互操作性问题提供了解决方案,并简化了WinBUGS中复杂PK / PD模型的困难编码。

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