NONLINEAR MIXED EFFECTS MODELS IN PHARMACOKINETICS

纵向或重复测量分析的非线性模型 数据一直是生物统计学研究的热点。 生物学， 临床试验，尤其是药物计量学应用， 推动了这项研究。一般来说，个人作为抽样 单位，以及相同或相关结局指标的重复测量 在连续的时间点收集。 在一个 个体使用固定效应和随机误差建模， 随机系数用于模拟个体之间的变异性。 通常只对大量个体进行几次重复测量 因此，需要采用汇总估计方法。 在 制药行业关注的主要是非线性 药物浓度的房室模型。 我们建议将最近和正在进行的进展，非线性混合 将效果建模集成到S-PLUS中的综合软件中。 专门将这款软件应用于药物计量竞技场。 我们提出了一个 用于分析药理学数据的综合模块， 预定义模型库，易于使用的图标图形用户 为房室模型和扩展模型设计的界面 诊断统计。 在开发这个软件的过程中，我们 建议从以下几个领域商业化实施新模式： 非线性混合效应模型的研究现状。 建议的商业应用 在所有拥有统计学学位或 生物统计学应用于制药行业， 药物计量学模型是非常重要的。 更多数量的 药理学家在同一领域工作。建议的模块提供 令人兴奋的新尺寸，它有许多易于使用的功能， 使其受到用户的欢迎。MathSoft打算瞄准 生物医药和生物制药市场。每个市场 代表着成千上万的潜在用户。

Nonlinear models for the analysis of longitudinal or repeated measures data have been an area of intense biostatistical research. Biological, clinical trial, and especially pharmacometric applications have largely driven this research. Typically the individual serves as the sampling unit, and repeated measurements of the same or related outcome measures are gathered at successive time points. Variability within an individual is modeled using fixed effects and random errors, while random coefficients are used to model variability between individuals. Often only a few repeated measurements on a large number of individuals are measured, so pooled estimation methods are required. In the pharmaceutical industry concern is primarily with the nonlinear compartmental modeling of drug concentrations. We propose to incorporate recent and ongoing advances in nonlinear mixed effects modeling into comprehensive software integrated into S-PLUS. Specializing this software to the pharmacometric arena. We propose a comprehensive module for the analysis of pharmacometric data containing a library of predefined models, an easy to use iconic graphical user interface designed for compartmental modeling, and extensive model diagnostics statistics. In the process of building this software, we propose to commercially implement new models from several areas of current research in nonlinear mixed effects modeling. PROPOSED COMMERCIAL APPLICATION A large percentage of all graduates with degrees in statistics or biostatistics are employed in the pharmaceutical industry where pharmacometric models are of great importance. A much larger number of pharmacologists work in the same area. The proposed module offers exciting new dimensions and it has many ease-of-use features that will make it quite popular with users. MathSoft intends to target the biomedical and biopharmaceutical markets. Each of these markets represents tens of thousands of potential users.