Dose [-concentration]-effect relationships can be obtained by fitting a predictive pharmacokinetic (PK)-pharmacodynamic (PD) model to both concentration and effect observations. Either a model can befit simultaneously to all the data ("simultaneous" method), or first a model can befit to the PK data and then a model can be fit to the PD data, conditioning in some way on the PK data or on the estimates of the PK parameters ("sequential" method). Using simulated data, we compare the performance of the simultaneous method with that of three sequential method variants with respect to computation time, estimation precision, and inference. Using NONMEM, under various study designs, observations of one type of PK and one type of PD response from different numbers of individuals were simulated according to a one-compartment PK model and direct Emax PD model, with parameters drawn from an appropriate population distribution. The same PK and PD models were fit to these observations using simultaneous and sequential methods. Performance measures include computation time,fraction of cases for which estimates are successfully obtained, precision of PD parameter estimates, precision of PD parameter standard error estimates, and type-I error rates of a likelihood ratio test. With the sequential method, computation time is less, and estimates are more likely to be obtained. Using the First Order Conditional Estimation (FOCE) method, a sequential approach that conditions on both population PK parameter estimates and PK data, estimates PD parameters and their standard errors about as well as the "gold standard" simultaneous method, and saves about 40% computation time. Type-I error rates of likelihood ratio test for both simultaneous and sequential approaches are close to the nominal rates.

中文翻译：

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总体PK / PD数据的同时分析与顺序分析I：最佳情况。

通过将预测药代动力学（PK）-药效学（PD）模型拟合到浓​​度和效应观察值，可以获得剂量[浓度]-效应关系。一个模型可以同时适合所有数据（“同时”方法），或者首先一个模型可以适合PK数据，然后一个模型可以适合PD数据，以某种方式对PK数据或条件进行调整。 PK参数的估计值（“顺序”方法）。使用模拟数据，我们在计算时间，估计精度和推断方面比较了同时方法和三个顺序方法变体的性能。在各种研究设计下，使用NONMEM，根据一室PK模型和直接Emax PD模型，并从适当的人口分布中提取参数，模拟了来自不同数量个体的一种PK和一种PD反应的观察结果。使用同步和顺序方法，将相同的PK和PD模型拟合到这些观察值。性能度量包括计算时间，成功获得估计的情况的分数，PD参数估计的精度，PD参数标准误差估计的精度以及似然比测试的I类错误率。使用顺序方法，计算时间更少，并且更可能获得估计。使用一阶条件估计（FOCE）方法，这是一种以总体PK参数估计和PK数据为条件的顺序方法，估计PD参数及其标准误差以及“黄金标准”同步方法，可节省约40％的计算时间。同时进行和顺序进行的似然比测试的I型错误率都接近标称率。