PD modeling: What is the most efficient approach to transfer data?

From: musor000@optonline.net Subject: [NMusers] PD modeling: What is the most efficient approach to transfer data? Date: Mon, 19 Dec 2005 21:14:22 -0500 Hello Nonmem Users, I am working on a PD model. Usually, it is not recommended to combine PK and PD models. First, it is necessary to develop a PK model. Then predicted values can be used in a PD model. What is the most efficient way to transfer data from PK to PD model? I simply took output PK dataset, modified it, and used it in a PD model. It was time consuming. Is there another way to transfer data (supermodel or something else)? Frequently, it is necessary to have more predicted timepoints than observed timepoints. One way to get predicted values is to create missing observations in an input dataset. This approach is time consuming and prone to errors. Is there a more simple way to get the predicted values? Kind regards, Pavel