![nonmem nonmem](https://slideplayer.com/slide/4538791/15/images/3/Introduction+to+NONMEM.jpg)
Upon successful NONMEM execution, all relevant tab files are created in this directory.ĬWRES calculation in NONMEM 6 is accomplished by calling R within SAS the COMP.R script (Xpose) calculates the CWRES tab file assuming the NONMEM 6 control stream contains the necessary arrays (HH, GG etc) to output the CWTAB.est or derive file (not required in NONMEM 7). The PIPE command writes the output from the command prompt into the SAS log to aid debugging NONMEM. The PIPE command and FILENAME is used in SAS to run NONMEM. The script changes the directory as specified using the X command. Users must define environment variables including the path of the NONMEM executable. The NM_SAS script runs NONMEM and performs the user-specified post-processing (compatible with NONMEM 5, 6 or 7). Templates for fixed format input files are created to import data into the SAS script. Methods: SAS scripts create NONMEM ready datasets for single and multiple analytes, and various input regimens. We have created a SAS-based environment to assemble NONMEM datasets from template input files, perform data checking, manage NONMEM runs, summarize run output within and across projects, and provide flexible post-processing including the management of scripts written in other 4th generation languages and compilers (R, FORTRAN, etc) Although SAS offers an excellent platform for these tasks, it has often been excluded from such analyses because the user community is not as invested with SAS, cost, and previously inferior graphics to other algorithms. Objectives: While the NONMEM algorithm remains the centerpiece of population analysis workflow, data assembly, pre and post processing are functions typically handled outside of NONMEM.