NONMEM VERSION-III IMPLEMENTATION ON A VAX 9000 - A DCL PROCEDURE FORSINGLE-STEP EXECUTION AND THE UNREALIZED ADVANTAGE OF A VECTORIZING FORTRAN COMPILER

There is great interest within the FDA, academia, and the pharmaceutic al industry to provide more detailed information about the time course of drug concentration and effect in subjects receiving a drug as part of their overall therapy. Advocates of this effort expect the eventua l goal of these endeavors to provide labeling which reflects the exper ience of drug administration to the entire population of potential rec ipients. The set of techniques which have been thus far applied to thi s task has been defined as population approach methodologies. While a consensus view on the usefulness of these techniques is not likely to be formed in the near future, most pharmaceutical companies or individ uals who provide kinetic/dynamic support for drug development programs are investigating population approach methods. A major setback in thi s investigation has been the shortage of computational tools to analyz e population data. One such algorithm, NONMEM, supplied by the NONMEM Project Group of the University of California, San Francisco has been widely used and remains the most accessible computational tool to date . The program is distributed to users as FORTRAN 77 source code with i nstructions for platform customization. Given the memory and compiler requirements of this algorithm and the intensive matrix manipulation r equired for run convergence and parameter estimation, this program's p erformance is largely determined by the platform and the FORTRAN compi ler used to create the NONMEM executable. Benchmark testing on a VAX 9 000 with Digital's FORTRAN (v. 1.2) compiler suggests that this is an acceptable platform. Due to excessive branching within the loops of th e NONMEM source code, the vector processing capabilities of the KV900- AA vector processor actually decrease performance. A DCL procedure is given to provide single step execution of this algorithm.