An R package for exploring and reporting pharmacometric analyses. 

The toolkit showcases our emphasis on programmatic information processing, for source-to-finish traceability.  It reflects decades of accumulated expertise in the efficient transformation of model inputs and outputs.  Especially relevant is our experience with PsN, a popular public interface to NONMEM.  You’ll find functions to harvest all the most important NONMEM outputs, helping you build and compare model results systematically.  Loaded also with classic data manipulation functions, relevant statistical summaries, and functions for specialized plots such as visual predictive checks (VPCs).  Much of the reporting functionality is oriented toward generating beautiful, flexible, and traceable output for LaTeX PDFs.  This package plays the role of integrator on our workbench, and is always available for your use as well.

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Argo is a command line tool that works from the command prompt, powershell, or terminal windows on Windows, Linux, and MacOS.  Argo manages and runs docker images to provide access to customized R environments.  The images come with preconfigured R […]


An R package for building pharmacometric data sets.  PMDatR distills decades of expert knowledge regarding the intricate needs of pharmacometric analysis datasets.   PMDatR builds on top of popular R packages such as dplyr[1] and tidyr[2], so much of the syntax is well known […]


Non-compartmental analysis (NCA) is a subdivision within pharmacokinetics (PK) that calculates PK parameters without deciding on a particular compartmental model and with minimal prior assumptions. qPharmetra has developed the open source R package qpNCA package. It performs all essential PK […]


R datasets of modest size are routinely stored as flat files and retrieved as data frames. The classic storage formats (comma delimited, tab delimited) do not have obvious mechanisms for storing data about the data: i.e., metadata such as column […]

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We are over 20 scientists with extensive experience located in the US and Europe. We work closely together and share knowledge to help our clients make better decisions.


Our succes in integrating information into models that generate unique insights, allowing executives to make better drug development decisions, is reflected in our gold-standard research publications.

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