Hi All,
I am very pleased to announce that PopED 0.1.2 is available from CRAN. PopED
is a tool that computes optimal experimental designs for both population and
individual studies based on nonlinear mixed-effect models. Often this is based
on a computation of the Fisher Information Matrix (FIM).
Get the latest version by running at your R command prompt:
install.packages("PopED")
New for this release:
* An updated model_prediction() function to allow for creation of NONMEM
datasets with user defined or optimized designs. This is useful for testing
optimized designs via PsN's ( http://psn.sf.net) SSE tool, for example.
* Added new examples to the system.file("examples",package="PopED")
directory of the PopED installation including
* evaluation and optimization of a one-target quasi-steady-state target
mediated drug disposition model (TMDD)
* How to write compiled model code for 10-100 times speed-up of
calculation time.
* Improvements in the computation of the global design criteria “ED" via
the Laplace approximation.
* Various small bug fixes.
Please see the release
https://github.com/andrewhooker/PopED/releases/tag/v0.1.2 for a complete
list of changes.
More information about PopED can be found at http://poped.sourceforge.net.
Best regards
Andrew
Andrew Hooker, Ph.D.
Associate Professor of Pharmacometrics
Dept. of Pharmaceutical Biosciences
Uppsala University
Box 591, 751 24, Uppsala, Sweden
Phone: +46 18 471 4355
Mobile: +46 768 000 725
http://www.farmbio.uu.se/research/researchgroups/pharmacometrics/