PDx-Pop 4.20 Update
December 21, 2010
William J. Bachman, Ph.D.
Updating PDx-Pop 4.x to PDx-Pop 4.20:
1. Quit the PDx-Pop program if currently running.
2. Copy to a backup folder any of the files with identical names in
your PDx-Pop installation directory (if you installed PDx-Pop to the
default directory, the directory is c:\pdxpop4) as those found in the
ftp folder (ftp://ftp.globomaxnm.com/Public/pdxpop/PDx-Pop4.2/).
3. Download all the files found at
ftp://ftp.globomaxnm.com/Public/pdxpop/PDx-Pop4.2/
<ftp://ftp.globomaxnm.com/Public/pdxpop/PDx-Pop4.2/> to your PDx-Pop 4
installation directory. Move the files 501.csv and wamexample.ctl to
the example1 directory under the installation directory.
4. Start the program and you are now ready to use PDx-Pop 4.20.
Update 4.20 is cumulative with update 4.10 (it contains the updates
found in 4.10). There is no need to precede update 4.20 with update
4.10 if you have not already updated to 4.10.
Software Bugs fixed in PDx-Pop 4.20:
1. A bug was corrected that affected all runs that used multiple
simultaneous threads including selecting multiple CPU's from the
Model/Run Tab or Evaluation Methods that used multiple simultaneous
threads by default including Multiple MCMC Runs and Initial Parameters
Variation. If the control files contained multiple $TABLE records, the
runs would fail and PDx-Pop would "hang" (the program would stop
functioning and could only be closed from the Windows Task manager).
The bug fix corrects the bug and also limits the number of multiple
simultaneous threads to the total number of CPU's available on the
system to prevent excess memory use which could lead to skipped runs.
2. Bugs were fixed that caused Bootstrap, Multiple MCMC chains, and
Initial Parameter Variation evaluation methods to fail on Linux and Mac
OS X.
New features have been added to PDx-Pop 4 in the new updated version,
PDx-Pop 4.20:
Wald Approximation Method (WAM) Analysis
Introduction to WAM Analysis
The Wald Approximation Method (WAM) as implemented in PDx-Pop is based
upon the publication by KG Kowalski and MM Hutmacher, "Efficient
Screening of Covariates in Population Models Using Wald's Approximation
to the Likelihood Ratio Test.", JPP 2001;28:253-275.
The WAM is an efficient covariate search algorithm that exploits
information contained in a full model fit (all covariates included
simultaneously) to guide selection of competing reduced models for
evaluation. The main goal of any covariate search algorithm is to find
a parsimonious model for prediction. The WAM generally requires fewer
model runs than stepwise procedures to identify a final reduced model
and provides a set of competing parsimonious models.
See the ReleaseNotes.pdf file for more information.
PDx-Pop 4.20 Update Now Available
Hi everyone
I am trying to build a model for a multiple dose oral drug. I am not sure
how to arrange my input data file. If anyone has done that could he please
send me his data file or part of it just to see how is the data arranged and
what I need to include.
Regards
Mariam
Quoted reply history
On 22 December 2010 20:54, Bachman, William <[email protected]>wrote:
> PDx-Pop 4.20 Update
>
> December 21, 2010
>
> William J. Bachman, Ph.D.
>
>
>
> *Updating PDx-Pop 4.x to PDx-Pop 4.20:*
>
> 1. Quit the PDx-Pop program if currently running.
> 2. Copy to a backup folder any of the files with identical names in
> your PDx-Pop installation directory (if you installed PDx-Pop to the
> default
> directory, the directory is c:\pdxpop4) as those found in the ftp folder (
> ftp://ftp.globomaxnm.com/Public/pdxpop/PDx-Pop4.2/).
> 3. Download all the files found at
> ftp://ftp.globomaxnm.com/Public/pdxpop/PDx-Pop4.2/ to your PDx-Pop 4
> installation directory. Move the files 501.csv and wamexample.ctl to
> the example1 directory under the installation directory.
> 4. Start the program and you are now ready to use PDx-Pop 4.20.
>
> Update 4.20 is cumulative with update 4.10 (it contains the updates found
> in 4.10). There is no need to precede update 4.20 with update 4.10 if you
> have not already updated to 4.10.
>
>
>
> *Software Bugs fixed in PDx-Pop 4.20:*
>
> 1. A bug was corrected that affected all runs that used multiple
> simultaneous threads including selecting multiple CPU’s from the Model/Run
> Tab or Evaluation Methods that used multiple simultaneous threads by
> default
> including Multiple MCMC Runs and Initial Parameters Variation. If the
> control files contained multiple $TABLE records, the runs would fail and
> PDx-Pop would “hang” (the program would stop functioning and could
> only be closed from the Windows Task manager). The bug fix corrects
> the bug and also limits the number of multiple simultaneous threads to the
> total number of CPU’s available on the system to prevent excess memory use
> which could lead to skipped runs.
> 2. Bugs were fixed that caused Bootstrap, Multiple MCMC chains, and
> Initial Parameter Variation evaluation methods to fail on Linux and Mac OS
> X.
>
> *New features have been added to PDx-Pop 4 in the new updated version,
> PDx-Pop 4.20:*
>
>
>
> Wald Approximation Method (WAM) Analysis
>
>
>
> Introduction to WAM Analysis
>
>
>
> The Wald Approximation Method (WAM) as implemented in PDx-Pop is based upon
> the publication by KG Kowalski and MM Hutmacher, “Efficient Screening of
> Covariates in Population Models Using Wald’s Approximation to the Likelihood
> Ratio Test.”, JPP 2001;28:253-275.
>
>
> The WAM is an efficient covariate search algorithm that exploits
> information contained in a full model fit (all covariates included
> simultaneously) to guide selection of competing reduced models for
> evaluation. The main goal of any covariate search algorithm is to find a
> parsimonious model for prediction. The WAM generally requires fewer model
> runs than stepwise procedures to identify a final reduced model and provides
> a set of competing parsimonious models.
>
> See the ReleaseNotes.pdf file for more information.
>
>
I suggest looking at the manuals, particularly Guide V, and the examples
supplied with NONMEM 7. (e.g. c:\nm7\examples and c:\nm7\run).
Quoted reply history
________________________________
From: [email protected] on behalf of Sarah Shahen
Sent: Fri 12/24/2010 7:04 AM
To: [email protected]
Subject: Re: [NMusers] PDx-Pop 4.20 Update Now Available
Hi everyone
I am trying to build a model for a multiple dose oral drug. I am not sure how
to arrange my input data file. If anyone has done that could he please send me
his data file or part of it just to see how is the data arranged and what I
need to include.
Regards
Mariam
On 22 December 2010 20:54, Bachman, William <[email protected]> wrote:
PDx-Pop 4.20 Update
December 21, 2010
William J. Bachman, Ph.D.
Updating PDx-Pop 4.x to PDx-Pop 4.20:
1. Quit the PDx-Pop program if currently running.
2. Copy to a backup folder any of the files with identical names
in your PDx-Pop installation directory (if you installed PDx-Pop to the default
directory, the directory is c:\pdxpop4) as those found in the ftp folder
(ftp://ftp.globomaxnm.com/Public/pdxpop/PDx-Pop4.2/).
3. Download all the files found at
ftp://ftp.globomaxnm.com/Public/pdxpop/PDx-Pop4.2/
<ftp://ftp.globomaxnm.com/Public/pdxpop/PDx-Pop4.2/> to your PDx-Pop 4
installation directory. Move the files 501.csv and wamexample.ctl to the
example1 directory under the installation directory.
4. Start the program and you are now ready to use PDx-Pop 4.20.
Update 4.20 is cumulative with update 4.10 (it contains the updates
found in 4.10). There is no need to precede update 4.20 with update 4.10 if
you have not already updated to 4.10.
Software Bugs fixed in PDx-Pop 4.20:
1. A bug was corrected that affected all runs that used multiple
simultaneous threads including selecting multiple CPU's from the Model/Run Tab
or Evaluation Methods that used multiple simultaneous threads by default
including Multiple MCMC Runs and Initial Parameters Variation. If the control
files contained multiple $TABLE records, the runs would fail and PDx-Pop would
"hang" (the program would stop functioning and could only be closed from the
Windows Task manager). The bug fix corrects the bug and also limits the number
of multiple simultaneous threads to the total number of CPU's available on the
system to prevent excess memory use which could lead to skipped runs.
2. Bugs were fixed that caused Bootstrap, Multiple MCMC chains,
and Initial Parameter Variation evaluation methods to fail on Linux and Mac OS
X.
New features have been added to PDx-Pop 4 in the new updated version,
PDx-Pop 4.20:
Wald Approximation Method (WAM) Analysis
Introduction to WAM Analysis
The Wald Approximation Method (WAM) as implemented in PDx-Pop is based
upon the publication by KG Kowalski and MM Hutmacher, "Efficient Screening of
Covariates in Population Models Using Wald's Approximation to the Likelihood
Ratio Test.", JPP 2001;28:253-275.
The WAM is an efficient covariate search algorithm that exploits
information contained in a full model fit (all covariates included
simultaneously) to guide selection of competing reduced models for evaluation.
The main goal of any covariate search algorithm is to find a parsimonious model
for prediction. The WAM generally requires fewer model runs than stepwise
procedures to identify a final reduced model and provides a set of competing
parsimonious models.
See the ReleaseNotes.pdf file for more information.