[NMusers] December 31st, Early Bird registration deadline QSPC2020

[Krekels, E.H.J.]

Dear colleagues,

With Christmas and New Year's quickly approaching, we would like to remind you 
of the deadline for early bird registration for Quantitative Systems 
Pharmacology Conference 2020 (QSPC2020), which is December 31st. For 
registration click here: https://www.qspc.eu/qspc2020/subscribe.

The website also contains a link to an app for uploading poster abstracts. The 
deadline for these abstracts is January 31st: 
https://www.qspc.eu/qspc2020/author

The focus of QSPC2020 will be on emerging computational and experimental 
approaches in the field of quantitative systems pharmacology and 
mechanism-based or physiologically-based pharmacokinetics and pharmacodynamics. 
The meeting will include plenary lectures by both established and young 
scientists, poster presentations, and ample opportunities for networking. More 
information regarding a.o. the program, satellite events, travel, accommodation 
etc. is available on our website: 
https://www.qspc.eu.

Happy holidays and we hope to see many of you in Leiden in April,

Liesbeth de Lange, Coen van Hasselt, and Elke Krekels

[NMusers] 2 Advanced NONMEM courses given in both US and Europe in 2020

[Mats Karlsson]

Dear colleagues,

We are pleased to offer 2 courses “Advanced methods for population model 
building, evaluation and usage in NONMEM” and “Pharmacometric modeling of 
composite score outcomes” in Lambertville, New Jersey March 9-11 and March 
12-13, 2020. The two courses will also be given in Uppsala, Sweden on May 11-13 
and May 14-15, respectively. For more information and registration see below 
and at http://www.uppsala-pharmacometrics.com.

Advanced methods for population model building, evaluation and usage in NONMEM

Pharmacometric modeling has become a pillar in model informed drug development 
(MIDD). With this comes expectations with respect to quality, efficiency, 
transparency and innovation in the implementation of the modeling and 
decision-making process. In this course we will present methods that will help 
make model building of standard problems more efficient and improve the final 
product. Further, it will give modelers a larger toolset of diagnostics and 
model components when it comes to development of models for challenging 
situations. Automated procedures recently developed for PsN & R facilitates a 
comprehensive assessment of a model and tailored functionality allow 
command-line transformations of models.

Mats Karlsson and Andrew Hooker will give a 2.5-day course on “Advanced methods 
for population model building, evaluation and usage in NONMEM”. The course 
presents strategies for model building and improvement, the latest methods for 
model evaluation, as well as strategies to consider when utilizing models for 
model-informed drug development.

The course consists of both lectures and hands-on computer exercises applying 
the methods discussed.  This hands-on material is based on the most recent 
developments from NONMEM 7.4, PsN and Xpose.  Participants get a vast amount of 
hands-on examples, code, code snippets and lecture material that can be useful 
on a daily basis.

If you want to learn how to use tools and methods for fast, efficient and 
comprehensive model building, evaluation and usage, come join us in March!

Topics covered:

  *   Model building and model components
 *   Overall modeling strategies
 *   Random effects models (standard and extended)
 *   Residual error models (standard and extended)
 *   Mixture modeling
 *   Handling censored data (e.g. BQL and dropout)
 *   Covariate models and model building
 *   Estimation methods and settings
  *   Model evaluation
 *   Prediction- and Residual-based
 *   Empirical Bayes Estimate (EBE) and sampling-based diagnostics
 *   Simulation and Simulation-Evaluation/Estimation-Based
 *   Outlier and influential individual diagnostics
 *   Automated evaluations
 *   Covariate model focused diagnostics
 *   Parameter uncertainty (bootstrap, SIR, COV)
  *   To consider when applying models for informed drug development
 *   Bias assessment
 *   Power and Type I error
 *   Model averaging

Pharmacometric modeling of composite score outcomes

The EDSS in multiple sclerosis, the ACR scale for rheumatoid arthritis, or the 
MDS-UPDRS in Parkinson’s disease; these composite scales are as diverse as the 
diseases they are designed to measure. Composite scores also arise through 
patient-reported outcomes (PROs) that aim at measuring symptom status, physical 
function, mental health, and other measures important to patients. The wide 
range of novel pharmacometric models and approaches developed during the past 
years are a testament to the growing importance of this data type. This course 
will cover recent innovations and provide participants with a rich set of tools 
for analyzing composite scores in a wide variety of therapeutic areas. The 
course will illustrate how one can leverage finely grained item-level 
information but also how summary score data are most efficiently utilized. 
Throughout the course, questions of both model building and model-use will be 
discussed and presented in an interactive format including hands-on exercises.

Mats Karlsson and Sebastian Ueckert will give a 2-day course on “Pharmacometric 
modeling of composite score outcomes”. The course covers data aspects, model 
building, evaluation and use for composite score outcomes.

Topics covered:

  *   Modeling data with item-level resolution using item response theory
  *   Modeling total score data either as continuous or discrete data under a 
variety of models
  *   Models for responder analysis to handle, e.g., ACR20/50/70 and PASI70/90
  *   Pharmacometric modeling of Patient Reported Outcomes (PROs).
  *   Model-based optimization of clinical trials with composite score outcomes
Intended course participants:
The course is designed for those who have a good working knowledge of 
pharmacometric analysis with experience in performing NONMEM analyses and/or 
have attended a NONMEM basic workshop.

Best regards,
Mats Karlsson








När du har kontakt med oss på Uppsala univer

[NMusers] Use AND to ignore rows for input dataset

[Mark Tepeck]

Hi Colleagues,

Although there are many workarounds to manage the input datasets for
NONMEM,  use of IGNORE would be a very handy solution. However, I am
surprised to see that AND is not supported by NONMEM. e.g.
IGNORE=(CMT.EQ.1, AND CMT.EQ.2 ) would throw an error. In contrast, NONMEM
use OR  for IGNORE=(CMT.EQ.1, CMT.EQ.2 ) by default, which is quite
different for the common practice of software.

I am wondering if the AND feature has been or will be implemented in the
last/future NONMEM version.

Thank you,

Mark

Re: [NMusers] Use AND to ignore rows for input dataset

[Sebastien Bihorel]

I would second that feature request!

From: owner-nmus...@globomaxnm.com  on behalf of 
Mark Tepeck 
Sent: Monday, December 16, 2019 15:16
To: Nmusers 
Subject: [NMusers] Use AND to ignore rows for input dataset

Hi Colleagues,

Although there are many workarounds to manage the input datasets for NONMEM,  
use of IGNORE would be a very handy solution. However, I am surprised to see 
that AND is not supported by NONMEM. e.g.  IGNORE=(CMT.EQ.1, AND CMT.EQ.2 ) 
would throw an error. In contrast, NONMEM use OR  for IGNORE=(CMT.EQ.1, 
CMT.EQ.2 ) by default, which is quite different for the common practice of 
software.

I am wondering if the AND feature has been or will be implemented in the 
last/future NONMEM version.

Thank you,

Mark

RE: [NMusers] Use AND to ignore rows for input dataset

[Bauer, Robert]

Guide VIII suggests the following:

Suppose it is desired that records be dropped that satisfy the logical ".AND." 
of several conditions. This can be implemented by using an ACCEPT list with the 
negations of the conditions. For example, suppose that records to be ignored 
are those having GEN=1 .AND. AGE > 60. This may be done as follows:
ACCEPT=(GEN.NE.1,AGE.LE.60)

Robert J. Bauer, Ph.D.
Senior Director
Pharmacometrics R&D
ICON Early Phase
820 W. Diamond Avenue
Suite 100
Gaithersburg, MD 20878
Office: (215) 616-6428
Mobile: (925) 286-0769
robert.ba...@iconplc.com
www.iconplc.com

From: owner-nmus...@globomaxnm.com  On Behalf Of 
Sebastien Bihorel
Sent: Monday, December 16, 2019 12:39 PM
To: Mark Tepeck ; Nmusers 
Subject: Re: [NMusers] Use AND to ignore rows for input dataset

I would second that feature request!

From: owner-nmus...@globomaxnm.com 
mailto:owner-nmus...@globomaxnm.com>> on behalf 
of Mark Tepeck mailto:mark.tep...@gmail.com>>
Sent: Monday, December 16, 2019 15:16
To: Nmusers mailto:nmusers@globomaxnm.com>>
Subject: [NMusers] Use AND to ignore rows for input dataset

Hi Colleagues,

Although there are many workarounds to manage the input datasets for NONMEM,  
use of IGNORE would be a very handy solution. However, I am surprised to see 
that AND is not supported by NONMEM. e.g.  IGNORE=(CMT.EQ.1, AND CMT.EQ.2 ) 
would throw an error. In contrast, NONMEM use OR  for IGNORE=(CMT.EQ.1, 
CMT.EQ.2 ) by default, which is quite different for the common practice of 
software.

I am wondering if the AND feature has been or will be implemented in the 
last/future NONMEM version.

Thank you,

Mark

ICON plc made the following annotations.
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are not the intended recipient, you are hereby notified that any disclosure, 
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prohibited. If
you have received this e-mail transmission in error, please reply to the 
sender, so that ICON plc can arrange for proper delivery, and then please 
delete the message.

Thank You,

ICON plc
South County Business Park
Leopardstown
Dublin 18
Ireland
Registered number: 145835

Re: [NMusers] Use AND to ignore rows for input dataset

[Sebastien Bihorel]

Since nowadays most datasets include a header line, IGNORE=@ (or something 
along those lines) is almost always used in control streams. Since ACCEPT and 
IGNORE cannot be used in the same $DATA record, the suggested technique is 
seldom usable in my experience.

From: owner-nmus...@globomaxnm.com  on behalf of 
Bauer, Robert 
Sent: Monday, December 16, 2019 17:39
To: Nmusers 
Subject: RE: [NMusers] Use AND to ignore rows for input dataset


Guide VIII suggests the following:



Suppose it is desired that records be dropped that satisfy the logical ".AND." 
of several conditions. This can be implemented by using an ACCEPT list with the 
negations of the conditions. For example, suppose that records to be ignored 
are those having GEN=1 .AND. AGE > 60. This may be done as follows:

ACCEPT=(GEN.NE.1,AGE.LE.60)



Robert J. Bauer, Ph.D.

Senior Director

Pharmacometrics R&D

ICON Early Phase

820 W. Diamond Avenue

Suite 100

Gaithersburg, MD 20878

Office: (215) 616-6428

Mobile: (925) 286-0769

robert.ba...@iconplc.com

www.iconplc.com



From: owner-nmus...@globomaxnm.com  On Behalf Of 
Sebastien Bihorel
Sent: Monday, December 16, 2019 12:39 PM
To: Mark Tepeck ; Nmusers 
Subject: Re: [NMusers] Use AND to ignore rows for input dataset



I would second that feature request!



From: owner-nmus...@globomaxnm.com 
mailto:owner-nmus...@globomaxnm.com>> on behalf 
of Mark Tepeck mailto:mark.tep...@gmail.com>>
Sent: Monday, December 16, 2019 15:16
To: Nmusers mailto:nmusers@globomaxnm.com>>
Subject: [NMusers] Use AND to ignore rows for input dataset



Hi Colleagues,



Although there are many workarounds to manage the input datasets for NONMEM,  
use of IGNORE would be a very handy solution. However, I am surprised to see 
that AND is not supported by NONMEM. e.g.  IGNORE=(CMT.EQ.1, AND CMT.EQ.2 ) 
would throw an error. In contrast, NONMEM use OR  for IGNORE=(CMT.EQ.1, 
CMT.EQ.2 ) by default, which is quite different for the common practice of 
software.



I am wondering if the AND feature has been or will be implemented in the 
last/future NONMEM version.



Thank you,



Mark


ICON plc made the following annotations.
--
This e-mail transmission may contain confidential or legally privileged 
information that is intended only for the individual or entity named in the 
e-mail address. If you are not the intended recipient, you are hereby notified 
that any disclosure, copying, distribution, or reliance upon the contents of 
this e-mail is strictly prohibited. If you have received this e-mail 
transmission in error, please reply to the sender, so that ICON plc can arrange 
for proper delivery, and then please delete the message.

Thank You,

ICON plc
South County Business Park
Leopardstown
Dublin 18
Ireland
Registered number: 145835

RE: [NMusers] Use AND to ignore rows for input dataset

[Bauer, Robert]

Sebastien:
It is not clear in the guide, but only parenthesized IGNORE and ACCEPT lists, 
such as IGNORE=(list) and ACCEPT=(list),  are incompatible.  IGNORE=c, where c 
could be any character except space, should work with IGNORE=(list) or 
ACCEPT=(list).  For example:

$DATA example1.csv ACCEPT=(CMT.EQN.1) IGNORE=@

Also, any data record starting with first non-blank character of # will always 
be ignored by NMTRAN.

Robert J. Bauer, Ph.D.
Senior Director
Pharmacometrics R&D
ICON Early Phase
820 W. Diamond Avenue
Suite 100
Gaithersburg, MD 20878
Office: (215) 616-6428
Mobile: (925) 286-0769
robert.ba...@iconplc.com
www.iconplc.com

From: Sebastien Bihorel 
Sent: Monday, December 16, 2019 5:02 PM
To: Bauer, Robert ; Nmusers 
Subject: Re: [NMusers] Use AND to ignore rows for input dataset

Since nowadays most datasets include a header line, IGNORE=@ (or something 
along those lines) is almost always used in control streams. Since ACCEPT and 
IGNORE cannot be used in the same $DATA record, the suggested technique is 
seldom usable in my experience.

From: owner-nmus...@globomaxnm.com 
mailto:owner-nmus...@globomaxnm.com>> on behalf 
of Bauer, Robert mailto:robert.ba...@iconplc.com>>
Sent: Monday, December 16, 2019 17:39
To: Nmusers mailto:nmusers@globomaxnm.com>>
Subject: RE: [NMusers] Use AND to ignore rows for input dataset


Guide VIII suggests the following:



Suppose it is desired that records be dropped that satisfy the logical ".AND." 
of several conditions. This can be implemented by using an ACCEPT list with the 
negations of the conditions. For example, suppose that records to be ignored 
are those having GEN=1 .AND. AGE > 60. This may be done as follows:

ACCEPT=(GEN.NE.1,AGE.LE.60)



Robert J. Bauer, Ph.D.

Senior Director

Pharmacometrics R&D

ICON Early Phase

820 W. Diamond Avenue

Suite 100

Gaithersburg, MD 20878

Office: (215) 616-6428

Mobile: (925) 286-0769

robert.ba...@iconplc.com

www.iconplc.com



From: owner-nmus...@globomaxnm.com 
mailto:owner-nmus...@globomaxnm.com>> On Behalf 
Of Sebastien Bihorel
Sent: Monday, December 16, 2019 12:39 PM
To: Mark Tepeck mailto:mark.tep...@gmail.com>>; Nmusers 
mailto:nmusers@globomaxnm.com>>
Subject: Re: [NMusers] Use AND to ignore rows for input dataset



I would second that feature request!



From: owner-nmus...@globomaxnm.com 
mailto:owner-nmus...@globomaxnm.com>> on behalf 
of Mark Tepeck mailto:mark.tep...@gmail.com>>
Sent: Monday, December 16, 2019 15:16
To: Nmusers mailto:nmusers@globomaxnm.com>>
Subject: [NMusers] Use AND to ignore rows for input dataset



Hi Colleagues,



Although there are many workarounds to manage the input datasets for NONMEM,  
use of IGNORE would be a very handy solution. However, I am surprised to see 
that AND is not supported by NONMEM. e.g.  IGNORE=(CMT.EQ.1, AND CMT.EQ.2 ) 
would throw an error. In contrast, NONMEM use OR  for IGNORE=(CMT.EQ.1, 
CMT.EQ.2 ) by default, which is quite different for the common practice of 
software.



I am wondering if the AND feature has been or will be implemented in the 
last/future NONMEM version.



Thank you,



Mark


ICON plc made the following annotations.
--
This e-mail transmission may contain confidential or legally privileged 
information that is intended only for the individual or entity named in the 
e-mail address. If you are not the intended recipient, you are hereby notified 
that any disclosure, copying, distribution, or reliance upon the contents of 
this e-mail is strictly prohibited. If you have received this e-mail 
transmission in error, please reply to the sender, so that ICON plc can arrange 
for proper delivery, and then please delete the message.

Thank You,

ICON plc
South County Business Park
Leopardstown
Dublin 18
Ireland
Registered number: 145835