shrinkage is
identically large for both positive and negative etas) would we expect the
mean of posthoc etas to be zero.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Div. of Pharmacokinetics and Drug Therapy
Dept. of Pharmaceutical Biosciences
Faculty of Pharmacy
Uppsala
noted mean posthoc eta
significantly different from zero even when the model is correct (see
reference below for some more discussion on the "uselessness" of posthoc
etas).
http://www.aapspharmaceutica.com/search/abstract_view.asp?id=941&ct=06Abstra
cts
Best regards,
Mats
Mats Karl
cortisol in
healthy volunteers.
Br J Clin Pharmacol. 2007 Feb 28; [Epub ahead of print]
Mats Karlsson, PhD
Professor of Pharmacometrics
Div. of Pharmacokinetics and Drug Therapy
Dept. of Pharmaceutical Biosciences
Faculty of Pharmacy
Uppsala University
Box 591
SE-751 24 Uppsala
Sweden
phone +46
Dear Paul,
Thanks for the praise. I'd just like to point out that Niclas Jonsson is the
main architect around the changes - least credit should go to me.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Div. of Pharmacokinetics and Drug Therapy
Dep
Dear Mahesh,
In order for the IIV in RV to be implemented, it is necessary that you use
the INTERACTION option in $EST, even if you use the additive error.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Div. of Pharmacokinetics and Drug Therapy
Dept. of
regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Div. of Pharmacokinetics and Drug Therapy
Dept. of Pharmaceutical Biosciences
Faculty of Pharmacy
Uppsala University
Box 591
SE-751 24 Uppsala
Sweden
phone +46 18 471 4105
fax +46 18 471 4003
[EM
rds,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Div. of Pharmacokinetics and Drug Therapy
Dept. of Pharmaceutical Biosciences
Faculty of Pharmacy
Uppsala University
Box 591
SE-751 24 Uppsala
Sweden
phone +46 18 471 4105
fax +46 18 471 4003
[EMAIL PROTECTED]
_
From: [EMAIL
Dear Paul,
When using $SIM only, the AUC will be estimated based on the simulated
parameter values including the ETA's. With PRED or if you do $SIM+$EST
(without POSTHOC), the AUC will be based on parameters with ETA set to zero.
Best regards,
Mats
Mats Karlsson, PhD
Profess
Dear Paul,
When using $SIM only, the AUC will be estimated based on the simulated
parameter values including the ETA's. With PRED or if you do $SIM+$EST
(without POSTHOC), the AUC will be based on parameters with ETA set to zero.
Best regards,
Mats
Mats Karlsson, PhD
Profess
Dear Paul,
When using $SIM only, the AUC will be estimated based on the simulated
parameter values including the ETA's. With PRED or if you do $SIM+$EST
(without POSTHOC), the AUC will be based on parameters with ETA set to zero.
Best regards,
Mats
Mats Karlsson, PhD
Profess
Just to elaborate slightly on this last suggestion. If you use a $MSFI to
input your parameters, use TRUE=FINAL to use the final, as opposed to the
initial, estimates from that preceding run. If $MSFI is not used, TRUE=FINAL
has no meaning.
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
;,
"rich+sparse unbalanced design", "sparse unbalanced design". Apart from this
effect I know of no reason to expect unbalanced designs not to be robust if
the model is correctly specified.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Bio
all diagnostics based individual ETAS are less useful.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Uppsala University
Box 591
751 24 Uppsala Sweden
phone: +46 18 4714105
fax: +46 18 471 4003
-Original Message-
From: [EMAIL PROTECTED]
when these share parameters
(as PK and PD data does). Therefore the advantage of using sequential will
not be as large (if advantageous at all) compared to sequential for FO.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Uppsala Unive
+2.00E+00 4.50E+01 5.27E+00 4.74E+01 3.70E+00 7.22E+00
-3.52E+00 3.06E-02
23
+2.00E+00 6.00E+01 5.27E+00 4.74E+01 1.80E+00 1.61E+00
1.89E-01 3.74E-02
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Uppsala
magnitude and will typically be:
%RV expected AUC difference
10 0.50%
20 2%
30 5%
40 9%
50 14%
70 29%
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Uppsala
ifferent if they are calculated in this way. I expect that if the model is
correct, the observed NCA AUCs will be more similar to the simulated NCA AUCs.
Hope this makes it clearer.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Uppsala Un
Nick,
See comments below.
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Uppsala University
Box 591
751 24 Uppsala Sweden
phone: +46 18 4714105
fax: +46 18 471 4003
-Original Message-
From: owner-nmus...@globomaxnm.com [mailto:owner-nmus
ssibly what you could do is be more
careful in your choice of prediction intervals to display. For example, if
you have a subpopulation of poor metabolizers of about 5%, displaying only
median and interquartile range PIs may not be a good idea.
Best regards,
Mats
Mats Karlsson, Ph
Pharmacol. 2005 Feb;59(2):189-98
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Uppsala University
Box 591
751 24 Uppsala Sweden
phone: +46 18 4714105
fax: +46 18 471 4003
From: owner-nmus...@globomaxnm.com [mailto:owner-nmus
is 5%,
but only 2% are allocated to this subpopulation by the EBE step.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Uppsala University
Box 591
751 24 Uppsala Sweden
phone: +46 18 4714105
fax: +46 18 471 4003
-Original Message-
Fr
Hi Nck,
Exactly - when in simulation mode the correct assignment will take place.
Here however, was the question about stratifying the VPC based on the value
of the POSTHOC estimates based on the real data.
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
e in NONMEM: finding the
individual probability of belonging to a subpopulation for the use in model
analysis and improved decision making."
Carlsson KC, Savić RM, Hooker AC, Karlsson MO.
AAPS J. 2009 Mar;11(1):148-54. Epub 2009 Mar 10.
Mats
Mats Karlsson, PhD
Professor of Pharmacometri
s
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Uppsala University
Box 591
751 24 Uppsala Sweden
phone: +46 18 4714105
fax: +46 18 471 4003
From: Diane R Mould [mailto:drmo...@attglobal.net]
Sent: Wednesday, April 15, 2009 6:16 PM
To:
rrelations, whereas Bill
interpreted it as CVs for IIV. It was just not enough info to make the
distinction. If the model is so simple, why not show the whole model.
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Uppsala University
Box 591
751 24 Upps
Hi Nele,
So what exactly is the IIV model you are testing? Showing code is probably
clearest. A model with only diagonal IIV in CL/F and V/F may well be
underparameterized.
What happened with the mixture?
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of
or two- or three-compartment models the advantages are that if indeed the
main covariance structure between CL/F, V1/F, Q/F, V2/F is a joint positive
correlation due to variability in bioavailability, fu etc, then a DIAG(5) is
more parsimonious than a BLOCK(4).
Mats
Mats Karlsson, PhD
Pr
Hi Steve,
See below.
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Uppsala University
Box 591
751 24 Uppsala Sweden
phone: +46 18 4714105
fax: +46 18 471 4003
-Original Message-
From: Stephen Duffull [mailto:stephen.duff...@otago.ac.nz]
Sent
Hi Leonid,
Pls see below.
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Uppsala University
Box 591
751 24 Uppsala Sweden
phone: +46 18 4714105
fax: +46 18 471 4003
-Original Message-
From: Leonid Gibiansky [mailto:lgibian...@quantpharm.com]
Sent
Dear Thomas,
Compartments can be turned on and off by specifying extra events (EVID=2) in
the data set. To turn off CMT N use CMT column equal to N, to turn it on
use N in CMT column.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical
Dear Anubha,
You need to have a record at time zero so that the integration can start.
This record can be a EVID=2
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Uppsala University
Box 591
751 24 Uppsala Sweden
phone: +46 18
mplex structural model that a
single profile indicated. Maybe you need to go to a two-compartment for
example.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Uppsala University
Box 591
751 24 Uppsala Sweden
phone: +46 18 4714105
fax: +
please contact me.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Uppsala University
Box 591
751 24 Uppsala Sweden
phone: +46 18 4714105
fax: +46 18 471 4003
hy it would be worse than a copula function. Nick's example is such
a situation, like all examples where death is one event...
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Uppsala University
Box 591
751 24 Uppsala Sweden
phone: +46 18 4
UNCCL UNCV CL V
As for the error model this was of course intentional - checking impact of
model misspecification is one of the reasons we do these kinds of simulation
studies. :)
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Uppsala
Dear Wang
Did you put proper boundaries on B2 & B3?
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Uppsala University
Box 591
751 24 Uppsala Sweden
phone: +46 18 4714105
fax: +46 18 471 4003
-Original Message-
From: owner-
ments have
incorrect type
No nonmem execution.
Is it that nonmem can give random number 0 and not 1? I can see only the
numerical issue of log(0).
;--
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Uppsala University
Box 591
751
Nick,
Pls see below.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Uppsala University
Box 591
751 24 Uppsala Sweden
phone: +46 18 4714105
fax: +46 18 471 4003
From: owner-nmus...@globomaxnm.com [mailto:owner-nmus
esign. Error
models for concentrations below LO? are not entirely unimportant, but will
not have the properties you mention below.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Uppsala University
Box 591
751 24 Uppsala Sweden
phone: +46 18 471410
Hi Nick,
Maybe Leonid's suggestion to agree to disagree was a good one but here we go
again :)
See below
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Uppsala University
Box 591
751 24 Uppsala Sweden
phone: +46 18 4714105
fax: +46 18 471
Nick,
So the advice regarding handling of error models actually concerns a study
that is to be done in your lab where negative concentrations are to be
reported. Not the million of studies with LOQ limits. Could have been useful
to know.
Best regards,
Mats
Mats Karlsson, PhD
Professor of
Steve,
And we need to design our studies to what is reported, which means taking
into account that for some observations, the only information you will get
is that they are below a limit.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Nick,
Pls see below.
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Uppsala University
Box 591
751 24 Uppsala Sweden
phone: +46 18 4714105
fax: +46 18 471 4003
-Original Message-
From: owner-nmus...@globomaxnm.com [mailto:owner-nmus...@globomaxnm.com
OFV
as a measure of goodness-of-fit is central and look at the risk something
improved the fit by chance, but I would not use it as measure of clinical
importance.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Uppsala University
Box 591
7
,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Uppsala University
Box 591
751 24 Uppsala Sweden
phone: +46 18 4714105
fax: +46 18 471 4003
-Original Message-
From: owner-nmus...@globomaxnm.com [mailto:owner-nmus...@globomaxnm.com] On
Behalf Of
this that have no practical impact. You do not indicate what else
in the survival analysis convinced you that the OFV was associated with
something of practical consequence. I trust your decision was not based
only on the OFV!
Nick
Mats Karlsson wrote:
> Nick,
>
> I agree that small
Nick,
Could you elaborate on how you reason around the necessity of showing a
priori power when you find a significant effects from the study data? How
would you show it?
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Uppsala University
Box
(and
alternatives such as residual error magnitude related to rate of change) in
these publications:
J Pharmacokinet Biopharm. 1995 Dec;23(6):651-72.
J Pharmacokinet Biopharm. 1998 Apr;26(2):207-46
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosci
within a week after application deadline.
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Uppsala University
Box 591
751 24 Uppsala Sweden
phone: +46 18 4714105
fax: +46 18 471 4003
71-80. Epub 2009 May 19.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Uppsala University
Box 591
751 24 Uppsala Sweden
phone: +46 18 4714105
fax: +46 18 471 4003
From: owner-nmus...@globomaxnm.com [mailto:owner
ion model should
include such a correlation. If shrinkage is high (>20% or so) I would tend
to use simulation-based or CWRES based diagnostics instead of posthoc eta's.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Uppsala University
Box 5
y, it is always appreciated to learn if and how the problem was
solved.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Uppsala University
Box 591
751 24 Uppsala Sweden
phone: +46 18 4714105
fax: +46 18 471 4003
-Original Message-
dissimilar to a cumulative normal are things to look out for.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Uppsala University
Box 591
751 24 Uppsala Sweden
phone: +46 18 4714105
fax: +46 18 471 4003
From: owner-nmus
non-parametric methods where very
little distributional assumption is being made. Semi-parametric methods are
essentially parametric but parameters are estimated that relates not just the
magnitude, but also the shape of the distribution.)
Best regards,
Mats
Mats Karlsson, PhD
Professo
results Stuart
were basing his thoughts on, do you? Maybe the keyword in Stuart’s sentence is
“largely”.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Uppsala University
Box 591
751 24 Uppsala Sweden
phone: +46 18 4714105
fax
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Uppsala University
Box 591
751 24 Uppsala Sweden
phone: +46 18 4714105
fax: +46 18 471 4003
From: owner-nmus...@globomaxnm.com [mailto:owner-nmus...@globomaxnm.com] On
Behalf Of Nick Holford
Sent: Monday
transformation
TVCL=THETA(1)
HTPAR=THETA(2)
ETATR=ETA(1)*SQRT(ETA(1)*ETA(1))**HTPAR
CL=TVCL*EXP(ETATR)
Logit transformation
TVCL=THETA(1)
LGPAR1 = THETA(2)
LGPAR2 = THETA(3)
PHI = LOG(LGPAR1/(1-LGPAR1))
PAR1 = EXP(PHI+ETA(1))
ETATR = (PAR1/(1+PAR1)-LGPAR1)*LGPAR2
CL=TVCL*EXP(ETATR)
Mats
Mats Karlsson, PhD
0.08444 1.74E-24 0.001808
LGPAR1 = THETA(2)
LGPAR2 = THETA(3)
PHI = LOG(LGPAR1/(1-LGPAR1))
PAR1 = EXP(PHI+ETA(1))
ETATR = (PAR1/(1+PAR1)-LGPAR1)*LGPAR2
HILL=THETA(1)*EXP(ETATR)
Y=1.1**HILL/(1.1**HILL+1) + EPS(1)
Best regards,
Mats
Mats Karlsson, PhD
It seems my mails are not appearing on nmusers – maybe a sign that the thread
has gone on too long. Anyway the one below is from yesterday.
/Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Uppsala University
Box 591
751 24 Uppsala Sweden
phone: +46
Dear Ann,
Change to ALAG4. Note that you could use ADVAN 5 or 7 for this model if you
specify all rate constants. These should be faster.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Uppsala University
Sweden
Postal
more complex than easily handled via a covariance, then I
suggest that you use the baseline observation as a covariate with error
(Dansirikul et al Pharmacokinet Pharmacodyn. 2008 Jun;35(3):269-83.)
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical
IOV may not be
modeled ideally. Then however, not only IOV, but also IIV and RV become
nuisance parameters as they will not represent the true IIV or RV.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Uppsala University
Sweden
Seems like the mail below from last week never appeared on the nmusers.
Probably the discussion became too long (or too hair-splitting.).
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Uppsala University
Sweden
Postal address
nt on the
concentration of drug rather than an on/off ). The number of parameters is
no more than the one you're using now, but avoids the change-point which
often cause numerical problems.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical B
assuring that the residual error model is
appropriate. Better alternatives are always welcome.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Uppsala University
Sweden
Postal address: Box 591, 751 24 Uppsala, Sweden
Phone +46
The pharmacometrics research group at Uppsala University are enrolling new
PhD students.
Information at http://www.personalavd.uu.se/ledigaplatser/engindex.html
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Uppsala University
this
upper boundary. If, as you say, the analyst has carefully thought through
the boundaries, an estimate at the boundary should represent the global
minimum within the reasonable parameter range. I think one can make a strong
argument for not discarding such runs.
Best regards,
Mats
Mats Karlsson, PhD
, 2012. Please specify a time
window for possible starting dates.
For further information and applications please contact Mats Karlsson
mats.karls...@farmbio.uu.se.
Some general information about the research group can be found at
http://www.farmbio.uu.se/research/researchgroups/pharmacometrics/ and
)
and the agreement between epsilon and the residual is lost.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Faculty of Pharmacy
Uppsala University
Box 591
75124 Uppsala
Phone: +46 18 4714105
Fax + 46 18 4714003
From
User's Guides, you may find useful info in Gisleskog et al J
Pharmacokinet Pharmacodyn. 2002 Dec;29(5-6):473-505.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Faculty of Pharmacy
Uppsala University
Box 591
75124 Up
SE = Standard error of Omega^2 (from output f
previous)
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Faculty of Pharmacy
Uppsala University
Box 591
75124 Uppsala
Phone: +46 18 4714105
Fax + 46 18 4714003
From: Bauer,
ETA10
ONEHEADER NOPRINT FILE=patab31
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Faculty of Pharmacy
Uppsala University
Box 591
75124 Uppsala
Phone: +46 18 4714105
Fax + 46 18 4714003
-Original Message-
From: owner
simple starting model, you can
try combining the two.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Faculty of Pharmacy
Uppsala University
Box 591
75124 Uppsala
Phone: +46 18 4714105
Fax + 46 18 4714003
From: owner
Hi Martin,
If you write P(3) =1-P(1)-P(2) you reduce the risk of writing something
incorrect J
Mats Karlsson
Mats Karlsson, PhD
Professor of Pharmacometrics
FIRST WORLD CONFERENCE ON PHARMACOMETRICS, 5-7 September 2012, Seoul (
<http://www.go-wcop.org/> www.go-wcop.org)
D
lable.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
FIRST WORLD CONFERENCE ON PHARMACOMETRICS, 5-7 September 2012, Seoul
(www.go-wcop.org)
Dept of Pharmaceutical Biosciences
Faculty of Pharmacy
Uppsala University
Box 591
75124 Uppsala
Phone: +46 18 4714105
Fax + 46 18 47
Dear Claire,
If you have data only from oral doses and covariances between disposition
parameters (CL; V), then you will not get any further improvement by
introducing variability in F1.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
FIRST WORLD CONFERENCE ON
to keep this parameterization
for P(1), maybe you should try switching initial est's between THETA3 and
THETA4.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
FIRST WORLD CONFERENCE ON PHARMACOMETRICS, 5-7 September 2012, Seoul (
<http://www.go-wcop.org/&
bayes estimates for diagnostics: problems
and solutions.
AAPS J. 2009 ;11:558-69.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Faculty of Pharmacy
Uppsala University
Box 591
75124 Uppsala
http://www.farmbio
558-69.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Faculty of Pharmacy
Uppsala University
Box 591
75124 Uppsala
http://www.farmbio.uu.se/research/researchgroups/pharmacometrics/
Phone: +46 18 4714105
Fax +
population PK model as prior, NONMEM and other non-linear mixed effects
models are probably preferable.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
FIRST WORLD CONFERENCE ON PHARMACOMETRICS, 5-7 September 2012, Seoul (
<http://www.go-wcop.org/> www.go-wc
Dear Francois,
Unless you create a new data set where events are allowed to occur at any
possible time (usually a dense time grid), then the result that you have got
is rather the expected (i.e. too good to be true).
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
ieve that the psn user guide for
npc/vpc (npc_vpc_userguide.pdf) contains the information you seek.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Faculty of Pharmacy
Uppsala University
Box 591
75124 Uppsala
Phone: +46 18 4714
more relevant. If
it is not, Nick's is more appropriate.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Faculty of Pharmacy
Uppsala University
Box 591
75124 Uppsala
Phone: +46 18 4714105
Fax + 46 18 4714003
-Original Message-
F
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Faculty of Pharmacy
Uppsala University
Box 591
75124 Uppsala
Phone: +46 18 4714105
Fax + 46 18 4714003
From: owner-nmus...@globomaxnm.com [mailto:owner-nmus...@globomaxnm.com] On
Behalf Of
M you can just specify
> $ESTIMATION MET=0 LIKE MAX=500
You should omit or rename the "ID" column, as NONMEM would expect ETAs when
ID as in the data set.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Faculty of
, you could use the
"-out=xxx.yyy" to point to the correct file if that does not follow naming
conventions. If you have not run it and really don't want to run it, you
could substitute xxx.yyy for some other output file with similar structure.
Best regards,
Mats
Mats Karlsso
Hi Anuba,
I would agree with your suggestion. That is how I usually do it.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Faculty of Pharmacy
Uppsala University
Box 591
75124 Uppsala
Phone: +46 18 4714105
Fax + 46 18
$ERROR
IPRED=F
LOQ=LLOQ
DUM=(LOQ-IPRED)/(SQRT(SIGMA(1,1))*IPRED)
CUMD=PHI(DUM)
IF (BQL.EQ.0) THEN
F_FLAG=0
Y=IPRED*(1+ ERR(1))
ENDIF
IF (BQL.EQ.1) THEN
F_FLAG=1
Y=CUMD
ENDIF
$EST METHOD=COND INTER LAPLACIAN
$SIGMA .1
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
*(CL1 + CLr)* EXP(ETA(1))
CL=(1.0-Z)*(CL2 + CLr)* EXP(ETA(2))
V2 = THETA(4)*(WT/70)*EXP(ETA(3))
(I'm not sure about your ETA variance structure as it is not entirely
provided, but if you use a covariance between CL and V use also separate
ETAs for V between mixtures)
Best regards,
Mats
Mats Kar
Registration for a course on Covariate model building and evaluation in
Glasgow June 10-11 has just opened at www.uppsala-pharmacometrics.com
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Faculty of Pharmacy
Uppsala University
inear
interpolation between observed covariate values
$ERROR
OCOV =COV;store previous time
OTIM =TIME ;store previous time
(NB haven't tested the code).
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Faculty o
gt; Leonid
> Original email:
> -----
> From: Mats Karlsson mats.karls...@farmbio.uu.se
> Date: Sat, 24 Aug 2013 10:02:00 +0200
> To: william.s.den...@pfizer.com, ellen.siwei...@gmail.com,
> nmusers@globomaxnm.com
> Subject: RE: [NMusers] Time-varing covariate
>
>
> Dear
Pharmacol.
2004 Oct;58(4):367-77.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Faculty of Pharmacy
Uppsala University
Box 591
75124 Uppsala
Phone: +46 18 4714105
Fax + 46 18 4714003
<http://www.farmbio.uu.se/resea
, you may not need
to have to use EVID=2 to make the covariate change at other times than event
times (as my example code tried to illustrate).
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Faculty of Pharmacy
Uppsala University
Box
mechanism-based approach for absorption modeling: the Gastro-Intestinal
Transit Time (GITT) model.
STEP = EXP(X*GAM)/(EXP(X*GAM)+EXP(X50*GAM))
Where X50 (inflection point) would be estimated and GAM (steepness)
typically fixed.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
population and individual).
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Faculty of Pharmacy
Uppsala University
Box 591
75124 Uppsala
Phone: +46 18 4714105
Fax + 46 18 4714003
www.farmbio.uu.se/research/researchgroups/pharmacometrics/<h
nonparametric
option does allow a fuller description of the correlation than the linear one
though, so if that was the problem, $NONP may offer a solution.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Faculty of Pharmacy
Uppsala University
Box
lsson MO.
AAPS J. 2013 Oct;15(4):1035-42. doi: 10.1208/s12248-013-9508-0.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical Biosciences
Faculty of Pharmacy
Uppsala University
Box 591
75124 Uppsala
Phone: +46 18 4714105
Fax + 46 18 4714003
www.farmbio.
nt model for the immunogenicity of certolizumab pegol in
rheumatoid arthritis subjects
Mats Karlsson, Uppsala University
Welcome,
Sofia Friberg Hietala
Fredrik Jonsson
Mats Karlsson
Marie Sandström
Janet Wade
Johan Wallin
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of Pharmaceutical
Dear Diane-Charlotte,
NONMEM interprets DATE in your in-data and makes use of it. If you don’t want
that, rename DATE to something that is not recognized. Each date aboce the
first adds 24 h to your time column
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
Dept of
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