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- [NMusers] Con't: fast and slow absorption

divide the dose between the two absorption components see fragment control file below SUBR ADVAN6 MODEL COMP FAST COMP SLOW COMP CENTRAL PK F1 THETA 1 F2 1 THETA 1 etc DES DFAST A 1 DSLOW A 2 DCP A 3 V3 DADT 1 KA1 DFAST DADT 2 KA2 DSLOW DADT 3 IN DCP CL IN KA1 DFAST KA2 DSLOW DADT 3 IN DCP CL Hope this helps If you have a change point model ie the two processes are sequential rather than parallel Search for the presentation bye Joel Owen at ECPAG about this issue See also this article to see how to constrain the bioavailibilities should you use an eta on them Csajka C Drover D Verotta D The use of a sum of inverse Gaussian functions to describe the absorption profile of drugs exhibiting complex absorption Pharm Res 2005 Aug 22 8 1227 35 Samer Samer MOUKSASSI PhD candidate université de montéral From Sam Liao sliao pharmaxresearch com Subject RE NMusers Con t fast and slow absorption Date Wed 15 Nov 2006 15 14 08 0500 Jian Here is an example NONMEM control stream for the pk model you need Please make sure to specify CMT 3 for your PK data You also need one dose event record with CMT 1 and the second dose event record with CMT 2 The AMT will be the same in both records Best regards Sam Liao Pharmax Research PROB PHARMACOKINETIC MODEL 1 CMPT WITH ONE SLOW AND ONE FAST ABSORPTION INPUT ID TIME DAY AMT CONC DV CMT AGE WT SEX RACE DATA nm prn IGNORE SUBROUTINE ADVAN6 TOL 6 MODEL NCOMP 3 COMP DEPOT1 DEFDOSE COMP DEPOT2 COMP CENT DEFOBS PK TVCL THETA 1 TVVD THETA 2 TKA1 THETA 3 TKA2 THETA 4 TF1 THETA 5 TLAG THETA 6

Original URL path: http://nonmem.org/nonmem/nm/98nov152006.html (2016-04-25)

Open archived version from archive - [NMusers] modelling lag time and absorption

over an 8 hour period Individual plots demonstrate that a 1 compartment PK model adequately describes the data Furthermore the plots show that there is considerable between patient varibility in Ka Tlag V F and CL F For instance some patient had detectable drug levels at the first sample taken wheras in 1 patient the 8 hour last sample was the first sample in which the drug could be detected In the dataset concentrations LOD were excluded with the exception of the last sample before concentration LOD or the first sample after concentration LOD These concentrations were set at half the value of the LOD ADVAN2 was used with FOCE interaction and a combined error model The results were dissapoining 1 biased PRED vs DV plots 2 High WRES values 3 Parameter estimates were dependent on the number of significant digits and intitial values 4 Individual plots of IPRED vs time demonstrated that Tlag was underestimated in 25 of the patients I tried to improve the model by application of log transformation FOCE additive error model all concentrations LOD excluded Diagnostic plots slightly improved 1 and 2 above whereas parameter estimates remained unstable and POSTHOC s of lag time were

Original URL path: http://nonmem.org/nonmem/nm/99nov152006.html (2016-04-25)

Open archived version from archive - [NMusers] Help on rounding error ( error=134) !

follows however the result turns out to be a very large V2 and very small CL and keeping giving the rounding error error 134 Does anyone can help me figure it out PK V1 THETA 1 EXP ETA 1 V2 THETA 2 EXP ETA 2 CL THETA 3 EXP ETA 3 Q THETA 4 EXP ETA 4 K CL V1 K12 Q V1 K21 Q V2 S1 V1 ERROR IPRED F W F IRES DV IPRED IWRES IRES W Y IPRED W EPS 1 OMEGA 0 25 OMEGA 0 5 OMEGA 0 5 OMEGA 0 5 SIGMA 0 25 Thanks a lot Ping From Nick Holford n holford auckland ac nz Subject Re NMusers Help on rounding error error 134 Date Mon 13 Nov 2006 11 50 39 1300 Ping Did you look at the model predictions If the predictions look Ok then you can ignore the rounding error message A visual predictive check would be a good way to decide if your model predictions are OK You say CL is small and V2 is large On what basis of prior knowledge do you judge them to be small and large Unless you have some good reason e g CL much bigger than cardiac output then it isn t usually helpful to judge the numerical values to be small or large Nick Nick Holford Dept Pharmacology Clinical Pharmacology University of Auckland 85 Park Rd Private Bag 92019 Auckland New Zealand email n holford auckland ac nz tel 64 9 373 7599x86730 fax 373 7556 http www health auckland ac nz pharmacology staff nholford From Toufigh Gordi tgordi Depomedinc com Subject Re NMusers Help on rounding error error 134 Date Sun 12 Nov 2006 20 19 14 0800 Hi Ping I am guessing that you have looked at some graphs of

Original URL path: http://nonmem.org/nonmem/nm/99nov122006.html (2016-04-25)

Open archived version from archive - [NMusers] Getting PRED and WRES

I try to get PRED and WRES from the model using the following statement TABLE ID STU TIME DV PRED RES WRES NOHEADER NOAPPEND NOPRINT FILE H PKRADI68 FI1 To my best knowledge NONMEM has to print them even if I do not request them Unfortunately NONMEM prints ID STU TIME DV only I calculate IPRED and IWRES IPRE F IRE DV IPRE IWRE IRE SD and they look great

Original URL path: http://nonmem.org/nonmem/nm/99nov062006.html (2016-04-25)

Open archived version from archive - [NMusers] NONMEM sparse data advantage reference

Universität Theodor Stern Kai 7 D 60590 Frankfurt am Main Tel 069 6301 4589 Fax 069 6301 7636 http www klinik uni frankfurt de zpharm klin From Nitin Mehrotra nitin utmem yahoo com Subject Re NMusers NONMEM sparse data advantage reference Date Thu 2 Nov 2006 06 52 21 0800 PST Dear Joern You might want to look at the following references 1 Ette EI Williams PJ Lane JR Population

Original URL path: http://nonmem.org/nonmem/nm/99nov022006.html (2016-04-25)

Open archived version from archive - [NMusers] covariate model building: forward inclusion and backward elimination

model building forward inclusion and backward elimination Date Mon 30 Oct 2006 10 22 30 0500 Hello NONMEM users This is question about forward inclusion and backward elimination Obviously backward elimination should be done using NONMEM Some scientist apply NONMEM to do forward inclusion Some other scientists use SAS or S plus to run regression analysis on Bayesian estimates while including covariates in the model Is that appropriate to use

Original URL path: http://nonmem.org/nonmem/nm/99oct302006.html (2016-04-25)

Open archived version from archive - [NMusers] sequential PKPD modeling

the PD data can support PK data analysis I am wondering whether it is possible that the increasing on the CL of drug A in the following email could be a consequence of PD effect of drug B rather then a real PK effect in a simultaneous PKPD modeling Jim Jiang From Liping CD Zhang liping zhang3 bms com Subject Re NMusers sequential PKPD modeling Date Thu 26 Oct 2006 15 54 50 0400 Hi Jim simultaneous analysis of PKPD data is a better analysis especially for the sparse PK data because the PD data can support PK data analysis Simultaneous analysis of PKPD data is a better method because it naturally follows the maximal likelihood theory PD s support for PK analysis is not for granted a misspecified PD model could distorted PK model For references see Bennett and Wakefield 2001 Biometrics 57 803 12 and Zhang et al 2003 JPP 405 16 I assume you ve had data from A alone and data from A and B administrated and when you model A B PK PD simultaneously you get a large Cl for A than the one from A alone I could only think of this case to

Original URL path: http://nonmem.org/nonmem/nm/99oct262006.html (2016-04-25)

Open archived version from archive - [NMusers] omega and mixture

different errors for each study Problem is that different studies have different dimention of OMEGA matrix Thus groups 1 2 and 4 have OMEGA BLOCK 2 Group 3 has OMEGA BLOCK 3 I want to use MIXTURE to specify 2 different OMEGA matrices Is this a reasonable and common approach My code is CONTR DATA STU MIX NSPOP 2 IF STU EQ 1 OR STU EQ 6 THEN P 1

Original URL path: http://nonmem.org/nonmem/nm/99oct232006.html (2016-04-25)

Open archived version from archive