RE: Parent and metabolite model-residual error model and L2

________________________________________ From: [email protected] [[email protected]] On Behalf Of Nick Holford [[email protected]] Sent: 02 September 2011 09:07 To: nmusers Subject: Re: [NMusers] Parent and metabolite model-residual error model and L2 Xipei, For Question 1 -- you need to specify both L2 and SIGMA(BLOCK). I think the answer to your Question 2 is well described in the online help for NONMEM. Perhaps you are not aware that you can find help for NM-TRAN/NONMEM as part of a normal NONMEM installation. You need to look for the html\index.html file, open it in an internet browser (save the URL as a favourite!), then search e.g. click on L for information about the L2 data item. For Question 3 -- I think L2 is only relevant for observation records (MDV=0 or EVID=0). Therefore I think you can use any value you look for L2 on a dosing record. A sensible value might be '.' which is meaningful to human readers to indicate that this is a missing value (which, in this case, does not matter) . You could also use '42' if you like hitchhiking. Note that there is no need to use POSTHOC with METHOD=1. The CONDITIONAL method always returns POSTHOC values in the output table. Best wishes, Nick DISCUSSION: L2 labels level-two (L2) data items. The level two data item is optional. Recall that the ID data item is used to group together the data records containing observations which have the same realization of the level-one random effects (etas). Similarly, the L2 data item is used to group together the data records containing observations which have the same realization of the level-two random effects (epsilons). The observations of such a group is called a level-two observation. The group itself is called a level-two (L2) record. Data records of an L2 record must be contiguous (and contained within the same individual record). By default, level-two observations are treated as being sta- tistically independent multivariate observations. (However, within a level-one observation, the level-two random effects can be made to be correlated between level-two observations.) Here is an example of a fragment of a data set using L2 data items. There are two types of observations, designated by the two different values of the user data item TYPE. Note that the L2 data items are the same for both of the observations at TIME=2, and they are also the same for both of the observations at TIME=112.5. ID TIME AMT APGR WT DV TYPE L2 1 0. 25.0 1.4 7 . . 1 1 2.0 . 1.4 7 6.0 1 1 1 2.0 . 1.4 7 17.3 2 1 1 12.5 3.5 1.4 7 . 2 2 1 24.5 3.5 1.4 7 . 2 2 1 37.0 3.5 1.4 7 . 2 2 1 48.0 3.5 1.4 7 . 2 2 1 60.5 3.5 1.4 7 . 2 2 1 72.5 3.5 1.4 7 . 2 2 1 85.3 3.5 1.4 7 . 2 2 1 96.5 3.5 1.4 7 . 2 2 1 108.5 3.5 1.4 7 . 2 2 1 112.5 . 1.4 7 8.0 1 2 1 112.5 . 1.4 7 31.0 2 2 On 2/09/2011 6:31 p.m., wangxipei wrote: > Dear NONMEM users, > > I am building a popPK model for a parent drug and its metabolite (rich > data,single dose). I want to estimate the correlation between the > residual errors of parent drug and its metabolite, because their > measurements were from a same blood sample. (My code and part of data > are shown as follows.) > Question 1: Should I use $SIGMA BLOCK (2) only, or should I use both > L2 and $SIGMA BLOCK(2)? > Question 2: I am not sure about the format of L2 data item, so I show > the first two individuals. > Within one individual, the observations of parent and its metabolite > at the same time point have the same L2 value, but different from > other time points. Is it correct? > Question 3: Does the L2 value of the dose event affect the estimation? > (I think it ! does not.) > > > ----------------------------------- NONMEM code > ------------------------------------------------------------------------------------------ > $INPUT C ID TIME DV AMT CMT EVID L2 > $DATA d.CSV IGNORE=@ > $SUBROUTINES ADVAN6 TOL=6 > $MODEL NCOMP=7 COMP(DEFDEP, DEFDOSE) COMP(CENTRAL, DEFOBS) > COMP(PERIPH) COMP(META) COMP(META2) > COMP(TRANSIT1) COMP(TRANSIT2) ; 2-COMP for parent drug, 2-comp for its > metabolite, 2-transit compartments to connect them. > $PK > CL=TVCL*EXP(ETA(1)) > ... > $DES > ... > $ERROR > DEL=0 > IF (F.EQ.0) DEL=1 > W=F > IPRED=F > IRES=DV-IPRED > IWRES=IRES/(W+DEL) > IF(CMT.EQ.2) Y=F + F*ERR(1) > IF(CMT.EQ.4) Y=F + F*ERR(2) + ERR(3)! > ... > $SIGMA BLOCK(2) > .2 ;parent RV > .1 .17 ;metabolite RV > $SIGMA BLOCK(1) 0 FIX;[A] > $EST PRINT=5 MAX=9999 SIG=3 METH=1 POSTHOC MSFO=run1.MSF > > > --------------individual data > -------------------------------------------------------------- > compartment 2 is the central compartment of parent drug, and > compartment 4 is the central comp. of metabolite. > > ID TIME DV AMT CMT EVID L2 1 0 . 100 1 1 0 1 0.33 1.096 . 2 0 1 1 0.66 > 0.623 . 2 0 2 1 0.66 0.130 . 4 0 2 1 1 0.329 . 2 0 3 1 1 0.407 . 4 0 3 > 1 1.5 0.139 . 2 0 4 1 1.5 0.541 . 4 0 4 1 2 0.073 . 2 0 5 1 2 0.552 . > 4 0 5 1 2.5 0.022 . 2 0 6 1 2.5 0.465 . 4 0 6 1 3 0.076 . 2 0 7 1 3 > 0.572 . 4 0 7 1 3.5 0.479 . 4 0 8 1 4 0.480 . 4 0 9 1 6 0.160 . 4 0 10 > 1 8 0.252 . 4 0 11 1 12 0.117 . 4 0 12 1 24 0.018 . 4 0 13 2 0 . 100 1 > 1 0 2 0.33 0.030 . 2 0 1 2 1 0.034 . 2 0 3 2 1.5 0.049 . 2 0 4 2 2 > 0.053 . 2 0 5 2 2.5 0.299 . 2 0 6 2 2.5 0.033 . 4 0 6 2 3 0.344 . 2 0 > 7 2 3 0.118 . 4 0 7 2 3.5 0.263 . 2 0 8 2 3.5 0.293 . 4 0 8 > > > > Many thanks in advance for any comments! > Xipei > > -- > Xipei Wang, Ph.D. student > Department of Pharmaceutics, School of Pharmaceutical Sciences, > Peking University Health Science Center, Beijing, > China > Email: [email protected] > > -- Nick Holford, Professor Clinical Pharmacology Dept Pharmacology& Clinical Pharmacology University of Auckland,85 Park Rd,Private Bag 92019,Auckland,New Zealand tel:+64(9)923-6730 fax:+64(9)373-7090 mobile:+64(21)46 23 53 email: [email protected] http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford ******************************************************************************************************************** This message may contain confidential information. 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