Dear Shankar,
You don't need to have information about enzyme levels or precursor to use the model mentioned by Rob, the idea of it is only to have a more physiological mechanism for the delay (not a lag but something that develops with a first-order delay) and magnitude (which is dependent 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 Biosciences Uppsala University Sweden Postal address: Box 591, 751 24 Uppsala, Sweden Phone +46 18 4714105 Fax + 46 18 4714003 From: owner-nmus...@globomaxnm.com [mailto:owner-nmus...@globomaxnm.com] On Behalf Of Shankar Lanke Sent: Monday, March 28, 2011 4:51 PM To: r.ter.he...@meandermc.nl Cc: nmusers@globomaxnm.com Subject: Re: [NMusers] Autoinduction model - An increased clearance(day 1- 14) Dear Rob ter Heine, I am working with Efavirenz, I working with 66 patients, 924 data points, intense on day 1 and 14 and a trough con in between the two weeks. I looked into the Physiological model presented by Dr. Karlsson earlier but I did not used it since I dont have any information about ENZYME comp or precursor. I used the reasonable estimates based on earlier literature and aslo I tried NPD approach. Thank you very much Rob ter Heine, I appreciate your input. On Mon, Mar 28, 2011 at 10:36 AM, <r.ter.he...@meandermc.nl> wrote: Dear Shankar, How rich is your dataset? In other words: do you have enough data troughout the induction period to estimate the lagtime? You could, for example try to fix the lagtime to a reasonable time and estimate the inter-individual variability. Another way of estimating the autoniduction is more physiologically based with a theoretical enzyme compartment. For example, see: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2014348/figure/fig01/ Which drug PK are you modelling? Most likely it is a non-nucleoside reverse transcriptase inhibitor. The cyp3a4 autoinduction with efavirenz is debatable and less profound than autoinduction with, for example, nevirapine. Sincerely, Rob ter Heine _____ Van: owner-nmus...@globomaxnm.com [mailto:owner-nmus...@globomaxnm.com] Namens Shankar Lanke Verzonden: maandag 28 maart 2011 15:53 Aan: nmusers@globomaxnm.com Onderwerp: [NMusers] Autoinduction model - An increased clearance(day 1- 14) Dear All, I am working on a Pop PK data where the patients are treated with HIV drug. An autoinduction is involved with prolonged administration of the drug. An increased CL is expected from day 1 to day 14. We have intense data on day 1 and day 14 with sparse data between. Since a lag period is involved for the induction I used the equation CL = CLinduced -(CLinduced - CLpre)*exp(-kout*(t-Tlag)) described by Johan Gabrielsson as more appropriate. Also when I included a lag period for absorption in my earlier model my fits are better and OBF decreased by 200. However the final model with or without lag time for absorption + auto induction model is either terminated or covariance step is being aborted. I changed the initial estimates several times but still no luck. Though the Auto induction model aborts the fits are better than the lag time model however the estimates for Vd are 4 fold less than the expected. I appreciate your input and suggestions. Here is my code. $SUBROUTINES ADVAN13 TRANS1 TOL=5 ;(I used ADVAN6 too) $MODEL NPAR=9 NCOMP=4 COMP=(DEPOT,DEFDOSE) COMP=(LAG) COMP=(OBSV,DEFOBS) COMP=(PERIP) $PK CLP=THETA(1) CLI=THETA(6) KOUT=THETA(7) TLAG=THETA(8)*EXP(ETA(6)) TVCL=CLI-(CLI-CLP)*EXP(-KOUT*(TIME-TLAG)) CL=TVCL*EXP(ETA(1)) TVV2=THETA(2) V2=TVV2*EXP(ETA(2)) TVQ=THETA(3) Q=TVQ*EXP(ETA(3)) TVV3=THETA(4) V3=TVV3*EXP(ETA(4)) TVKA=THETA(5) KA=TVKA*EXP(ETA(5)) TVALAG1=THETA(9) ALAG1=TVALAG1*EXP(ETA(7)) S3=V2 $DES K=CL/V2 K23=Q/V2 K32=Q/V3 DADT(1)=-KA*A(1) DADT(2)=KA*A(1)-A(2)/ALAG1 DADT(3)=A(2)/ALAG1-K23*A(3)-K*A(3)+K32*A(4) DADT(4)=K23*A(3)-K32*A(4) $ERROR DEL=0 IF (F.LE.0.0001) DEL=1 IPRE=F W1= 1 W2= F IRES= DV-IPRE IWRE=IRES/(W1+W2) Y = F + W1*ERR(1) + W2*ERR(2) DV2=ABS(V2-TVV2) $EST METHOD=1 INTERACTION PRINT=5 MAX=9999 SIG=3 MSFO=JLM.MSF $THETA (0, 6);[CLP] (0, 90);[V2] (0, 19);[Q] (0, 200);[V3] (0, 0.16);[KA] (0, 8);[CLI] (0, 0.001);[KOUT] (0, 250);[TLAG] (0, 0.3);[ALAG1] $OMEGA 0.23 ;[CL] omega(1,1) 0.18;[V2] omega(2,2) 0 FIXED ;[Q] omega(3,3) 0.42;[V3] omega(4,4) 0.19;[KA] omega(5,5) 0.09;[TLAG for Ka] 0.1;[ALAG1 for CLI] $SIGMA 0.06 ;[P] sigma(1,1) 0.09 ;[A] sigma(2,2) $COV MATRIX=S Regards, Shankar Lanke Ph.D. University at Buffalo Office # 716-645-4853 Fax # 716-645-2886 Cell # 678-232-3567 _____ De informatie in dit e-mail bericht is uitsluitend bestemd voor de geadresseerde. Verstrekking aan en gebruik door anderen is niet toegestaan. Door de elektronische verzending van het bericht kunnen er geen rechten worden ontleend aan de informatie. _____ -- Regards, Shankar Lanke Ph.D. University at Buffalo Office # 716-645-4853 Fax # 716-645-2886 Cell # 678-232-3567
