Re: Modeling variability in absorption and clearance (Auto induction)

On Tue, May 15, 2012 at 4:27 AM, Amit Taneja <[email protected]>wrote: > ** ** ** ** ** > > Shankar,**** > > ** ** > > Here is a poster presented at PAGE 2011 wherein time dependent increase in > Ka is parametrised using an Emax function. In principle, time dependent > increase in clearance (metabolic enzyme induction) may be parametrised in > this way.**** > > ** ** > > Here is another parametrisation for clearance autoinduction, using an > exponential function discussed on the nm user’s list not too long ago. *** > * > > ** ** > > To be truly mechanistic, and describe the relationship between the parent > compound, an active metabolite and enzyme kinetics you may want to consider > the parametrisation discussed in the following paper (also recently > discussed on this forum)**** > > ** ** > > A mechanism-based pharmacokinetic-enzyme model for cyclophosphamide > autoinduction in breast cancer patients.**** > > Hassan et al,**** > > Br J Clin Pharmacol. 1999 Nov;48(5):669-77. 2.**** > > ** ** > > ** ** > > Hope this helps**** > > ** ** > > Amit Taneja**** > > Phd fellow**** > > Pharmacology,**** > > ****Leiden** **Amsterdam** **Center**** for Drug Research**** > > **Leiden**, the ****Netherlands******** > > ** ** > > On 3/4/2012 5:33 PM, Wang, Xiaofeng wrote: **** > > Dear nmusers, > > I have a drug with clearance autoinduction. I have sparse data(three > observations on day 1, two between day 7 and 14, and one on day 28). I am > trying to run a time-dependent clearance model. I tried FO and FOCEI, but I > always got unreasonable estimate for the initial clearance (CLI) which is > about 0.15 L/h (from knowledge of previous studies, the reasonable initial > clearance should be around 20 L/h and maximum induction occurs around day > 7). Could someone give me some advice about my model and my data? Thank you. > > Xiaofeng > > The CTL file: > $PROB > $INPUT C ID TIME AMT DV MDV EVID ADDL II CMT > $DATA C:/ IGNORE=C > $SUBROUTINES ADVAN6 TOL=6 > $MODEL NCOMPARTMENTS=3 > COMP=(DEPOT,DEFDOSE) > COMP=(CENTRAL,DEFOBS) > COMP=(PERIP) > $PK > CLI=THETA(1)*EXP(ETA(1)) > CLSS=THETA(2)*EXP(ETA(2)) > KIN=THETA(3)*EXP(ETA(3)) > V2= THETA(4)*EXP(ETA(4)) > Q= THETA(5)*EXP(ETA(5)) > V3= THETA(6)*EXP(ETA(6)) > KA= THETA(7)*EXP(ETA(7)) > S2=V2 > K23=Q/V2 > K32=Q/V3 > > $DES > CL=CLSS-(CLSS-CLI)*EXP(-KIN*T) > K20=CL/V2 > DADT(1)=-KA*A(1) > DADT(2)=KA*A(1)+K32*A(3)-K23*A(2)-K20*A(2) > DADT(3)=K23*A(2)-K32*A(3) > $ERROR > IPRE=LOG(1) > IF(F.GT.0) IPRE=LOG(F) > Y = IPRE+EPS(1) > $EST METHOD=0 POSTHOC PRINT=10 MAX=9999 SIG=2 NOABORT MSFO=050.MSF > $THETA > (0, 20);[CLI] > (0, 65);[CLSS] > (0, 0.02) ;[KIN] > (0, 45);[V2] > (0, 5);[Q] > (0, 58);[V3] > (0, 0.2);[KA] > > $OMEGA .25 .25 .25 .25 .25 .25 .25 > $SIGMA .2 > $COV PRINT=E > $TABLE ID TIME DV CLI CLSS KIN V2 Q V3 KA IPRE CWRES ONEHEADER NOPRINT > FILE=050.TAB > $TABLE ID TIME CLI CLSS KIN V2 Q V3 KA FIRSTONLY NOAPPEND NOPRINT > FILE=050.PAR > $TABLE ID ETA1 ETA2 ETA3 ETA4 ETA5 ETA6 ETA7 FIRSTONLY NOAPPEND NOPRINT > FILE=050.ETA > $TABLE ID TIME CLI CLSS KIN V2 Q V3 KA FIRSTONLY NOAPPEND NOPRINT > FILE=PATAB050 > > **** > > ** ** > > ** ** > ------------------------------ > > *From:* [email protected] [mailto:[email protected]] > *On Behalf Of *Shankar Lanke > *Sent:* Monday, May 14, 2012 6:44 PM > *To:* [email protected] > *Cc:* [email protected] > *Subject:* Re: [NMusers] Modeling variability in absorption and clearance > (Auto induction)**** > > ** ** > > Dear Heine,**** > > ** ** > > Thank you very much for your response on Efavirenz data (tablets), I have > tried transit compartmental model and what I noticed is, it accounts for > the delay in the absorption but not troughs within the absorption phase. (I > am not sure if it is the sampling error in 26 patients or anything else). I > dont have a genotype data, including wt as a covariate in clearance and Vd > isnt helping much (OBF ~). Based on your experience have you ever come > across a situation where continuous dosing may result in increased in > absorption rate constant. Individual analysis results shown increased Ka in > 60% of patients. **** > > ** ** > > Thank you once again.**** > > ** ** > > Regards,**** > > ** ** > > On Mon, May 14, 2012 at 12:06 PM, <[email protected]> wrote:**** > > Dear Shankar Lanke,**** > > **** > > you can try modeling variable absorption with a chain of transit > compartments and estimating the mean absorption and to account for > interoccasion variability in relative oral bioavailability (e.g. > F1=1*EXP(ETA(1)). **** > > **** > > Other things that you should account for with efavirenz in my opnion are** > ** > > **** > > 1.The liquid formulation of efavirenz has a lower bioavailability. **** > > 2. slow metabolizers may exist due to CYP2B6 polymorphism. If you do not > have genotype data available, you could try mixture modeling of multiple > subpopulations.**** > > 3. weight is a known covariate on clearance and volume of distribution**** > > 4. CYP3A4 autoinduction of efavirenz is debatable. **** > > **** > > Cheers,**** > > Rob ter Heine**** > > **** > > ------**** > > R. ter Heine, PhD, PharmD**** > > Hospital pharmacist i.t.**** > > **Meander** **Medical** **Center**, **Amersfoort**, The ****Netherlands*** > ***** > > T: +31-33-8502335**** > > E: [email protected]**** > > ** ** > ------------------------------ > > *Van:* [email protected] [mailto:[email protected]] > *Namens *Shankar Lanke > *Verzonden:* maandag 14 mei 2012 17:33 > *Aan:* nmusers > *Onderwerp:* [NMusers] Modeling variability in absorption and clearance > (Auto induction)**** > > Dear All,**** > > **** > > I am working on Efavirenz (NNRTI dosed at 600 mg/day oral) population > pharmacokinetic data analysis (70 patients, 800 samples). Intense sampling > data on day 1 and 14. Individual day 1 and 14 analysis shows an increased > absorption in few patients plus increased clearance (auto induction) in > some of these patients and other patients (who revealed no change in > absorption). It is shown in earlier clinical studies that fed state results > in increased bioavailability. I have no covariate information which may > support this (available info Wt, Sex, total protein and TBR). Moreover the > absorption profiles are very haphazard with troughs and peaks in the > absorption phase, similar to what Bulitta et.al 2009, Pg 3462-3471 > showed(Antimicrobial agents and chemotherapy). I have tried this > Michaelis-Menton model in absorption with and without lag time ( run > fails). **** > > **** > > NONMEM runs for one C.M. with no variability in absorption and clearance > as an OBF value of 1498, 2CM 1390 (Vd is low 68 liters cv% 7 and Vd perip > CV% 64 ). 2 CM with autoinduction model (for all patients)is OBV 1284 (run > fails). **** > > **** > > Efavirenz preclinical trials shows that dose variability results in non > linearity in absorption (Balani et.al 1998, vol 27, No.1), no clinical > trials supporting this info and dose is 600 mg/day in my data. Auto > induction was shown in clinical trials (zhu et.al). I have identified > the patients who have clearance and absorption variability and created two > columns in data sheet.Runs including the variability in absorption > and clearance for some patients completely fails with Vd as low as 30 and > perip as high as 400 liters.**** > > **** > > My questions to NM community are**** > > 1. How to handle this data if we dont have any covariate information for > absorption and clearance variability.**** > > 2. Any references to model the data without crashing the runs**** > > **** > > Your suggestions are appreciated.**** > > **** > > Thank you very much in advance.**** > > **** > > Regards,**** > > ** ** > > ** ** > ------------------------------ > > 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. > Assistant Professor > Department of Pharmaceutical Sciences > ****College** of **Pharmacy**** > The ****University** of **Findlay**** > (C) 678-232-3567 > (O) 419-434-5448 > Fax# 419-434-4390**** > -- Regards, Shankar Lanke Ph.D. Assistant Professor Department of Pharmaceutical Sciences College of Pharmacy The University of Findlay (C) 678-232-3567 (O) 419-434-5448 Fax# 419-434-4390