Re: Cone shaped DV-PRED

From: bulitta@ibmp.osn.de Subject: Re: [NMusers] Cone shaped DV-PRED Date: Wed, April 20, 2005 9:48 pm Dear Dr Vakily, One proposal to model your data would be to dose a zero order input into the gut compartment with first order absorption from the gut into the central compartment. You might add more flexibility to the absorption process by adding a lag-time for the zero-order input. It is questionable, whether this model has a real mechanistic interpretation. However, you can use e.g. ADVAN 2 / 4 / 12, and thus it is very fast. I am not sure, if your data (5 points per profile) allow to estimate all the parameters and their between subject variability (BSV). From my experience, especially BSV on the duration (TK0) of the zero order input may become difficult. I usually do not include BSV on TK0, unless it really improves the predictive performance. I noticed a tendency that the predictive performance was better, with a BLOCK structure for the OMEGAs of the absorption parameters. After Nick showed me how to do this, I was happy to test this model and a series of others on about 10 drugs with complex absorption characteristics (solubility limit, active transporters, pH-dependent lipophilicity (Log D) etc.). Maybe it only worked, since I had at least 10 data points per profile. However, it might be worth to give it a try. I would recommend to start with a one-compartment disposition model to get reasonable estimates for the absorption parameters (and their variability) and then add more disposition compartments, if required. I got this model to work with three disposition compartments with convincing predictive performance. However, if the initials for the absorption parameters are really bad, there is a good chance that this model fails completely. If you still experience an insufficient predictive performance in the "Cmax region", I would try the "sequential independent zero and then first order absorption model" described in Nicks paper below. Please find two papers on complex absorption models and the control stream below. Hope this helps. Best wishes Juergen ---------------------------------------------------- Juergen Bulitta, M.Sc. Research Scientist IBMP - Institute for Biomedical and Pharmaceutical Research Paul-Ehrlich-Strasse 19 90562 Nurnberg - Heroldsberg Germany ---------------------------------------------------- Holford, N. H., R. J. Ambros, and K. Stoeckel. 1992. Models for describing absorption rate and estimating extent of bioavailability: application to cefetamet pivoxil. J Pharmacokinet Biopharm 20:421-42. Piotrovskij, V. K., G. Paintaud, G. Alvan, and T. Trnovec. 1994. Modeling of the saturable time-constrained amoxicillin absorption in humans. Pharm Res 11:1346-51. $PROBLEM Zero order input into the gut compartment $INPUT ID TIME AMT RATE CMT EVID DVID DV $DATA ../Data/Raw_data.csv IGNORE=# $ESTIM MAXEVAL=9999 NOABORT PRINT=1 METHOD=COND INTERACTION SLOW SIG=5 $COV $SUB ADVAN4 TRANS4 $THETA (0,10) ;POP_CLT unit L/h total body clearance $THETA (0,20) ;POP_V1 unit L volume of central compartment $THETA (0,100) ;POP_V2 unit L volume of peripheral compartment $THETA (0,10) ;POP_CLD2 unit L/h intercompartmental clearance $THETA (0,15) ;POP_TABS unit min half-life of absorption from gut into central compartment $THETA (0,36) ;POP_TK0 unit min duration of zero order input into the gut compartment $THETA (0,12) ;POP_TLAG unit min lag time for the zero order input into the gut $OMEGA 0.05 ; BSVCLT $OMEGA 0.08 ; BSVVSS $OMEGA BLOCK(3) 0.2 ; BSVTK0 0.01 0.01 ; BSVTABS 0.01 0.01 0.3 ; BSVLAG $SIGMA 0.01 ;cvcp $SIGMA 0.001 ;sdcp $PK CL = POP_CLT*EXP(BSVCLT) V2 = POP_V1*EXP(BSVVSS) V3 = POP_V2*EXP(BSVVSS) Q = POP_CLD2 TABS = POP_TABS*EXP(BSVTABS) KA = LOG(2)/(TABS/60) S2 = V2 Tk0 = POP_Tk0*EXP(BSVTK0) D1 = TK0/60 TLAG = POP_TLAG*EXP(BSVLAG) ALAG1 = TLAG/60 $ERROR CP=F Y=CP*(1+CVCP)+SDCP $TABLE ID TIME AMT CMT EVID DVID CL V2 V3 KA TK0 Y ONEHEADER NOPRINT FILE=Zero_order_input_into_gut.fit ######################### raw_data.csv example #ID,TIME,AMT,RATE,CMT,EVID,DVID,DV 1,0,800,-2,1,1,0,. 1,0,.,.,.,2,1,. 1,0.167,.,.,.,2,1,. 1,0.333,.,.,.,0,1,0.12 1,0.5,.,.,.,0,1,0.95 1,0.75,.,.,.,0,1,1.5 1,1,.,.,.,0,1,2.6 1,2,.,.,.,0,1,7.2 1,3,.,.,.,0,1,13.5 1,4,.,.,.,0,1,12.2 1,6,.,.,.,0,1,11.2 1,8,.,.,.,0,1,10.3 1,12,.,.,.,0,1,7.92 1,16,.,.,.,0,1,5.51 1,24,.,.,.,0,1,2.98 1,36,.,.,.,0,1,0.82 1,48,.,.,.,0,1,0.25 ################################ _______________________________________________________