Query on model development

Dear All, I am new to the field of POP-PK. We are developing a POP-PK model for our in-house drug. The conc. are in ng/mL and dose is in mg. The drug is administered orally and follows 1-compartment model. It has a short half-life of 2-3 h. We have developed the basic model using rich data from serial sampling of healthy subjects. -We have determined the Bayesian estimates of CL and V. But I think, we are overestimating these values. If we determine CL , using non-compartmental analysis (rich data )we are getting lower estimates (800 L/h), while using NONMEM (using same rich data), we are getting quite high estimates (mean for 25 mg- 4000 L/hr). Kindly give your inputs on further modifying this model to get an irreducible model and also validating the model. Thanking you in anticipation. Thanks and regards Tausif Ahmed, Ph.D. Senior Research Scientist Metabolism and Pharmacokinetics Department, Ranbaxy Research Lab., India Model: PROB Oral RSd-RMD-PK01-healthy study $DATA RSD_PK01ctdata.csv IGNORE=C $INPUT ID TIME CONC=DV DOSE AMT AGE WT MDV $SUBROUTINES ADVAN2 TRANS2; One Compartment Linear Model $PK TVCL=THETA(1) ; mean clearance CL=TVCL*EXP(ETA(1)) TVV=THETA(2) ; mean central volume V=TVV*EXP(ETA(2)) K=CL/V ;reparameterization required S1=V/1000 KA=THETA(3) $THETA (0, 100) ; clearance estimate (L\hr) (0, 100) ; volume estimate (L) (0, 1.5) ; Absorption rate constant $OMEGA .16 .16 ; forty percent cv $SIGMA .16 ; forty percent cv $ERROR IPRED=F Y=F+ERR(1) $ESTIMATION METHOD=0 MAXEVAL=9999 PRINT=5 POSTHOC SIGDIGITS=4 $COVARIANCE $TABLE ID TIME DV DOSE CL V ETA1 ETA2 AMT AGE WT MDV NOPRINT ONEHEADER FILE=CS1_oralRSDRMDPK01.PAR $SCAT CONC VS TIME OUTPUT MINIMUM VALUE OF OBJECTIVE FUNCTION ************************************************** 6971.242 ************************************************** ************************************************************************ ************************************************ ******************** ******************** FINAL PARAMETER ESTIMATE ************************************************************************ ************************************************ THETA - VECTOR OF FIXED EFFECTS PARAMETERS ********* TH 1 TH 2 TH 3 4.97E+03 8.02E+03 1.70E-01 OMEGA - COV MATRIX FOR RANDOM EFFECTS - ETAS ******** ETA1 ETA2 ETA1 + 2.57E+00 ETA2 + 0.00E+00 1.14E+00 SIGMA - COV MATRIX FOR RANDOM EFFECTS - EPSILONS **** EPS1 EPS1 + 4.72E+02 (i) The information contained in this e-mail message is intended only for the confidential use of the recipient(s) named above. This message is privileged and confidential. If the reader of this message is not the intended recipient or an agent responsible for delivering it to the intended recipient, you are hereby notified that you have received this document in error and that any review, dissemination, distribution, or copying of this message is strictly prohibited. If you have received this communication in error, please notify us immediately by e-mail, and delete the original message. (ii) The sender confirms that Ranbaxy shall not be responsible if this email message is used for any indecent, unsolicited or illegal purposes, which are in violation of any existing laws and the same shall solely be the responsibility of the sender and that Ranbaxy shall at all times be indemnified of any civil and/ or criminal liabilities or consequences there. <<Public.gif>>

Hello Tausif Please check the scaling factor that you included in the model. It should be S2=V/1000. I think this should correct the differences that you are observing. Atul Venkatesh Atul Bhattaram Pharmacometrics US Food and Drug Administration "The contents of this message are mine personally and do not necessarily reflect any position of the Government or the Food and Drug Administration." ________________________________

Use S2=V/1000 instead of S1=V/1000 Leonid Tausif Ahmed wrote: > Dear All, > > I am new to the field of POP-PK. We are developing a POP-PK model for our in-house drug. The conc. are in ng/mL and dose is in mg. The drug is administered *orally* and follows *1-compartment* model. It has a short half-life of 2-3 h. We have developed the basic model using rich data from serial sampling of healthy subjects. -We have determined the Bayesian estimates of CL and V. But I think, we are overestimating these values. If we determine CL , using non-compartmental analysis (rich data )we are getting lower estimates (800 L/h), while using NONMEM (using same rich data), we are getting quite high estimates (mean for 25 mg- 4000 L/hr). Kindly give your inputs on further modifying this model to get an irreducible model and also validating the model. Thanking you in anticipation. Thanks and regards > > Tausif Ahmed, Ph.D. > Senior Research Scientist > Metabolism and Pharmacokinetics Department, > Ranbaxy Research Lab., India > > Model: PROB Oral RSd-RMD-PK01-healthy study > > $DATA RSD_PK01ctdata.csv IGNORE=C > > $INPUT ID TIME CONC=DV DOSE AMT AGE WT MDV $SUBROUTINES ADVAN2 TRANS2; One Compartment Linear Model > > $PK > TVCL=THETA(1) ; mean clearance > CL=TVCL*EXP(ETA(1)) > TVV=THETA(2) ; mean central volume > V=TVV*EXP(ETA(2)) > K=CL/V ;reparameterization required > S1=V/1000 > KA=THETA(3) > > $THETA (0, 100) ; clearance estimate (L\hr) > > (0, 100) ; volume estimate (L) > (0, 1.5) ; Absorption rate constant > > $OMEGA .16 .16 ; forty percent cv $SIGMA .16 ; forty percent cv $ERROR > > IPRED=F > Y=F+ERR(1) > > $ESTIMATION METHOD=0 MAXEVAL=9999 PRINT=5 POSTHOC SIGDIGITS=4 $COVARIANCE $TABLE ID TIME DV DOSE CL V ETA1 ETA2 AMT AGE WT MDV NOPRINT ONEHEADER FILE=CS1_oralRSDRMDPK01.PAR $SCAT CONC VS TIME *OUTPUT* ** MINIMUM VALUE OF OBJECTIVE FUNCTION ************************************************** 6971.242 ************************************************** > > ************************************************************************************************************************ > > ******************** ******************** FINAL PARAMETER ESTIMATE ************************************************************************************************************************ > > THETA - VECTOR OF FIXED EFFECTS PARAMETERS ********* > > TH 1 TH 2 TH 3 > > 4.97E+03 8.02E+03 1.70E-01 > > OMEGA - COV MATRIX FOR RANDOM EFFECTS - ETAS ******** > > ETA1 ETA2 > > ETA1 > > + 2.57E+00 > > ETA2 > > + 0.00E+00 1.14E+00 > > SIGMA - COV MATRIX FOR RANDOM EFFECTS - EPSILONS **** > > EPS1 > > EPS1 > > + 4.72E+02 > > (i) The information contained in this e-mail message is intended only for the confidential use of the recipient(s) named above. This message is privileged and confidential. If the reader of this message is not the intended recipient or an agent responsible for delivering it to the intended recipient, you are hereby notified that you have received this document in error and that any review, dissemination, distribution, or copying of this message is strictly prohibited. If you have received this communication in error, please notify us immediately by e-mail, and delete the original message. > > (ii) The sender confirms that Ranbaxy shall not be responsible if this email message is used for any indecent, unsolicited or illegal purposes, which are in violation of any existing laws and the same shall solely be the responsibility of the sender and that Ranbaxy shall at all times be indemnified of any civil and/ or criminal liabilities or consequences there.

Public StationerySince the concentration measured is in ng/ml (ug/L) you have to make correction as follows: S2=V/10000 ; S2 because you are using one compartment with absorption (S2 - Scale for central compartment) - Krishna R. Devarakonda ----- Original Message -----

Hi Tausif, When you use ADVAN2 there are three types of scaling factors you can use depending upon the problem (S1=Depot, S2=Central, S3=Output). So in your case, it should be S2=V/1000 instead of S1=V/1000. Hope it helps Regards Nitin Tausif Ahmed <[EMAIL PROTECTED]> wrote: Dear All, I am new to the field of POP-PK. We are developing a POP-PK model for our in-house drug. The conc. are in ng/mL and dose is in mg. The drug is administered orally and follows 1-compartment model. It has a short half-life of 2-3 h. We have developed the basic model using rich data from serial sampling of healthy subjects. -We have determined the Bayesian estimates of CL and V. But I think, we are overestimating these values. If we determine CL , using non-compartmental analysis (rich data )we are getting lower estimates (800 L/h), while using NONMEM (using same rich data), we are getting quite high estimates (mean for 25 mg- 4000 L/hr). Kindly give your inputs on further modifying this model to get an irreducible model and also validating the model. Thanking you in anticipation. Thanks and regards Tausif Ahmed, Ph.D. Senior Research Scientist Metabolism and Pharmacokinetics Department, Ranbaxy Research Lab., India Model: PROB Oral RSd-RMD-PK01-healthy study $DATA RSD_PK01ctdata.csv IGNORE=C $INPUT ID TIME CONC=DV DOSE AMT AGE WT MDV $SUBROUTINES ADVAN2 TRANS2; One Compartment Linear Model $PK TVCL=THETA(1) ; mean clearance CL=TVCL*EXP(ETA(1)) TVV=THETA(2) ; mean central volume V=TVV*EXP(ETA(2)) K=CL/V ;reparameterization required S1=V/1000 KA=THETA(3) $THETA (0, 100) ; clearance estimate (L\hr) (0, 100) ; volume estimate (L) (0, 1.5) ; Absorption rate constant $OMEGA .16 .16 ; forty percent cv $SIGMA .16 ; forty percent cv $ERROR IPRED=F Y=F+ERR(1) $ESTIMATION METHOD=0 MAXEVAL=9999 PRINT=5 POSTHOC SIGDIGITS=4 $COVARIANCE $TABLE ID TIME DV DOSE CL V ETA1 ETA2 AMT AGE WT MDV NOPRINT ONEHEADER FILE=CS1_oralRSDRMDPK01.PAR $SCAT CONC VS TIME OUTPUT MINIMUM VALUE OF OBJECTIVE FUNCTION ************************************************** 6971.242 ************************************************** ************************************************************************************************************************ ******************** ******************** FINAL PARAMETER ESTIMATE ************************************************************************************************************************ THETA - VECTOR OF FIXED EFFECTS PARAMETERS ********* TH 1 TH 2 TH 3 4.97E+03 8.02E+03 1.70E-01 OMEGA - COV MATRIX FOR RANDOM EFFECTS - ETAS ******** ETA1 ETA2 ETA1 + 2.57E+00 ETA2 + 0.00E+00 1.14E+00 SIGMA - COV MATRIX FOR RANDOM EFFECTS - EPSILONS **** EPS1 EPS1 + 4.72E+02 (i) The information contained in this e-mail message is intended only for the confidential use of the recipient(s) named above. This message is privileged and confidential. If the reader of this message is not the intended recipient or an agent responsible for delivering it to the intended recipient, you are hereby notified that you have received this document in error and that any review, dissemination, distribution, or copying of this message is strictly prohibited. If you have received this communication in error, please notify us immediately by e-mail, and delete the original message. (ii) The sender confirms that Ranbaxy shall not be responsible if this email message is used for any indecent, unsolicited or illegal purposes, which are in violation of any existing laws and the same shall solely be the responsibility of the sender and that Ranbaxy shall at all times be indemnified of any civil and/ or criminal liabilities or consequences there. Nitin Mehrotra, Ph.D Post Doctoral Research Fellow 874 Union Avenue, Suite4.5p/5p Department of Pharmaceutical Sciences University of Tennessee Health Science Center Memphis, TN, USA-38163 901-448-3385 (Lab) [EMAIL PROTECTED] --------------------------------- Be a better Globetrotter. Get better travel answers from someone who knows. Yahoo! Answers - Check it out.