non-linear PK

9 messages 7 people Latest: Oct 06, 2005

non-linear PK

From: Jing Li Date: October 06, 2005 technical
From: "Jing Li" jli29@jhmi.edu Subject: [NMusers] non-linear PK Date: Thu, 06 Oct 2005 11:47:14 -0400 Hi, I am trying to fit a population PK model with nonlinear elimination (Michaelis-Menten) with NONMEM. The drug was given to 15 patients by 20-min infusion weekly. Each patient received 6 different doses each week for 6 weeks, and intense PK sampling was drawn after each dose. The drug shows apparent non-linear clearance. The following is the model control file. The model did not converge no matter how I changed the initial estimates. Is there any problem with the control file? Any thoughts would be appreciate! Best regards. Jing $PROB 20-MIN IV INFUSION MULTIPLE DOSE WITHOUT COVARIATES $INPUT ID WEEK AMT RATE TIME XDV DV MDV EVID ;XDV, observations, DV, log-transformed concentrations $DATA ANTISOMA_DART_3.csv IGNORE=@ $SUBROUTINES ADVAN9 TRANS1 TOL=3 $MODEL NPAR=9, NCOMP=3, COMP=(CENTRAL,DEFOBS), COMP=(PERIPH1), COMP=(PERIPH2) ;$ABB DERIV2=NO $PK VM = THETA(1) *EXP(ETA(1)) KM = THETA(7)*EXP(ETA(7)) V1 = THETA(2)*EXP(ETA(2)) V2 = THETA(3)*EXP(ETA(3)) V3 = THETA(4)*EXP(ETA(4)) Q2 = THETA(5)*EXP(ETA(5)) Q3 = THETA(6)*EXP(ETA(6)) SC = V1 K12 = Q2/V1 K21 = Q2/V2 K23 = Q3/V2 K32 = Q3/V3 OBS = XDV ;non-transformed observations $ERROR (ONLY OBSERVATION) DEL = 0 IF(F.EQ.0) DEL = .000001 IPRED = F + DEL W = SQRT(THETA(8)**2+THETA(9)**2*F*F) IPRED = LOG(IPRED) IRES = DV-IPRED IWRES = IRES/W Y = IPRED+ERR(1)*W $DES C1 = A(1)/V1 DADT(1) = - K12*A(1) - A(1)*VM/(KM+C1) DADT(2) = K12*A(1) - K21*A(2) + K32*A(3) - K23*A(2) DADT(3) = K23*A(2) - K32*A(3) $THETA (0,1) ;1 VM (uM/h) $THETA (0,3,10) ;2 V1 $THETA (0,5,20) ;3 V2 $THETA (.5,2,10) ;4 V3 $THETA (0,.2,5) ;5 Q2 $THETA (0,1,5) ;6 Q3 $THETA (10,200) ;7 KM (uM) $THETA (0,.5) ;8 SD ADD ERROR $THETA (0,.1) ;9 CV PROP ERROR $OMEGA .1 ;1 VM $OMEGA .1 ;2 V1 $OMEGA .3 ;3 V2 $OMEGA .1 ;4 V3 $OMEGA .1 ;5 Q2 $OMEGA .1 ;6 Q3 $OMEGA .1 ;7 KM $SIGMA 1 FIX $EST MAXEVALS=9990 PRINT=2 POSTHOC MSFO=msfb40 POSTHOC ;METH=1 INTER $COV $TAB ID ID WEEK AMT RATE ONEHEADER NOPRINT FILE=mytab40 $TAB ID TIME DV IPRED IWRES ONEHEADER NOPRINT FILE=sdtab40 $TAB ID VM KM V1 V2 V3 Q2 Q3 ETA1 ETA2 ETA3 ETA4 ETA5 ETA6 ONEHEADER NOPRINT FILE=patab40

Re: non-linear PK

From: Leonid Gibiansky Date: October 06, 2005 technical
From: Leonid Gibiansky Subject: Re: [NMusers] non-linear PK Date: Thu, 06 Oct 2005 12:27:16 -0400 Hi Jing, 1. You have way too many eta effects. Start with CL, central volume only, fix the rest to zero, at least to define the range of parameter values. You may add more later if needed. 2. This is an error: W = SQRT(THETA(8)**2+THETA(9)**2*F*F) you should use W = SQRT(THETA(8)**2+THETA(9)**2/F/F) 3. This is an error as well: DADT(1) = - K12*A(1) - A(1)*VM/(KM+C1) DADT(2) = K12*A(1) - K21*A(2) + K32*A(3) - K23*A(2) you are missing K21*A(2) in DADT(1) = - K12*A(1) - A(1)*VM/(KM+C1)+ K21*A(2) Leonid

Re: non-linear PK

From: Brenda Cirincione Date: October 06, 2005 technical
From: Brenda Cirincione Brenda.Cirincione@cognigencorp.com Subject: Re: [NMusers] non-linear PK Date: Thu, 06 Oct 2005 12:29:45 -0400 Hi, At a quick glance and without knowing more about your specific PK model, one of the things that I noticed in your control stream is that the differential equation for compartment 2, Dadt(2), you include a term -K21*A(2), but a corresponding term +K21*A(2) is not included in the Dadt(1) differential equation. This may contribute to the difficulties that you are seeing. Regards, Brenda

Re: non-linear PK

From: Juan Jose Perez Ruixo Date: October 06, 2005 technical
From: "Perez Ruixo, Juan Jose [PRDBE]" JPEREZRU@PRDBE.jnj.com Subject: Re: [NMusers] non-linear PK Date: Thu, 6 Oct 2005 18:51:56 +0200 Dear Jing, The input from the second compartment to the first compartment is missing. Probably what you want to fit is a system of DE as follows DADT(1) = - K12*A(1) + K21*A(2) - A(1)*VM/(KM+C1) DADT(2) = K12*A(1) - K21*A(2) - K23*A(2) + K32*A(3) DADT(3) = + K23*A(2) - K32*A(3) However, I'm not sure you want to start with a catenary model, instead of a mamillary model. If you like to test a mamillary model, it should be as follows: DADT(1) = - K12*A(1) + K21*A(2) - K13*A(1) + K31*A(3) - A(1)*VM/(KM+C1) DADT(2) = K12*A(1) - K21*A(2) DADT(3) = + K13*A(1) - K31*A(3) Regards, Juan Jose Perez Ruixo, PhD. Principal Scientist. Advanced PK/PD Modelling & Simulation, Global Clinical Pharmacokinetic and Clinical Pharmacology, Johnson & Johnson Pharmaceutical Research & Development, a Division of Janssen Pharmaceutica, NV. Email: jperezru@prdbe.jnj.com

Re: non-linear PK

From: Kenneth Kowalski Date: October 06, 2005 technical
From: "Kowalski, Ken" Ken.Kowalski@pfizer.com Subject: Re: [NMusers] non-linear PK Date: Thu, 6 Oct 2005 13:05:35 -0400 Leonid, I think W is correctly specified in Jing's control stream below. As she has coded it, W is the residual standard deviation (given the ETAs) for the combined proportional and additive error model. That is, Var(Y | ETAs) = (W2)Var(ERR(1)) = W2 = THETA(8)**2 + (THETA(9)**2)*F*F where THETA(8) is the residual SD for the additive component and THETA(9) is the residual CV for the proportional component. Ken

Re: non-linear PK

From: Leonid Gibiansky Date: October 06, 2005 technical
From: Leonid Gibiansky leonidg@metrumrg.com Subject: Re: [NMusers] non-linear PK Date: Thu, 06 Oct 2005 13:20:13 -0400 Ken, Note that data are log-transformed. See http://www.cognigencorp.com/nonmem/nm/99apr232002.html for Mats Karlsson explanation how to apply combined error in the log-transformed case. ----------------------cut here ----------------- To get the same error structure for log-transformed data as the additive+proportional on the normal scale, I use Y=LOG(F)+SQRT(THETA(x)**2+THETA(y)**2/F**2)*EPS(1) with $SIGMA 1 FIX THETA(x) and THETA(y) will have the same meaning as on the untransformed scale with Y=F+SQRT(THETA(y)**2+THETA(x)**2*F**2)*EPS(1) with $SIGMA 1 FIX ----------------------cut here ---------------------- Leonid

Re: non-linear PK

From: Paul Hutson Date: October 06, 2005 technical
From: Paul Hutson prhutson@pharmacy.wisc.edu Subject: Re: [NMusers] non-linear PK Date: Thu, 06 Oct 2005 12:20:29 -0500 Jing: From a first look: 1) your central compartment (1) does not appear to reflect the return from compartment 2 DADT(1) = - K12*A(1) - A(1)*VM/(KM+C1)+ K21*A(2) 2) your saturable term should use C1 instead of A(1) in order to yield units of mass/time. 3) Is there a reason you are setting this up to have no exchange between compartment 1 and 3? Paul > > $DES > C1 = A(1)/V1 > DADT(1) = - K12*A(1) - A(1)*VM/(KM+C1) > DADT(2) = K12*A(1) - K21*A(2) + K32*A(3) - K23*A(2) > DADT(3) = K23*A(2) - K32*A(3) > > -- Paul R. Hutson, Pharm.D. Associate Professor UW School of Pharmacy 777 Highland Avenue Madison WI 53705-2222 Tel 608.263.2496 Fax 608.265.5421 Pager 608.265.7000, p7856

Non-linear CL

From: Toufigh Gordi Date: October 06, 2005 technical
From: "Gordi, Toufigh" Toufigh.Gordi@cvt.com Subject: [NMusers] Non-linear CL Date: Thu, 6 Oct 2005 13:01:28 -0700 Jing, Scrolling through your control stream, I find at least 3 possible sources of error. The first one is the large number of ETAs you have. All your parameters are associated with a variability terms, i.e. 6 ETAs! Do you really have enough information in your data to be able to estimate these parameters? In my limited experience, 1-3 ETAs are normally sufficient in most models. The second is the lack of infusion instructions to NONMEM. If your compound is given as infusion, you need to tell NONMEM about it. Third problem is with your $DES. The way it is written now, your drug lives the first compartment through elimination and transfer to compartment 2. Nothing comes back to it. However, in the next line, the drug leaves compartment 2 by going back to comp 1. The mass balance is not preserved. Also, you have a third compartment that is in contact with comp 2 but not the central compartment (comp 1). I think you will have issues with the ability to identify the model parameters, unless you have observations in compartments 2 or 3. Is this supported by other knowledge you have about how your compound is distributed and eliminated? I also have a question. When you state that CL in nonlinear, is it concentration- or time-dependent? In other words, does clearance change with a single dose or from one dose to the next? Toufigh Gordi P.s. There seems to be something wrong with the server. I sent this message this morning and it never got through, while I get double copies of other people's mails. I have had similar experience before. Associate Director of Clinical Pharmacology CV Therapeutics Inc. 3172 Porter Dr. Palo Alto, CA 94304 Tel.: 650-384-8929

Re: Non-linear CL

From: Jing Li Date: October 06, 2005 technical
From: "Jing Li" jli29@jhmi.edu Subject: Re: [NMusers] Non-linear CL Date: Thu, 06 Oct 2005 16:47:51 -0400 Hi, Thanks very much for everyone's input! As you pointed out, I fixed the problems with $DES and Error model, and changed subroutine of advan9 to advan6 in my control stream. Also, I reduced the number of ETAs. The model is running, looks promising. The drug shows a concentration- and dose-dependent CL, as well as a concentration-dependent protein binding. That means, the unbound fraction changes with time (with highest unbound fraction at the end of infusion). I also have unbound concentrations. So, eventually, I will fit the total and unbound concentration simultaneously, with a link of a non-linear protein binding function. Best regards. Jing _______________________________________________________