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RE: simultaneous PK/PD

From: Elassaiss - Schaap, J. - <jeroen.elassaiss>
Date: Thu, 24 Jun 2010 09:17:15 +0200

Nick,
 
Thank you for your feedback on that! Has this been described somewhere?
 
Jeroen

________________________________

From: owner-nmusers
On Behalf Of Nick Holford
Sent: Thursday, 24 June, 2010 8:28
To: nmusers
Subject: Re: [NMusers] simultaneous PK/PD


Jeroen,

There is no need to defined a different EPS for PK and PD. Every =
observation record has a new random instance of EPS associated with it. =
So if there is only one random residual error parameter (PK or PD) then =
only one EPS is needed.

In this particular case EPS(1) is always mean 0 and variance 1 but it is =
scaled by THETA(8) for PK and THETA(9) for PD so that the residual error =
is appropriate for the type of observation.

There is no implied correlation between the random residual error.

Nick

Elassaiss - Schaap, J. (Jeroen) wrote:

        Dear Hauke,
         
        Moreover in this case, I would assign a different sigma to PK and PD. =
Your model actually states the belief that the variability in PK and PD =
are 100% correlated (unless they are always measured at different =
times). If you have background support for such a model it is fine, but =
in general I would advice to associate EPS(1) with THETA(8) for PK and =
EPS(2) with THETA(9) for PD.
          
        Hope this helps,
        Jeroen
         

        Modeling & Simulation Expert
        Pharmacokinetics, Pharmacodynamics & Pharmacometrics (P3) - DMPK
        MSD
        PO Box 20 - AP1112
        5340 BH Oss
        The Netherlands
        jeroen.elassaiss
        T: +31 (0)412 66 9320
        F: +31 (0)412 66 2506
        www.msd.com

        
        
________________________________

        From: owner-nmusers
[mailto:owner-nmusers
        Sent: Wednesday, 23 June, 2010 14:54
        To: nmusers
        Subject: [NMusers] simultaneous PK/PD
        
        

        Dear NMusers,

        

        I want to combine my sequential PK and PD model to one simultaneous =
model. In both models I used an exponential error model =
(log-transformation). When I write the model as follows, NONMEM gives me =
this error message:

        
        326 RANDOM VARIABLE IS DEFINED IN A NESTED IF STRUCTURE.

        

        Leaving out the condition C.GT.0 will also lead to errors. Is there =
another way to write this?

        

        Thanks

        

        Hauke

        

        

        $ERROR

          C1=(A(1)/V1)

          C3=A(3)

          

          IPRE=0

          

          IF (M1H2.EQ.1) THEN

                    IF (C1.GT.0) IPRE = LOG(C1)

                    IRES = DV-IPRE

                    W = EPS(1)*THETA(8)

                    Y = IPRE+W

          ENDIF

          

          IF (M1H2.EQ.2) THEN

                    IF (C3.GT.0) IPRE = LOG(C3)

        IRES = DV-IPRE

                    W = EPS(1)*THETA(9)

                    Y = IPRE+W

          ENDIF

          

          DEL = 0

          IF(W.EQ.0) DEL = 1

          IWRE = IRES/(W+DEL)

        

        $SIGMA

         1 FIX

        

        -----------------------------

        Hauke Rühs

        Apotheker

        Pharmazeutisches Institut

        - Klinische Pharmazie -

        An der Immenburg 4

        53121 Bonn

        

        Tel: + 49-(0)228 73-5781

        Fax: + 49-(0)228 73-9757

        

        www.klinische-pharmazie.info <http://www.klinische-pharmazie.info/>

        

        

        

________________________________

        This message and any attachments are solely for the intended recipient. =
If you are not the intended recipient, disclosure, copying, use or =
distribution of the information included in this message is prohibited =
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________________________________



--
Nick Holford, Professor Clinical Pharmacology
Dept Pharmacology & Clinical Pharmacology
University of Auckland,85 Park Rd,Private Bag 92019,Auckland,New Zealand
tel:+64(9)923-6730 fax:+64(9)373-7090 mobile:+64(21)46 23 53
email: n.holford
http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford

This message and any attachments are solely for the intended recipient. =
If you are not the intended recipient, disclosure, copying, use or =
distribution of the information included in this message is prohibited =
--- Please immediately and permanently delete.

Received on Thu Jun 24 2010 - 03:17:15 EDT

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