NONMEM Users Network Archive

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RE: Getting rid of correlation issues between CL and volume parameters

From: Bob Leary <Bob.Leary>
Date: Mon, 25 Nov 2013 10:04:53 -0500

Nele,
Basically what you have done is traded an off diagonal parameter in a two dimensional Omega matrix for an extra on-diagonal parameter in a three dimensional diagonal Omega matrix.
Y0u still have 3 Omega parameters either way.
For methods like SAEM and IMP, the two-dimensional formulation is much preferable since you end up in a lower 2-d dimensional eta space which a) is easier to sample,
b) is easily mu-modeled (not the case for the 3-d formulation) , and c) SAEM and IMP methods handle full block Omegas very naturally, in fact more naturally than
diagonal Omegas. With FOCEI it is not so clear if there would be any difference at all.



-----Original Message-----
From: owner-nmusers o:owner-nmusers@globomaxnm.com] On Behalf Of Mueller-Plock, Nele
Sent: Monday, November 25, 2013 2:05 AM
To: Leonid Gibiansky; 'nmusers'
Subject: RE: [NMusers] Getting rid of correlation issues between CL and volume parameters

Dear Leonid,

Thanks for your answer. Maybe I was not completely clear about the reasons why I tried to account for F1. The reason is that after oral dosing, a correlation between CL and should be present, as these parameters in reality represent CL/F and V/F. One way to account for this would be to estimate the correlation via the $OMEGA BLOCK syntax. As this is sometimes hard to estimate, I looked if any alternative is available, and then found the discussion of this topic in the provided link (http://www.wright-dose.com/tip2.php).
From your answer, I would conclude that the proposed code should only account for random between-subject variability, i.e. it should only consider the ETA on F1, but not the THETA (which in my example had values of 1, 0.8 and 0.5). Is this correct?

So whereas an increase in ETA on F1 without accounting for the correlation would automatically result in positive ETA values for CL and V, even without any inherent variability in true CL and V, with the code

F1=1
FF1=EXP(ETA(1))
CL=THETA()*EXP(ETA())/FF1
V=THETA()*EXP(ETA())/FF1

this would already be taken care of, and the $OMEGA BLOCK could be omitted. Right?

Thanks and best
Nele
______________________________________________________________
 
Dr. Nele Mueller-Plock, CAPM
Principal Scientist Modeling and Simulation Global Pharmacometrics Therapeutic Area Group
 
Takeda Pharmaceuticals International GmbH Thurgauerstrasse 130
8152 Glattpark-Opfikon (Zürich)
Switzerland

Visitor address:
Alpenstrasse 3
8152 Glattpark-Opfikon (Zürich)
Switzerland

Phone: (+41) 44 / 55 51 404
Mobile: (+41) 79 / 654 33 99
 
mailto: nele.mueller-plock@takeda.com
http://www.takeda.com

-----Original Message-----
From: Leonid Gibiansky [mailto:lgibiansky@quantpharm.com]
Sent: Freitag, 22. November 2013 19:44
To: Mueller-Plock, Nele; 'nmusers'
Subject: Re: [NMusers] Getting rid of correlation issues between CL and volume parameters

Nele,
I am not sure why would you like to divide by F1.
Can we just do it explicitly?

F1=EXP(ETA(1))
(or F1=function(dose)*EXP(ETA(1))
CL=..
V=..

F1 can be > 1 as it is not absolute but relative (to the other subjects); I assume that this is oral dose, not IV, correct?

In your code, be careful not to call it F1 as the nonmem will interpret it as bioavailability parameter, and you should not account for it twice.

So it should be either
F1=EXP(ETA(1))
CL=THETA()*EXP(ETA())
V=THETA()*EXP(ETA())

or

F1=1 (can me implicit and omitted)
FF1=EXP(ETA(1))
CL=THETA()*EXP(ETA())/FF1
V=THETA()*EXP(ETA())/FF1

but not

F1=EXP(ETA(1))
CL=THETA()*EXP(ETA())/F1
V=THETA()*EXP(ETA())/F1

Leonid




--------------------------------------
Leonid Gibiansky, Ph.D.
President, QuantPharm LLC
web: www.quantpharm.com
e-mail: LGibiansky at quantpharm.com
tel: (301) 767 5566



On 11/22/2013 12:14 PM, Mueller-Plock, Nele wrote:
> Dear all,
>
> I have come across an interesting proposal to account for correlation between CL and volume parameters by dividing by bioavailability within the NONMEM control stream:
>
> http://www.wright-dose.com/tip2.php
>
> I liked the approach, however I have been wondering how exactly to interpret the resulting parameter values for CL and V.
>
> As an illustration, a potential problem might be that we have doses of 10, 25 and 50 mg with a fixed bioavailability of 100% for the 10 mg dose, and bioavailabilities of 80% and 50% for the doses of 25 and 50 mg, respectively. In addition, a between-subject variability on F1 of ~30% would be present.
>
> If I now code my CL and V as follows:
> CL=THETA(1)/F1
> V=THETA(2)/F1,
> to account for the correlation between CL and V, what exactly would be the meaning/interpretation of THETA(1) and THETA(2)?
> As the THETAs would be the same for all doses, the CL of 50 mg would be twice as high as the one for the 10 mg dose – does that make sense, as we already estimated the reduced relative bioavailability using parameter F1?
>
> Any comments would be very much appreciated.
> Thanks and best
> Nele
>
>
>
> Dr. Nele Müller-Plock, CAPM
> Principal Scientist Modeling and Simulation Pharmacometrics
> Experimental Medicine
>
> Takeda Pharmaceuticals International GmbH
> 8152 Glattpark-Opfikon (Zürich)
> Switzerland
>
> Visitor address:
> Alpenstrasse 3
> 8152 Glattpark-Opfikon (Zürich)
> Switzerland
>
> Phone: (+41) 44 / 55 51 404
> Mobile: (+41) 79 / 654 33 99
> mailto: nele.mueller-plock
> http://www.takeda.com
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Received on Mon Nov 25 2013 - 10:04:53 EST

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