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

-----Original Message----- From: Bob Leary [Bob.Leary .com<mailto:Bob.Leary Sent: Monday, November 25, 2013 04:05 PM W. Europe Standard Time To: Mueller-Plock, Nele; Leonid Gibiansky; 'nmusers' Subject: RE: [NMusers] Getting rid of correlation issues between CL and volume parameters 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 obomaxnm.com [mailto:owner-nmusers 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 http://www.takeda.com -----Original Message----- From: Leonid Gibiansky [mailto:lgibiansky 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 > -------------------------------------------------------------------- > > The content of this email and of any files transmitted may contain confidential, proprietary or legally privileged information and is intended solely for the use of the person/s or entity/ies to whom it is addressed. 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