- On 21 May 2004 at 19:40:44, L T (choco4evermore.-a-.yahoo.ca) sent the message
Hi all

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I have a couple questions regarding non-compartmental modeling. We would

like to determine the Ka of lopinavir from steady-state PK data (PK

profiles). LPV is given orally (assumes 1st order absorption and 1st order

elimination), and all patients are at steady state. We modeled our data

using WinNonlin 4.1, non-compartmental analyses. Here are my questions:

1. Is it true that AUMC(0-infinity) = AUMC (tau, steady-state)? Just like

AUC (0-infinity) = AUC (tau)?

2. from my previous studies, MRT (oral) = MRT (iv) + 1/Ka

and also MRT (oral) = 1/K + 1/Ka

where K is the elimination rate constant and Ka the absorption rate

constant. Is it valid for me to calculate Ka from my non-compartmental

results using K=lambda z, and MRT(oral) = AUMC(tau)/AUC(tau)?

I would appreciate any advice in this matter.

Thank you!

Lillian Ting

University of British Columbia - On 25 May 2004 at 20:28:03, "Hans Proost" (j.h.proost.-a-.farm.rug.nl) sent the message
Dear Lillian,

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With respect tu your question:

> 1. Is it true that AUMC(0-infinity) = AUMC (tau, steady-state)? Just

like

> AUC (0-infinity) = AUC (tau)?

No, this is not true, as can be concluded from a simple numerical example. I

can send you a spreadsheet demonstrating this. If k is large, both values

are close to each other, since both profiles are close to each other. In

'normal' cases, AUC(0-infinity) is larger than AUC(tau); e.g. for k = 0.05

/h, ka = 2 /h, and tau = 24 h, the difference is about a factor 2.

Consequently, the answer to your second question is also negative.

Best regards,

Hans Proost

Johannes H. Proost

Dept. of Pharmacokinetics and Drug Delivery

University Centre for Pharmacy

Antonius Deusinglaan 1

9713 AV Groningen, The Netherlands

tel. 31-50 363 3292

fax 31-50 363 3247

Email: j.h.proost.aaa.farm.rug.nl - On 26 May 2004 at 20:02:12, Arthur B Straughn (astraughn.at.utmem.edu) sent the message
Hans,

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Have to disagree with you about being able to evaluate Ka from steady-state

data using non-compartment analysis. I do agree that AUMC(0-inf) single

dose is not equal to AUMC(0-tau) at steady-state, but it is a simple

spreadsheet exercise to conduct reverse superposition on the steady-state

data to acquire single dose concentrations. From the single dose data AUC

and AUMC will give correct MRT and thus ka. There are several

assumptions/conditions however that need to be met: 1. The terminal

disposition can be determined from the steady-state data (study design may

require wash out data) 2. Absorption is first order (true for single dose

as well but if one only wants MAT the order of absorption in not

important). The reverse superposition doesn't even require data to be at

steady state as long as you have characterized the dosing interval and

terminal disposition appropriately with the sampling scheme. Again you may

or may not need wash out to get K. I think there was a paper on

this topic in J. Pharm. Sci. a number of years ago.

Art Straughn, Pharm.D.

Professor and Director Drug Research Laboratory

Department of Pharmaceutical Sciences

University of Tennessee

Memphis, TN

astraughn.aaa.utmem.edu - On 27 May 2004 at 19:32:44, L T (choco4evermore.aaa.yahoo.ca) sent the message
Hi Hans

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Thanks for the input. Could you send me the spreadsheet you mentioned so I

can take a look?

Unfortunately we only have steady-state data. Maybe there is some other

way to calculate Ka?

Thanks!

Lillian

Univeristy of British Columbia - On 27 May 2004 at 19:45:18, "J.H.Proost" (J.H.Proost.-at-.farm.rug.nl) sent the message
Dear Arthur,

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You wrote:

>"Have to disagree with you about being able to evaluate Ka from

>steady-state data using non-compartment analysis."

I did not say whether or not Ka can be calculated. I said that AUMC after

single dose and at steady state are different. This implies that the

suggested method for calculating Ka is not correct.

>"... it is a simple spreadsheet exercise to conduct reverse superposition

>on the steady-state data to acquire single dose concentrations."

Thank you for pointing to this method. I did not know it, and I will have a

look at the reference in J. Pharm. Sci. But I have my doubts on such

methods with respect to their accuracy and precision, apart from the

numerous assumptions that cannot be checked properly.

Personally I am not in favor of noncompartmental pharmacokinetics, mainly

because it does not allow a prediction of the time course of the

concentration. The latter is essential for relating dose to therapeutic

activity of a drug, a key issue in pharmacokinetics. In my view, the

advantage of not using a (compartmental) model does not counterbalance this

disadvantage. What can we learn from noncompartmental pharmacokinetics? I

posed this question in the PharmPK group some time ago, but did not learn much.

Best regards,

Hans Proost

Johannes H. Proost

Dept. of Pharmacokinetics and Drug Delivery

University Centre for Pharmacy

Antonius Deusinglaan 1

9713 AV Groningen, The Netherlands

tel. 31-50 363 3292

fax 31-50 363 3247

Email: j.h.proost.at.farm.rug.nl - On 28 May 2004 at 16:22:26, "Art Straughn" (astraughn.at.utmem.edu sent the message
Hans,

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Sorry, I just meant to disagree with the implications (not the statement),

that since AUMC(0-inf) single dose is not the same as AUMC(0-Tau), then Ka

could not be determined using non-compartment analysis with ss data. I am

not a fan of "connect-the-dots" for AUMC determinations anyway because of

the extensive extrapolation (usually 20% or more) when compared to

extrapolation of AUC (5 to 10%). As you point out, questions about

precision and accuracy are brought into the picture. This though, should not

distract from the value these kinetic parameters have had related to

absorption and disposition modeling.

As far as which is better: "connect-the-dots" (non-compartment) vs.

"minimizing SSE"(compartment), it depends on what "truth" you want to glean

from the data. Generally, regulatory truth requires the use of

"connect-the-dots", while intellectual truth mandates the use of "Minimize

SSE". The real truth is probably somewhere in between. Please note: I am

not implying regulators only accept "connect-the-dots" analysis as fondly

referred to by Nick H. as Mickey Mouse Kinetics.

Art Straughn, Pharm.D.

Professor and Director

Drug Research Laboratory

University of Tennessee

874 Union Ave

Suite 5P

Memphis, TN 38163

E-mail: ASTRAUGHN.at.UTMEM.EDU

Phone: (901) 448-6033

Fax: (901) 448-6940 - On 28 May 2004 at 16:27:50, L T (choco4evermore.aaa.yahoo.ca sent the message
Hi Arthur

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Thanks for your suggestion. Could you send me that spreadheet that does

reverse superposition on steady-state data please? I didn't know about

this method and would like to give it a try.

I only have steady-state data, and no wash-out period in this

study. Hopefully we can still utilize such data.

Thanks a lot!

Cheers,

Lillian

University of British Columbia

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