Dear all,
I am creating a dataset with the SS=2 option and I noticed an unexpected prediction profile that indicated that I am misinterpreting the way SS works in NONMEM... I would appreciate any feedback.
My understanding of the SS option in NONMEM is that the dose is assumed as previously given at regular intervals (specified by II), and the level of drug concentration resulting from this process is calculated. There are different options (1, 2 and 3), which I list below to clarify the way I understand them to work, so that it might be clear where I am mistaken.
According to the NONMEM guide, SS=1 should zero-out all system compartments and reset them to the value resulting only from the steady-state dose, thus virtually forgetting the past dosing history completely, with the exception of the steady-state dose and its previous infinite homologous doses. SS=3 - besides all the Greek in the explanation - seems to be doing the same, but using different values for the initial estimates (?!?). In any case, I tried and it zeroes-out the compartments as SS=1 does.
SS=2, instead, is supposed to calculate the steady-state level of drug resulting from the implied series of doses, and add that amount ON TOP of whatever other amount would be in the compartments resulting from extra sources, i.e., I would add, other amounts present in the compartments due to events PRIOR to the SS=2 record.
I want to build an integrated model to analyze multiple drugs at the same time, so I would avoid the SS=1 option, as the doses for drug x would cancel out the ones for drug y... So I used SS=2, but it behaves in a way I did not expect.
I have dosing history for three days before the experiment, but not for all patients. The drug is given once daily, normally in the morning, but the exact time generally changes from day to day, so I decided to model the first dose I have record of as steady-state, and then follow the dosing history. Some subjects, however, always declared to have taken the dose at 8 am. I pasted a fragment of the dataset below.
#ID TIME DV AMT SS II MDV
1 0 . 450 2 24 1
1 24 . 450 0 . 1
1 48 . 450 0 . 1
1 72 . 450 0 . 1
1 72.2 0.05 . . . 0
1 73.3 3.83 . . . 0
1 74.4 3.27 . . . 0
1 75 2.66 . . . 0
1 96 . . . . 1
I would expect to observe the very same predictions at 24 hours distance, as 24 hours is the inter-dose interval.
However, after a minimization successful and that's what I get as an output:
ID TIME Y DV PRED RES WRES IPRE IRES IWRE
1 0 */0.11356 /* 0 0.16226 0 0 */0.11356/* -0.11356 -0.090191 1 24 */0.11356/* 0 0.16226 0 0 */0.11356/* -0.11356 -0.090191 1 48 */0.056889/* 0 0.081288 0 0 */0.056889/* -0.056889 -0.045196 1 72 */0.056782/* 0 0.081132 0 0 */0.056782 /* -0.056782 -0.045111 1 72.2 0.59151 0.05 0.81647 -0.76647 -0.4746 0.59151 -0.54151 -0.42489 1 73.3 2.557 3.83 3.5268 0.30316 0.49445 2.557 1.273 0.83272 1 74.4 3.3771 3.27 4.6667 -1.3967 -0.27596 3.3771 -0.10714 -0.062947 1 75 3.5245 2.66 4.8757 -2.2157 -0.6256 3.5245 -0.86455 -0.49795 1 96 0.056782 0 0.081132 0 0 0.056782 -0.056782 -0.045111
The first two records (0 and 24) have a value which is about twice as much as the following (48, 72 and 96), which seem to be going towards a lower steady-state level.
With SS=1 it does work as expected, but when I will add the compartments for the other drugs, SS=1 will interfere with those.
I am sure I am misinterpreting something here, but in my understanding, it should not matter whether I choose SS=1 or SS=2, as long as the dose is the first one in the dataset... SS=1 forgets the past dosing history, while SS=2 remembers it, but what difference does it make if there was no other dose in the past?
Thank you in advance to anyone who can help - or even just had the patience to read all this.. ;)
Paolo
--
------------------------------------------------
Paolo Denti, PhD
Post-Doctoral Fellow
Division of Clinical Pharmacology
Department of Medicine
University of Cape Town
K45 Old Main Building
Groote Schuur Hospital
Observatory, Cape Town
7925 South Africa
phone: +27 21 404 7719
fax: +27 21 448 1989
email: [email protected]
Weird behavior (or poor understanding on my side) of the SS=2 option
2 messages
2 people
Latest: Oct 09, 2009
Paolo is correct in his understanding.
A bug was introduced into PREDPP when the Initial Steady State feature
was introduced, in NONMEM VI 2.0.
SS=2 doses do not work correctly. This same bug is present in NONMEM 7.
More details will be sent when available.
On Mon, 05 Oct 2009 09:37:05 +0200, "Paolo Denti"
<[email protected]> said:
> Dear all,
> I am creating a dataset with the SS=2 option and I noticed an unexpected
> prediction profile that indicated that I am misinterpreting the way SS
> works in NONMEM... I would appreciate any feedback.
>
> My understanding of the SS option in NONMEM is that the dose is assumed
> as previously given at regular intervals (specified by II), and the
> level of drug concentration resulting from this process is calculated.
> There are different options (1, 2 and 3), which I list below to clarify
> the way I understand them to work, so that it might be clear where I am
> mistaken.
>
> According to the NONMEM guide, SS=1 should zero-out all system
> compartments and reset them to the value resulting only from the
> steady-state dose, thus virtually forgetting the past dosing history
> completely, with the exception of the steady-state dose and its previous
> infinite homologous doses. SS=3 - besides all the Greek in the
> explanation - seems to be doing the same, but using different values for
> the initial estimates (?!?). In any case, I tried and it zeroes-out the
> compartments as SS=1 does.
>
> SS=2, instead, is supposed to calculate the steady-state level of drug
> resulting from the implied series of doses, and add that amount ON TOP
> of whatever other amount would be in the compartments resulting from
> extra sources, i.e., I would add, other amounts present in the
> compartments due to events PRIOR to the SS=2 record.
>
> I want to build an integrated model to analyze multiple drugs at the
> same time, so I would avoid the SS=1 option, as the doses for drug x
> would cancel out the ones for drug y... So I used SS=2, but it behaves
> in a way I did not expect.
>
> I have dosing history for three days before the experiment, but not for
> all patients. The drug is given once daily, normally in the morning, but
> the exact time generally changes from day to day, so I decided to model
> the first dose I have record of as steady-state, and then follow the
> dosing history. Some subjects, however, always declared to have taken
> the dose at 8 am. I pasted a fragment of the dataset below.
>
> #ID TIME DV AMT SS II MDV
> 1 0 . 450 2 24 1
> 1 24 . 450 0 . 1
> 1 48 . 450 0 . 1
> 1 72 . 450 0 . 1
> 1 72.2 0.05 . . . 0
> 1 73.3 3.83 . . . 0
> 1 74.4 3.27 . . . 0
> 1 75 2.66 . . . 0
> 1 96 . . . . 1
>
> I would expect to observe the very same predictions at 24 hours
> distance, as 24 hours is the inter-dose interval.
> However, after a minimization successful and that's what I get as an
> output:
> ID TIME Y DV PRED RES WRES IPRE IRES IWRE
> 1 0 */0.11356 /* 0 0.16226 0 0 */0.11356/*
> -0.11356 -0.090191
> 1 24 */0.11356/* 0 0.16226 0 0 */0.11356/*
> -0.11356 -0.090191
> 1 48 */0.056889/* 0 0.081288 0 0 */0.056889/*
> -0.056889 -0.045196
> 1 72 */0.056782/* 0 0.081132 0 0 */0.056782 /*
> -0.056782 -0.045111
> 1 72.2 0.59151 0.05 0.81647 -0.76647 -0.4746
> 0.59151 -0.54151 -0.42489
> 1 73.3 2.557 3.83 3.5268 0.30316 0.49445 2.557
> 1.273 0.83272
> 1 74.4 3.3771 3.27 4.6667 -1.3967 -0.27596
> 3.3771 -0.10714 -0.062947
> 1 75 3.5245 2.66 4.8757 -2.2157 -0.6256 3.5245
> -0.86455 -0.49795
> 1 96 0.056782 0 0.081132 0 0 0.056782
> -0.056782 -0.045111
>
> The first two records (0 and 24) have a value which is about twice as
> much as the following (48, 72 and 96), which seem to be going towards a
> lower steady-state level.
>
> With SS=1 it does work as expected, but when I will add the compartments
> for the other drugs, SS=1 will interfere with those.
>
> I am sure I am misinterpreting something here, but in my understanding,
> it should not matter whether I choose SS=1 or SS=2, as long as the dose
> is the first one in the dataset... SS=1 forgets the past dosing history,
> while SS=2 remembers it, but what difference does it make if there was
> no other dose in the past?
>
> Thank you in advance to anyone who can help - or even just had the
> patience to read all this.. ;)
> Paolo
>
> --
> ------------------------------------------------
> Paolo Denti, PhD
> Post-Doctoral Fellow
> Division of Clinical Pharmacology
> Department of Medicine
> University of Cape Town
>
> K45 Old Main Building
> Groote Schuur Hospital
> Observatory, Cape Town
> 7925 South Africa
> phone: +27 21 404 7719
> fax: +27 21 448 1989
> email: [email protected]
> ------------------------------------------------
>
--
Alison Boeckmann
[email protected]