Hi, everyone:
I am trying to develop a pop PK model for a compound with a large
variability in absorption. I have difficulty in fitting the absorption
phase, especially the Cmax. Some of the subjects are underpredicted while
some subjects are overpredicted.
Since the study is a four-way cross-over study with 5 different occasions,
I am thinking about incorporating interoccasion variability (IOV) on Ka in
my model. I tried to test IOV using the code:
IF OCC==1 BOVKA=ETA(1)
...
IF OCC==5 BOVKA=ETA(5)
KA=THETA(1)*EXP(BOVKA)
$OMEGA BLOCK (1); for OCC=1
0.16
$OMEGA BLOCK(1) SAME; for OCC=2
...
$OMEGA BLOCK(1) SAME; for OCC=5
But it didn't improve the fitting. Then I tried to remove the "SAME" and
five different estimation of ETAs were obtained. The fitting wasn't really
improved. Can anyone comment on that whether it is oaky to have 5 different
ETAs on one parameter in the model according to different occasions?
Also, is there any suggestion to improve the fitting of absorption? I also
tried ALAG model but not improve the fitting either. The Ka is kind of
large for my compound (around 1.5). some of the subjects have the first
sample as Cmax but not in other subjects. some of the subjects showed a
second peak during distribution in some occasions but not in other
occasions. Not sure how to handle all these visibilities in my data and get
the good fit of absorption phase.
Any suggestions would be appreciated.
Thanks!
Best,
--
Xu, Claire
Ph.D Candidate
Division of Clinical Pharmacology, Wishard Hospital
Indiana University School of Medicine
1001 West 10th Street, Myers W7122
Indianapolis, IN 46202
T - 317/7558242
Question about interoccation variability
Dear Xu,
You may want to consider to model a relative bioavailability between your
treatment. If your dose is in compartment 1, then you fix F1 to 1 for one of
your treatment and estimate F1 (relative bioavailability) for your other
treatment.
Best regards,
Jean
Quoted reply history
From: [email protected] [mailto:[email protected]] On
Behalf Of Xu, Claire
Sent: Tuesday, July 10, 2012 4:46 PM
To: [email protected]
Subject: [NMusers] Question about interoccation variability
Hi, everyone:
I am trying to develop a pop PK model for a compound with a large variability
in absorption. I have difficulty in fitting the absorption phase, especially
the Cmax. Some of the subjects are underpredicted while some subjects are
overpredicted.
Since the study is a four-way cross-over study with 5 different occasions, I am
thinking about incorporating interoccasion variability (IOV) on Ka in my model.
I tried to test IOV using the code:
IF OCC==1 BOVKA=ETA(1)
...
IF OCC==5 BOVKA=ETA(5)
KA=THETA(1)*EXP(BOVKA)
$OMEGA BLOCK (1); for OCC=1
0.16
$OMEGA BLOCK(1) SAME; for OCC=2
...
$OMEGA BLOCK(1) SAME; for OCC=5
But it didn't improve the fitting. Then I tried to remove the "SAME" and five
different estimation of ETAs were obtained. The fitting wasn't really improved.
Can anyone comment on that whether it is oaky to have 5 different ETAs on one
parameter in the model according to different occasions? Also, is there any
suggestion to improve the fitting of absorption? I also tried ALAG model but
not improve the fitting either. The Ka is kind of large for my compound (around
1.5). some of the subjects have the first sample as Cmax but not in other
subjects. some of the subjects showed a second peak during distribution in some
occasions but not in other occasions. Not sure how to handle all these
visibilities in my data and get the good fit of absorption phase.
Any suggestions would be appreciated.
Thanks!
Best,
--
Xu, Claire
Ph.D Candidate
Division of Clinical Pharmacology, Wishard Hospital
Indiana University School of Medicine
1001 West 10th Street, Myers W7122
Indianapolis, IN 46202
T - 317/7558242
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I think I would try IOV on F1 first before putting it on KA like Jean suggested
but above all I think there is an essential element missing in your code. IOV
is variability between occasions on top of inter individual variability.
So do something like:
F1=1
F1=THETA(1)*EXP(ETA(6)+BOVKA)
$OMEGA 0.25 ; IIV F1
Furthermore, there may be other elements contributing to the inability to
predict Cmax well, such as more complex absorption features. I think we lack
info to comment on that.
HTH, Klaas
Quoted reply history
On 10 jul. 2012, at 23:56, "Lavigne, Jean" <[email protected]> wrote:
> KA=THETA(1)*EXP(BOVKA)
Hi Klaas and Jean,
Thanks a lot for your immediate response and input. I will definitely test
that whether having IOV on F1 will help.
But I have a more general question about IOV. Can you comment on having one
IOV in the model versus having five different IOVs across five different
occasions? Is it reasonable to have different IOVs in the model?
Thanks a lot for your generous help.
Best,
Claire
Quoted reply history
On Tue, Jul 10, 2012 at 6:42 PM, Klaas Prins <[email protected]>wrote:
> I think I would try IOV on F1 first before putting it on KA like Jean
> suggested but above all I think there is an essential element missing in
> your code. IOV is variability between occasions on top of inter individual
> variability.
>
> So do something like:
> F1=1
> F1=THETA(1)*EXP(ETA(6)+BOVKA)
> $OMEGA 0.25 ; IIV F1
>
> Furthermore, there may be other elements contributing to the inability to
> predict Cmax well, such as more complex absorption features. I think we
> lack info to comment on that.
>
> HTH, Klaas
>
>
> On 10 jul. 2012, at 23:56, "Lavigne, Jean" <[email protected]>
> wrote:
>
> > KA=THETA(1)*EXP(BOVKA)
>
>
--
Xu, Claire
Ph.D Candidate
Division of Clinical Pharmacology, Wishard Hospital
Indiana University School of Medicine
1001 West 10th Street, Myers W7122
Indianapolis, IN 46202
T - 317/7558242
Claire,
It is the traditional assumption that BOV variance does not change with occasion (an assumption implemented with the SAME option). But it would be quite reasonable to look for BOV variance that is different from occasion to occasion eg. BOV in F might be relatively low soon after starting treatment in hospital but increase as patients became more active and had more interesting meals at home.
So its a modelling choice that you can test in the usual way based on OFV.
BTW in the example below if you want to use BOV on F1 the code should be F1=POPF1*EXP(ETA(F1)+BOVF1) where POPF1 would typically be set to 1 (unless you had a better idea of what the actual mean bioavailability of oral doses was) and ETA(F1) is the ETA for BSV of F1.
Nick
Quoted reply history
On 11/07/2012 7:16 a.m., Xu, Claire wrote:
> Hi Klaas and Jean,
>
> Thanks a lot for your immediate response and input. I will definitely test that whether having IOV on F1 will help. But I have a more general question about IOV. Can you comment on having one IOV in the model versus having five different IOVs across five different occasions? Is it reasonable to have different IOVs in the model?
>
> Thanks a lot for your generous help.
> Best,
> Claire
>
> On Tue, Jul 10, 2012 at 6:42 PM, Klaas Prins < [email protected] < mailto: [email protected] >> wrote:
>
> I think I would try IOV on F1 first before putting it on KA like
> Jean suggested but above all I think there is an essential element
> missing in your code. IOV is variability between occasions on top
> of inter individual variability.
>
> So do something like:
> F1=1
> F1=THETA(1)*EXP(ETA(6)+BOVKA)
> $OMEGA 0.25 ; IIV F1
>
> Furthermore, there may be other elements contributing to the
> inability to predict Cmax well, such as more complex absorption
> features. I think we lack info to comment on that.
>
> HTH, Klaas
>
> On 10 jul. 2012, at 23:56, "Lavigne, Jean"
> <[email protected] <mailto:[email protected]>> wrote:
>
> > KA=THETA(1)*EXP(BOVKA)
>
> --
> Xu, Claire
> Ph.D Candidate
> Division of Clinical Pharmacology, Wishard Hospital
> Indiana University School of Medicine
> 1001 West 10th Street, Myers W7122
> Indianapolis, IN 46202
> T - 317/7558242
--
Nick Holford, Professor Clinical Pharmacology
First World Conference on Pharmacometrics, 5-7 September 2012
Seoul, Korea http://www.go-wcop.org
Dept Pharmacology & Clinical Pharmacology, Bldg 505 Room 202D
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: [email protected]
http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford
Hi Nick,
Thank you a lot for clarifying how to incorporate BOV in the model.
I tested BOV on F1 with the same option as well as variable BOVs on F1 from
different occasions. But either of them improved the fitting. Actually
according to the results from non-compartmental analysis, AUC0-inf are very
similar across different occasions, while a trend of difference in Cmax and
Tmax was observed. Do you think that more complex absorption models would
help?
Open to any comments.
Thanks again for your great input.
Best,
Claire
Quoted reply history
On Wed, Jul 11, 2012 at 9:33 AM, Nick Holford <[email protected]>wrote:
> Claire,
>
> It is the traditional assumption that BOV variance does not change with
> occasion (an assumption implemented with the SAME option). But it would be
> quite reasonable to look for BOV variance that is different from occasion
> to occasion eg. BOV in F might be relatively low soon after starting
> treatment in hospital but increase as patients became more active and had
> more interesting meals at home.
> So its a modelling choice that you can test in the usual way based on OFV.
>
> BTW in the example below if you want to use BOV on F1 the code should be
> F1=POPF1*EXP(ETA(F1)+BOVF1)
> where POPF1 would typically be set to 1 (unless you had a better idea of
> what the actual mean bioavailability of oral doses was) and ETA(F1) is the
> ETA for BSV of F1.
>
> Nick
>
>
> On 11/07/2012 7:16 a.m., Xu, Claire wrote:
>
>> Hi Klaas and Jean,
>> Thanks a lot for your immediate response and input. I will definitely
>> test that whether having IOV on F1 will help.
>> But I have a more general question about IOV. Can you comment on having
>> one IOV in the model versus having five different IOVs across five
>> different occasions? Is it reasonable to have different IOVs in the model?
>> Thanks a lot for your generous help.
>> Best,
>> Claire
>> On Tue, Jul 10, 2012 at 6:42 PM, Klaas Prins
>> <[email protected]<mailto:
>> klaas.prins@**qpharmetra.com <[email protected]>>> wrote:
>>
>> I think I would try IOV on F1 first before putting it on KA like
>> Jean suggested but above all I think there is an essential element
>> missing in your code. IOV is variability between occasions on top
>> of inter individual variability.
>>
>> So do something like:
>> F1=1
>> F1=THETA(1)*EXP(ETA(6)+BOVKA)
>> $OMEGA 0.25 ; IIV F1
>>
>> Furthermore, there may be other elements contributing to the
>> inability to predict Cmax well, such as more complex absorption
>> features. I think we lack info to comment on that.
>>
>> HTH, Klaas
>>
>>
>> On 10 jul. 2012, at 23:56, "Lavigne, Jean"
>> <[email protected]
>> <mailto:jean.lavigne@celerion.**com<[email protected]>>>
>> wrote:
>>
>> > KA=THETA(1)*EXP(BOVKA)
>>
>>
>>
>>
>> --
>> Xu, Claire
>> Ph.D Candidate
>> Division of Clinical Pharmacology, Wishard Hospital
>> Indiana University School of Medicine
>> 1001 West 10th Street, Myers W7122
>> Indianapolis, IN 46202
>> T - 317/7558242
>>
>>
> --
> Nick Holford, Professor Clinical Pharmacology
>
> First World Conference on Pharmacometrics, 5-7 September 2012
> Seoul, Korea http://www.go-wcop.org
>
> Dept Pharmacology & Clinical Pharmacology, Bldg 505 Room 202D
> 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: [email protected]
> http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford
>
>
>
>
>
--
Xu, Claire
Ph.D Candidate
Division of Clinical Pharmacology, Wishard Hospital
Indiana University School of Medicine
1001 West 10th Street, Myers W7122
Indianapolis, IN 46202
T - 317/7558242
Claire,
See below:
Quoted reply history
On 11/07/2012 9:45 p.m., Xu, Claire wrote:
> Hi Nick,
> Thank you a lot for clarifying how to incorporate BOV in the model.
>
> I tested BOV on F1 with the same option as well as variable BOVs on F1 from different occasions. But either of them improved the fitting.
I am not sure what you mean here. Do you mean that NEITHER of them improved the fit? If that is the case then it would be compatible with your other observation that AUC is very similar across occasions which suggests that there is negligible BOV in CL or F. I find that a bit surprising but it is not impossible.
> Actually according to the results from non-compartmental analysis, AUC0-inf are very similar across different occasions, while a trend of difference in Cmax and Tmax was observed. Do you think that more complex absorption models would help?
Because you are do see BOV in Cmax and Tmax then it seems you should try to focus on looking for BSV+BOV on your absorption model parameters (Ka, Tlag). Of course you can also work on the absorption model structure as well.
> Open to any comments.
> Thanks again for your great input.
> Best,
> Claire
--
Nick Holford, Professor Clinical Pharmacology
First World Conference on Pharmacometrics, 5-7 September 2012
Seoul, Korea http://www.go-wcop.org
Dept Pharmacology & Clinical Pharmacology, Bldg 505 Room 202D
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: [email protected]
http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford
Dear Claire,
If you have data only from oral doses and covariances between disposition
parameters (CL; V), then you will not get any further improvement by
introducing variability in F1.
Best regards,
Mats
Mats Karlsson, PhD
Professor of Pharmacometrics
FIRST WORLD CONFERENCE ON PHARMACOMETRICS, 5-7 September 2012, Seoul (
http://www.go-wcop.org/ www.go-wcop.org)
Dept of Pharmaceutical Biosciences
Faculty of Pharmacy
Uppsala University
Box 591
75124 Uppsala
Phone: +46 18 4714105
Fax + 46 18 4714003
From: [email protected] [mailto:[email protected]] On
Behalf Of Xu, Claire
Sent: 12 July 2012 15:11
Cc: nmusers
Subject: Re: [NMusers] Question about interoccation variability
Hi Nick,
Thanks for your helpful comment. I will test BOV + BSV on my absorption
model parameters first.
Sorry for my typo. I meant neither of the models improved the fit.
Thanks again for your help.
Best,
Claire
Quoted reply history
On Thu, Jul 12, 2012 at 8:07 AM, Nick Holford <[email protected]>
wrote:
Claire,
See below:
On 11/07/2012 9:45 p.m., Xu, Claire wrote:
Hi Nick,
Thank you a lot for clarifying how to incorporate BOV in the model.
I tested BOV on F1 with the same option as well as variable BOVs on F1 from
different occasions. But either of them improved the fitting.
I am not sure what you mean here. Do you mean that NEITHER of them improved
the fit? If that is the case then it would be compatible with your other
observation that AUC is very similar across occasions which suggests that
there is negligible BOV in CL or F. I find that a bit surprising but it is
not impossible.
Actually according to the results from non-compartmental analysis, AUC0-inf
are very similar across different occasions, while a trend of difference in
Cmax and Tmax was observed. Do you think that more complex absorption models
would help?
Because you are do see BOV in Cmax and Tmax then it seems you should try to
focus on looking for BSV+BOV on your absorption model parameters (Ka, Tlag).
Of course you can also work on the absorption model structure as well.
Open to any comments.
Thanks again for your great input.
Best,
Claire
--
Nick Holford, Professor Clinical Pharmacology
First World Conference on Pharmacometrics, 5-7 September 2012
Seoul, Korea http://www.go-wcop.org http://www.go-wcop.org/
Dept Pharmacology & Clinical Pharmacology, Bldg 505 Room 202D
University of Auckland,85 Park Rd,Private Bag 92019,Auckland,New Zealand
tel:+64(9)923-6730 <tel:%2B64%289%29923-6730> fax:+64(9)373-7090
<tel:%2B64%289%29373-7090> mobile:+64(21)46 23 53
<tel:%2B64%2821%2946%2023%2053>
email: [email protected]
http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford
--
Xu, Claire
Ph.D Candidate
Division of Clinical Pharmacology, Wishard Hospital
Indiana University School of Medicine
1001 West 10th Street, Myers W7122
Indianapolis, IN 46202
T - 317/7558242
Hi Mat,
Yes, I only have oral PK data and as you expected, the introduction of
variability on F didn't improve the fit.
As Nick suggested previously, I also tried different combinations of BSV and
BOV on ka and Tlag using one compartment and two compartment model. The
incorporation of BOV on ka with two compartment Tlag model gave best fitting
compared to other models. But the parameter estimations are problematic, e.g.
RSEs are very big for V and Q. I think the model is overparamerization.
Any comments and suggestions would be appreciated.
Thanks.
Best,
Claire
Sent from my iPhone
Quoted reply history
On Jul 12, 2012, at 9:43 AM, "Mats Karlsson" <[email protected]>
wrote:
> Dear Claire,
>
> If you have data only from oral doses and covariances between disposition
> parameters (CL; V), then you will not get any further improvement by
> introducing variability in F1.
>
> Best regards,
> Mats
>
> Mats Karlsson, PhD
> Professor of Pharmacometrics
>
> FIRST WORLD CONFERENCE ON PHARMACOMETRICS, 5-7 September 2012, Seoul
> (www.go-wcop.org)
>
> Dept of Pharmaceutical Biosciences
> Faculty of Pharmacy
> Uppsala University
> Box 591
> 75124 Uppsala
>
> Phone: +46 18 4714105
> Fax + 46 18 4714003
>
> From: [email protected] [mailto:[email protected]] On
> Behalf Of Xu, Claire
> Sent: 12 July 2012 15:11
> Cc: nmusers
> Subject: Re: [NMusers] Question about interoccation variability
>
> Hi Nick,
> Thanks for your helpful comment. I will test BOV + BSV on my absorption model
> parameters first.
> Sorry for my typo. I meant neither of the models improved the fit.
> Thanks again for your help.
> Best,
> Claire
>
> On Thu, Jul 12, 2012 at 8:07 AM, Nick Holford <[email protected]>
> wrote:
> Claire,
>
> See below:
>
>
> On 11/07/2012 9:45 p.m., Xu, Claire wrote:
> Hi Nick,
> Thank you a lot for clarifying how to incorporate BOV in the model.
> I tested BOV on F1 with the same option as well as variable BOVs on F1 from
> different occasions. But either of them improved the fitting.
>
> I am not sure what you mean here. Do you mean that NEITHER of them improved
> the fit? If that is the case then it would be compatible with your other
> observation that AUC is very similar across occasions which suggests that
> there is negligible BOV in CL or F. I find that a bit surprising but it is
> not impossible.
>
>
>
> Actually according to the results from non-compartmental analysis, AUC0-inf
> are very similar across different occasions, while a trend of difference in
> Cmax and Tmax was observed. Do you think that more complex absorption models
> would help?
>
> Because you are do see BOV in Cmax and Tmax then it seems you should try to
> focus on looking for BSV+BOV on your absorption model parameters (Ka, Tlag).
> Of course you can also work on the absorption model structure as well.
>
>
>
> Open to any comments.
> Thanks again for your great input.
> Best,
> Claire
>
>
>
> --
> Nick Holford, Professor Clinical Pharmacology
>
> First World Conference on Pharmacometrics, 5-7 September 2012
> Seoul, Korea http://www.go-wcop.org
>
> Dept Pharmacology & Clinical Pharmacology, Bldg 505 Room 202D
> 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: [email protected]
> http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford
>
>
>
>
>
>
>
> --
> Xu, Claire
> Ph.D Candidate
> Division of Clinical Pharmacology, Wishard Hospital
> Indiana University School of Medicine
> 1001 West 10th Street, Myers W7122
> Indianapolis, IN 46202
> T - 317/7558242