RE: [NMusers] RE: Large errors in the estimation of volume of distribution (Vd) for sparse data

From: HUI, Ka Ho <matthew.hui_at_link.cuhk.edu.hk>
Date: Thu, 19 Nov 2015 13:56:55 +0000

Thank you Zheng. Yes most subjects have only 1 point between doses. I was j=
ust wondering if there are techniques that may improve the results.

And thank you Kajsa. Yes I updated my PsN and tried again. It still did not=
 work at first but later I spotted some coding mistakes in my control file.=
 Under $INPUT block I used CP=DV instead DV, which caused the error.

Thanks and regards,
Matthew

From: Kajsa Harling [mailto:kajsa.harling_at_farmbio.uu.se]
Sent: Monday, November 16, 2015 9:41 PM
To: HUI, Ka Ho <matthew.hui_at_link.cuhk.edu.hk>; nmusers_at_globomaxnm.com
Cc: Kaila, Nitin <Nitin.Kaila_at_pfizer.com>; Abu Helwa, Ahmad Yousef Mohammad=
 - abuay010 <ahmad.abuhelwa_at_mymail.unisa.edu.au>; felix boakye-agyeman <boa=
kyefe_at_gmail.com>
Subject: Re: [NMusers] RE: Large errors in the estimation of volume of dist=
ribution (Vd) for sparse data

Regarding the error message from PsN vpc: I can see from the message that y=
ou are using a *very* old version of PsN. I suggest that you install the la=
test version and try again.

Best regards,
Kajsa Harling
From: Zheng Liu [mailto:Zheng.Liu_at_rch.org.au]
Sent: Monday, November 16, 2015 1:08 PM
To: HUI, Ka Ho <matthew.hui_at_link.cuhk.edu.hk>; Kaila, Nitin <Nitin.Kaila_at_pf=
izer.com>; Abu Helwa, Ahmad Yousef Mohammad - abuay010 <ahmad.abuhelwa_at_myma=
il.unisa.edu.au>; felix boakye-agyeman <boakyefe_at_gmail.com>; nmusers_at_globom=
axnm.com
Subject: RE: Large errors in the estimation of volume of distribution (Vd) =
for sparse data


Hi Matthew,



Very large standard error and bias of Vd suggest that Vd is not well identi=
fied. Or in other word, your data didn't contain sufficient information to =
fit Vd. Loosely speaking it is a problem of over-parameterization, because =
you have only one measurement point, but you try to fit 2 parameters (Vd an=
d clearance).



Zheng

On 11/10/2015 05:12 AM, HUI, Ka Ho wrote:
Thanks for your responses!

Nitin, I encountered an error when generating VPC by PsN. It says "No DV va=
lues found after filtering original data. At lib/tool/npc.subs.pm line 2215=
." What does it mean?

Felix, Past published data suggested similar parameter estimates and models=
 compared to my final model. This is PO and I fixed Ka at a pre-estimated v=
alue (So no estimation of fixed or random effect).

Ahmad, Yes. The CV is even larger.

Matthew



From: Abu Helwa, Ahmad Yousef Mohammad - abuay010 [mailto:ahmad.abuhelwa_at_my=
mail.unisa.edu.au]
Sent: Tuesday, November 10, 2015 5:34 AM
To: HUI, Ka Ho <matthew.hui_at_link.cuhk.edu.hk><mailto:matthew.hui_at_link.cuhk.=
edu.hk>; nmusers_at_globomaxnm.com<mailto:nmusers_at_globomaxnm.com>
Subject: RE: Large errors in the estimation of volume of distribution (Vd) =
for sparse data

Hi Mathew,

Have you tried using an exponential model for vd ? like this: Vd = TEHTA=
(1)*EXP(ETA(1))

Ahmad.


From: felix boakye-agyeman [mailto:boakyefe_at_gmail.com]
Sent: Tuesday, November 10, 2015 12:41 AM
To: HUI, Ka Ho <matthew.hui_at_link.cuhk.edu.hk><mailto:matthew.hui_at_link.cuhk.=
edu.hk>
Subject: Re: [NMusers] Large errors in the estimation of volume of distribu=
tion (Vd) for sparse data

Hello,
   Do you have historical data to compare you data to? (Do you know if you =
are hitting a local minimum)
Is this iv or po, if its po how is your Ka?
You may also be over-parameterized due to your data

From: Kaila, Nitin [mailto:Nitin.Kaila_at_pfizer.com]
Sent: Tuesday, November 10, 2015 12:14 AM
To: HUI, Ka Ho <matthew.hui_at_link.cuhk.edu.hk><mailto:matthew.hui_at_link.cuhk.=
edu.hk>
Subject: RE: Large errors in the estimation of volume of distribution (Vd) =
for sparse data

Matthew.

Construct visual predictive check (VPC) plots, using all the estimates of t=
he bootstrap runs, as that will be a more true estimate of overall variabil=
ity in the Cp predictions.

Use the -rawres option in PsN to perform the VPC, and then compare your ori=
ginal final model VPC plot with the VPC plot with all estimates of the boot=
strap.

Nitin

From: owner-nmusers_at_globomaxnm.com<mailto:owner-nmusers_at_globomaxnm.com> [ma=
ilto:owner-nmusers_at_globomaxnm.com] On Behalf Of HUI, Ka Ho
Sent: Monday, November 9, 2015 9:43 AM
To: nmusers_at_globomaxnm.com<mailto:nmusers_at_globomaxnm.com>
Subject: [NMusers] Large errors in the estimation of volume of distribution=
 (Vd) for sparse data


Dear all,

I have some population PK data which are in general very sparse (95% have o=
nly 1 blood sample between 2 successive doses). I developed a population PK=
 model with the one-compartment model with 1st order absorption. The progre=
ss is generally okay except that whenever a random effect, i.e. *(1+ETA(1))=
, is used to describe distribution of Vd, OMEGA would be estimated to be ve=
ry large (around 45% in terms of CV, with 80% Shrinkage), despite statistic=
al significance (dOF approx. -5.5). So I dropped the random effect and expr=
essed Vd in terms of a single fixed effect. When the final model has come o=
ut, I performed bootstrap and found that most estimates are accurate except=
 Vd, which has a very large standard error and bias (mean 232, bias 49, SE =
156), while the estimates for CL and other parameters look normal. I then c=
onstructed the predictive plots for the developed model using both the orig=
inal estimates (i.e. estimates using my original dataset) (#1) and estimate=
s from one of the bootstrap runs which has an extreme estimate of Vd (9xx) =
(#2), and found out that the two plots of plasma profiles are quite differe=
nt in terms of the shape (#1 is "taller", #2 is much flatter) but have simi=
lar average Cp.

These seem to be suggesting that given my sparse data, it is impossible to =
require accurate estimations of both CL and Vd. Apart from fixing Vd to a f=
ixed value, is there any other possible solutions? Or is there anything tha=
t I might have overlooked?

Thanks and regards,
Matthew





Received on Thu Nov 19 2015 - 08:56:55 EST

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