-----Original Message-----
From: Leonid Gibiansky [mailto:[email protected]]
Sent: Thursday, September 10, 2015 5:10 PM
To: Zhu, Penny; [email protected]
Subject: Re: FW: [NMusers] Question of fitting population PK
model using summary statistics of data instead of raw data
It is likely impossible without strong assumptions. I would
first fit the population model (fixed effects only) and then
start to simulate with different assumption trying to match
observed SD or CV for peaks and troughs. You may need to
assume the structure and the magnitude of the error model
and the structure of the IIV model (ETAs on CL, or V, or
both equal, etc.). You may get some rough idea about the
magnitude of the IIV but you may need strong assumptions
about the residual and IIV model.
Leonid
--------------------------------------
Leonid Gibiansky, Ph.D.
President, QuantPharm LLC
web: www.quantpharm.com
e-mail: LGibiansky at quantpharm.com
tel: (301) 767 5566
On 9/10/2015 2:06 PM, Penny Zhu wrote:
Dear Dinko
Thank you for the suggestion. It seems this NAD
approach only uses the mean data and does not estimate
inter-subject variability using the standard deviation
data.
My intention is to establish a population PK/PD model
with appropriate estimation of intersubject variability
based on the mean and standard deviation data at each
timepoint.
A major assumption is that we have good knowledge of
the base
structure of the model (e.g. biexponential), and won't
run the risk
mistaking 2 mono exponential models for a biexponential
model
Your help and discussions will be very much
appreciated.
Penny
-----Original Message-----
From: Rekic, Dinko [mailto:[email protected]]
Sent: Thursday, September 10, 2015
10:41 AM
To: Zhu, Penny
Subject: RE: [NMusers] Question of
fitting population PK
model using summary statistics of data
instead of raw data
See the link and text below.
http://accp1.org/pharmacometrics/theory_popmeth.htm#npd
Naive averaged data approach (NAD)
A model without BSV and
BOV is fitted to the
mean data from all individuals.
Features
-Specialized software not
necessary.
Disadvantages
-Does not
distinguish between
BSV and WSV.
-Inappropriate means lead to
biased parameter estimates.
-May
produce model distortion
i.e., 2 mono exponential equations
averaged together can
yield a biexponential.
-Covariate
modeling cannot be
performed.
Kind regards
Dinko
_________________________________
Dinko Rekić, Ph.D., MSc(Pharm)
Pharmacometrics reviewer
Division of Pharmacometrics
Office of Clinical Pharmacology
Office of Translational Science
Center for Drug Evaluation and
Research
U.S. Food and Drug Administration
10903 New Hampshire Ave
Silver Spring, MD 20993
WO Bldg 51, Rm 3122
Office phone: (8)240 402-3785
"The contents of this message are mine
personally and do not
necessarily reflect any position of
the Government or the
Food and Drug Administration."
-----Original Message-----
From: [email protected]
[mailto:[email protected]]
On Behalf Of Penny Zhu
Sent: Thursday, September 10, 2015
9:49 AM
To: [email protected]
Subject: [NMusers] Question of fitting
population PK model
using summary statistics of data
instead of raw data
Dear all
Assuming the population PK or PD data
are log-normally (or
normally) distributed, if you have the
mean and standard
deviation of a readout at each
timepoint but do not have the
actual raw data (assuming all pateints
are with the same
dosing regimen, etc), is it
possible to establish a
well fitted population PK or PD
model? How would one
get about doing it?
Your help is very much appreciated
Penny
