Question of fitting population PK model using summary statistics of data instead of raw data

1 messages 1 people Latest: Sep 11, 2015

Re: Question of fitting population PK model using summary statistics of data instead of raw data

From: Michael Fossler Date: September 11, 2015 technical
I would argue that it is impossible. With mean data and SD's at each time-point, it is impossible to separate between and with-subject variability. However, a model with "strong assumptions", as Leonid has aptly put it, may still be very useful. It should not be too difficult to come up with reasonable BSV estimates, and the residual error estimates could probably be taken from the assay information, once you have fit the mean curve. You should not expect too much from such a model, but it may be helpful in simulating some future studies. Sent from my iPhone
Quoted reply history
> On Sep 10, 2015, at 6:00 PM, Leonid Gibiansky <lgibiansky_at_quantpharm.com> wrote: > > 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 e stimation 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:Dinko.Rekic_at_fda.hhs.gov] >> 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 Reki, 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: owner-nmusers_at_globomaxnm.com >> [mailto:owner-nmusers_at_globomaxnm.com] >> On Behalf Of Penny Zhu >> Sent: Thursday, September 10, 2015 9:49 AM >> To: nmusers_at_globomaxnm.com >> 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 >> ________________________________ Notice: This e-mail message, together with any attachments, contains information of Trevena, Inc., 1018 West 8th Avenue, King of Prussia, PA 19406, USA. This information may be confidential, proprietary, copyrighted and/or legally privileged. It is intended solely for use by the individual or entity named on this message. If you are not the intended recipient, and have received this message in error, please notify us immediately and delete it and any attachments from your system.