- On 20 Sep 2015 at 15:32:11, Bharadwaj, Manushree (manushb.-at-.OSTATEMAIL.OKSTATE.EDU) sent the message

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Hello,

I have two questions:

A) I am going through the metrum institute videos about population PK PD analysis. In Lab 2

(https://www.youtube.com/watch?v=ZA_MpMTFsUs&index=3&list=PLvLDbH2lpyXOETHzGfPGOtXayHNmXT9Cx&

spfreload=1), the instructor uses a tool called solver to perform iterations to determine the least

objective function value. The instructor is using a Mac (open office). How can I get that tool or

add-in in excel?

B) In the weighted least square example discussed in the video, the weighting used is (1/observed

concentration). What are the other common weighting strategies? Is there any specific reason to

prefer one weighting strategy over the other?

Thank you,

Manu

--

With regards-

Manushree Bharadwaj, BVSc, PhD Candidate

Graduate Teaching Assistant

Department of Physiological Sciences

Center for Veterinary Health Sciences

Oklahoma State University

Stillwater, OK-74074 - On 21 Sep 2015 at 08:53:16, sent the message

From: William Wolowich

Manu:

Solver is an add-in that you need to activate in excel. It is part of the analysis pack, you might

have to download it from the microsoft site if it doesn't show up in your add ins list.

Weighting for regression is mostly empiric. Other common schemes include 1/obs^2, 1/predicted, and

1/ predicted^2. The last two are iterative.

Woolwich

--

From: Nick Holford

Manu,

If you look at this web page:

http://holford.fmhs.auckland.ac.nz/teaching/medsci719/timetable.php

and find the section on "Error Models and Objective Functions" there is a link to:

http://holford.fmhs.auckland.ac.nz/teaching/medsci719/workshops/errormodels/

On that web page you will find a description of how to install the Excel solver (from Excel) (look

at the Excel section of the web page).

If you follow the instructions for using the solver (on this web page) you can find examples which

show how different weighting schemes affect parameter estimation. You may also wish to look at

http://holford.fmhs.auckland.ac.nz/docs/error-models-and-objective-functions.pdf

which gives some additional explanation about objective functions and weighting.

Nick

--

From: Roger Jelliffe

Dear Manu:

A – What is probably happening is that the differential equations must be solved numerically. This

is done by differential equation solvers - integration routines to solve the differential

equations. Why are you using something in Excel? I am not clear.

As to population analysis, you might look at

Bustad A, Terziivanov D, Leary R, Port R, Schumitzky A, and Jelliffe R: Parametric and Nonparametric

Population Methods: Their Comparative Performance in Analysing a Clinical Data Set and Two Monte

Carlo Simulation Studies. Clin. Pharmacokinet., 45: 365-383, 2006.

Neely M, van Guilder M, Yamada W, Schumitzky A, and Jelliffe R: Accurate Detection of Outliers and

Subpopulations with Pmetrics, a Nonparametric and Parametric Pharmacometric Modeling and Simulation

Package for R. Therap. Drug Monit. 34: 467-476, 2012.

Pmetrics is a freely available software package, embedded in R. The papers above compare the

strengths and weaknesses of parametric versus nonparametric approaches to population modeling.

Nonparametric approaches get more likely results because they do not constrain the model parameter

distributions into some assumed shape like normal or lognormal. The shape is determined only by the

data itself.

You can get Pmetrics at www.lapk.org. Rather than minimize a least squares objective function as

your instructor appears to want to do, Pmetrics maximizes the likelihood of the results given the

data. Most likely results, not just the best fit. If you assume a normal distribution for the

population parameters, they will be the same. If you release the distributions to be free of those

constraining assumptions of normality, as with Pmetrics, then the likelihood is the better objective

function.

Further, parametric population models will not permit maximally precise drug dosing for optimal

patient care, as they use only a single summary value for each model parameter, rather than the

entire distribution itself, as the nonparametric approach does. This is called Multiple Model (MM)

dosage design. You might look at

Jelliffe R, Bayard D, Milman M, Van Guilder M, and Schumitzky A: Achieving Target Goals most

Precisely using Nonparametric Compartmental Models and "Multiple Model" Design of Dosage Regimens.

Therap. Drug Monit. 22: 346-353, 2000.

B – The weighting is not clear. Why is he using 1/the concentration? What you want to do is to get

real. The proper way to weight the data is by the reciprocal of the variance of the measured

concentration. A lot of people weight by 1/observed conc or 1/conc squared, but the really correct

thing is to use 1/variance of the assay measurement itself – whatever it is. You might look at

almost any statistics book, and find that the proper measure of precision of a measurement whose

error has a Gaussian distribution is by the reciprocal of the variance of the assay measurement at

that value. You also might look at

Jelliffe R, Schumitzky A, Bayard D, and Neely M: Describing Assay Precision - Reciprocal of

Variance is much better than CV%. Therapeutic Drug Monitoring. 06/2015; 37(3):389-94.

DOI:10.1097/FTD.0000000000000168

Also, for more general references, you might look at

Jelliffe R: Estimation of Creatinine Clearance in Patients with Unstable Renal Function, without a

Urine Specimen. Am. J. Nephrology, 22: 320-324, 2002.

Jelliffe R: Goal-Oriented, Model-Based Drug Regimens: Setting Individualized Goals for each Patient.

Therap. Drug Monit. 22: 325-329, 2000.

Jelliffe R, Schumitzky A, Bayard D, Leary R, Botnen A, Van Guilder M, Bustad A, and Neely M: Human

Genetic variation, Population Pharmacokinetic – Dynamic Models, Bayesian feedback control, and

Maximally precise Individualized drug dosage regimens. Current Pharmacogenomics and Personalized

Medicine, 7: 249-262, 2009.

Many approaches to modeling are not oriented to any clinical application, as they mainly

serve the interests of the pharmaceutical industry. You will go to meeting after meeting, and you

will see everyone talking about this or that model of some drug, but very few are really oriented

toward being really maximally useful to anyone but the industry. It is mainly for this reason that I

stopped going to the PAGE meetings a number of years ago. Maybe I will go again sometime, but only

time will tell.

In the meantime, if you are really interested in population PK/PD modeling, I would strongly

urge you to look at Pmetrics, which is much better suited to clinical applications and to being

socially useful, in addition to being, in my view, better science – more likely results, maximally

precise dosage regimens to hit target goals best.

Hope this helps,

Very best regards,

Roger Jelliffe

--

From: Edward O'Connor

It is an add on no charge. Open options in excel and check for add ons. Select solver you might

also want analysis tool pal - On 21 Sep 2015 at 14:47:16, Dr. Prasad Tata (drprasadtata.at.yahoo.com) sent the message

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Dear Bharadwaj:

Solver is part of data analysis pack of Excel, personally I found it very useful when trying to

solve complex equations. You have to open Option---> add in ---> click on data solver and click Go

close the excel program and reopen you will see solver is added you are good to go..... Happy baby

steps into Modeling and Simulation.

Best,

Prasad NV Tata, Ph.D., FCP - On 21 Sep 2015 at 18:03:21, David S. Farrier (DFarrier.-at-.summitpk.com) sent the message

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Manushree,

For you interest, if you wish, you can see the Solver Add-in in action assisting in my identical

Excel Win and Mac versions of PK Solutions - pharmacokinetics data analysis the easy way for

education and research.

Regards,

Dr. David S. Farrier

Founder / Owner

www.SummitPK.com - On 24 Sep 2015 at 09:01:59, Peter W Mullen (pmullen.aaa.kemic.com) sent the message

Hi Manu,

The following three papers may interest you as they utilize Solver in Excel:

1) Meineke, I. & Brockmöller, J. "Simulation of complex pharmacokinetic models in Microsoft Excel."

Computer Methods and Programs in Biomedicine, 88: 239-245 (2007)

The program described in this paper, "Pk-engine", allows for the simulation of various

pharmacokinetic models, but no modeling.

2) Zhang, Y. et al. "PKSolver: An add-in program for pharmacokinetic and pharmacodynamic data

analysis in Microsoft Excel." Computer Methods and Programs in Biomedicine, 99: 306-314 (2010);

3) Wu, B. & Hu, M. "A Useful Microsoft Excel Add-in Program for Pharmacokinetic Analysis."

Pharmaceutica Analytica Acta, doi:10.4172/2153-2435.S11-002 (2011) Available online at:

http://www.omicsonline.org/a-useful-microsoft-excel-add-in-program-for-pharmacokinetic-analysis-2153

-2435.S11-002.pdf

The program ("XlSimEst") made available by Wu and Hu, unlike "PKSolver", both accepts user-defined

models and provides standard error estimates for the fitted PK parameters.

Peter

Peter W. Mullen, PhD, FCSFS

KEMIC BIORESEARCH (www.kemic.com)

P.O. Box 878

22 Nichols Ave.

Kentville

Nova Scotia, B4N 4H8

Canada

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