luvblooms4u
●

2010-11-09 07:07

Posting: # 6117
Views: 13,862

## PK PD modelling [Tips / Tricks]

Dear All

Regards

When a drug is administered, after absorption it reaches the systemic circulation and from there it moves to site of action or get distributed to some of the tissues (kidney, liver, Cancer cells if it is a targeted for that) and in mean time it get eliminated from systemic circulation by metabolism through liver/kidney etc.

But, even the tissue where it has been distributed keeps on proliferating or growing thus increasing the number of cells available for metabolism or in other term with increase in the number of cell, the metabolic capability increases thus that may lead to increase metabolism of the drug in that specific region or tissue.

My question is that
1. Is there will be any effect on the PD out come because of the increased metabolism/ increased metabolic activity of the tissue where the drug is distributed or it is simply controlled by the systemic clearance?
2. Is there any PK PD model is available for the same?
3. If no PK PD model available, what approaches one should try for to generate one.
I hope someone at the forum will help me out with this as I am stuck and not finding any way out.

Regards

Luvblooms
yjlee168
★★

Kaohsiung, Taiwan,
2010-11-09 20:16

@ luvblooms4u
Posting: # 6126
Views: 12,222

## time-dependent clearance

Dear Luvblooms,

I guess you're talking about time-dependent clearance here.

» But, even the tissue where it has been distributed keeps on proliferating or growing thus increasing the number of cells available for metabolism or in other term with increase in the number of cell, the metabolic capability increases thus that may lead to increase metabolism of the drug in that specific region or tissue.
»
» My question is that
» 1. Is there will be any effect on the PD out come because of the increased metabolism/ increased metabolic activity of the tissue where the drug is distributed or it is simply controlled by the systemic clearance?

Yes and no. It depends on the changes of clearance (Cl). However, you may need to know when Cl is going to change (its starting time and stopping time) first. Of course, you can have as many as Cls you want, only if you need to know each Cl's starting time and stopping time to switch to different Cl. That's the difficult part. However, you figure it out from your data by plotting all data with 'Conc. vs. Time' first; and make your guess. It may take you some time to get good guess (trial-and-error).

» 2. Is there any PK PD model is available for the same?

Not totally the same but should have a lot of similar PK/PD models. You can look for Pubmed with keyword "time-dependent clearance" or google it.

» 3. If no PK PD model available, what approaches one should try for to generate one.
»
» I hope someone at the forum will help me out with this as I am stuck and not finding any way out.

I think you may need to create this model yourself to fit your data (needs). I would suggest that you can try ADAPT v5 (a fortran compiler required, freeware), Boomer (no compiler required, freeware), or Winnonlin (commercial), SAAM-II (commercial). Hope this can help.

All the best,
---Yung-jin Lee
bear v2.8.4:- created by Hsin-ya Lee & Yung-jin Lee
Kaohsiung, Taiwan http://pkpd.kmu.edu.tw/bear
Helmut
★★★

Vienna, Austria,
2010-11-10 03:03

@ yjlee168
Posting: # 6131
Views: 12,132

## PK/PD + PopPK software

Dear Yung-jin!

» SAAM-II (commercial).

Is SAAM-II really commercial? I think that you only have to register for the download. An alternative is WinSAAM (registration required). Another commercial software is Kinetica.

You shouldn’t be that decent to keep quiet about your Java-GUI for Boomer; JGuiB – makes life easier, especially for an occasional user like myself!

It is important to note that all PK(PD) software have a quite steep learning curve.

Cheers,
Helmut Schütz

The quality of responses received is directly proportional to the quality of the question asked. ☼
Science Quotes
yjlee168
★★

Kaohsiung, Taiwan,
2010-11-10 11:41

@ Helmut
Posting: # 6136
Views: 12,103

## PK/PD + PopPK software

Dear Helmut,

» Is SAAM-II really commercial? I think that you only have to register for the download.

As far as I can remember, yes, SAAM-II is commercial, but they have teaching license for free. See its order form (Attachment B).

» An alternative is WinSAAM (registration required).
» Another commercial software is Kinetica.

Agree. Both are very popular in the field of PK/PD modeling.

» You shouldn't be that decent to keep quiet about your Java-GUI for Boomer; JGuiB - makes life easier, especially for an occasional user like myself!

Thank you. It is just a GUI for Boomer.

» It is important to note that all PK(PD) software have a quite steep learning curve.
»
» If you have mastered some of the above, you are ready to start with Monolix (freeware).

Yes, I have used Monolix for a while. They are ready to release stable v3.2 soon. I have some problems to work with v3.2 (beta 2). I have contacted Monolix Developing Team. I don't know if they got similar feedback or not. Very nice program for Pop PK/PD; furthermore, it is freeware. I still stay with v3.1 R2.

All the best,
---Yung-jin Lee
bear v2.8.4:- created by Hsin-ya Lee & Yung-jin Lee
Kaohsiung, Taiwan http://pkpd.kmu.edu.tw/bear
luvblooms4u
●

2010-11-12 05:29

@ yjlee168
Posting: # 6139
Views: 11,788

## time-dependent clearance

Dear yjlee168:,

» I guess you're talking about time-dependent clearance here.

Yes and No,
I am a bit confused though. Actually I was trying to see the cell proliferation dependent clearance.

» Yes and no. It depends on the changes of clearance (Cl). However, you may need to know when Cl is going to change (its starting time and stopping time) first. Of course, you can have as many as Cls you want, only if you need to know each Cl's starting time and stopping time to switch to different Cl. That's the difficult part. However, you figure it out from your data by plotting all data with 'Conc. vs. Time' first; and make your guess. It may take you some time to get good guess (trial-and-error).

Actually I am mainly looking for the Tissue metabolism related effects which may not be observed in 'Conc. vs. Time' graph.I think I am thinking in a right way!!

» » 2. Is there any PK PD model is available for the same?
» Not totally the same but should have a lot of similar PK/PD models. You can look for Pubmed with keyword "time-dependent clearance" or google it.

Thanks a lot. I will look for the same.

» I think you may need to create this model yourself to fit your data (needs).

Thanks a lot for your suggestion.

Let me search and try them then I will be back!

Luvbloms
SDavis
★★

UK,
2010-11-16 23:19

@ luvblooms4u
Posting: # 6152
Views: 11,811

## time-dependent clearance

Hi LuvBlooms,

You've had some great advice from Helmut et al.; some of these recorded webinars may be useful back ground;

http://pharsight.com/events/eventsonline_archive.php

Also if may make a small plug for my own company's training courses if you're looking for something delivered in an applied manner with WinNonlin

Forthcoming meetings and training http://www.pharsight.com/training;

Introduction to Phoenix v6.1: 8-10 Dec 2010, Paris, France.
Introduction to Phoenix v6.x: 22-24 Feb 2011 Berlin, Germany.
Introduction to Phoenix v6.x: 15-17 Mar 2011 Paris, France
Introduction to Phoenix v6.x: 12-14 Apr 2011 London, UK
Introduction to Phoenix v6.x: 10-12 May 2011 Amsterdam, NL.
Population analysis with Phoenix v6.1 NLME : 17-19 May 2011, Paris, France.
Population analysis with Phoenix v6.1 NLME : 6-7 Jun 2011, Athens, Greece (Before PAGE)
2-3 April 2011, Two-day Pre ACOP-meeting Workshop: Population Modelling with Phoenix NLME and Connect.

Simon
Helmut
★★★

Vienna, Austria,
2010-11-10 04:36

@ luvblooms4u
Posting: # 6132
Views: 12,126

## PK PD modelling

Dear Luvblooms!

First I agree with Yung-jin’s post.

I’m afraid you have to give us more information. Normally the half-life of drugs is too short to be influenced by an increasing number of cells (are you thinking about a tumor?). Exceptions are drugs with very long half-lives (let’s say, more than a week), or the patient is in true steady-state (again, I’m talking about weeks).
What we see in time-dependent clearances Yung-jin mentioned are mainly following types:
• AUCτ (steady state) > AUC (single dose): Capacity limited and/or Auto-inhibition
• AUCτ (steady state) < AUC (single dose): Auto-induction
If other drugs are administered simultaneously, PK interactions (mainly competitive inhibition) may occur as well.

• Get some books. Read them. Take a vacation. Read them again.
• Consider getting some training.
• Yung-jin called it trial-and-error. Carl Metzler (the author of NONLIN in the mid-1960s) once published a paper “Curve-Fitting: Art or Science?”… Be prepared, it will take you some time. The worst I know was a population PK/PD model, where an experienced group (!) of pharmaco­kineticists worked almost one year (!!) on two datasets (SD, MD)…
• If you really notice a change in clearance (e.g., in a multiple dose study trough values increase to a pseudo-equilibrium and subsequently decrease to the final steady state), try the following methods to model the changing clearance:
• Try a catenary model (additional hypothetical compartment before the central).
• Try a sigmoidal model.
• Classical PK/PD modeling may work well for some subjects, but fail terribly for others. Or you may end up with a one-compartment model for subjects with low concentrations and a two-compartment model for others. Population PK/PD is a much better choice, but the learning curve is even more steep… If you have sparse data (not a ‘rich dataset’ of well-defined profiles), only Pop-PK/PD will work.
• Try to get as much data as possible. If you have urine data, simultaneous fitting may improve your model. If you have data of a metabolite, fine.
• Start with an unweighted model. If one of the variants of the Gauss-Newton algorithm fails, try a grid-search (Simplex). Use these estimates as new starting values for Gauss-Newton. If still not stable (high standard errors), tweak the constraints (parameters’ boundaries). Try different weighting schemes next. Look at the residuals: Evenly spread around zero? Any trend? Funnel pattern? Base the model selection on the minimum AIC.
• The error distribution of the parts of the dataset may differ. Sometimes 1/y² is best for plasma and 1/y for urine. If PD-data cover only a limited range, unweighted may be the best.
• Once you have a Pop-PK/PD model of acceptable quality, start adding covariates (e.g., body weight/surface, sex, creatine clearance, disease state,…) until you get no further improvement.
• Pop-PK/PD models must be validated (Search the Guidelines for ‘Population’).
• Internal validation: Randomly select a group of subjects from the dataset, estimate model parameters, and check the agreement of the remaining group of subjects with predicted data.
• External validation (preferred): Check the prediction from the model with observed values of another study.
Good luck!

Suggestions:

J Gabrielsson and D Weiner
Pharmacokinetic an Pharmacodynamic Data Analysis: Concepts and Applications
Swedish Pharmaceutical Press, Stockholm (4th edition 2007)
  Good starting point, many examples, code for WinNonlin.
P Bonate
Pharmacokinetic-Pharmacodynamic Modeling and Simulation
Springer, New York (2006)
  Nothing to read in the subway. Good examples on model-identifiability and -discrimination.
M Rowland and T Tozer
Clinical Pharmacokinetics and Pharmacodynamics: Concepts and Applications
Lippincott Williams & Wilkins, Baltimore (4th edition 2010)
  The classic one.

Cheers,
Helmut Schütz

The quality of responses received is directly proportional to the quality of the question asked. ☼
Science Quotes
luvblooms4u
●

2010-11-12 06:31

@ Helmut
Posting: # 6140
Views: 11,804

## PK PD modelling

Dear HS

» I’m afraid you have to give us more informations. Normally the half-life of drugs is too short to be influenced by an increasing number of cells (are you thinking about a tumor?).

Yes mainly for Tumor cell related metabolism!! and also for the drugs that get distributed in tissues for longer period of time.

» Exceptions are drugs with very long half-lives (let’s say, more than a week), or the patient is in true steady-state (again, I’m talking about weeks).

Yes! That is the main area of concern

» Some general remarks about modeling:
» Get some books. Read them. Take a vacation. Read them again.

. I will love to do that!

» If you really notice a change in clearance (e.g., in a multiple dose
»   study trough values increase to a pseudo-equilibrium and subsequently
»   decrease to the final steady state), try the following methods to model
»   the changing clearance:
»    Add a lag-time.

Let me try this !!

»    Try a catenary model (additional hypothetical compartment before
»     the central).

Yeah This might be the approach I should look for but what if I want to see and related the metabolism in the hypothetical compartment

Let me read them first and clear my thoughts then I will be back!

Thanks a lot

Luv!!
Helmut
★★★

Vienna, Austria,
2010-11-13 15:47

@ luvblooms4u
Posting: # 6146
Views: 11,749

## Profile check first!

Dear Luv(blooms)!

One additional note: Check the time-course in a multiple dose study as suggested by Yung-jin in his first post. If you don’t see a deviation from linear PK, stop worrying about trying to fit any (!) model. If a change in clearance(s) is not reflected in plasma concentrations, no model will work (i.e. converge).

Example modified from Danielsson/Weiner (4th ed. pp. 684–90), Autoinduction, two-compartment PK.

Single dose study; 1 h infusion of 40 mg (bottom left). It was decided based on a simulation (top green line) to start the multiple dose study with a 1 h infusion of 120 mg as a loading dose, followed by 0.5 h infusions of 40 mg (τ = 8 h). What we see, is autoinduction which lead roughly after the second day to equilibrium of only ≈50 % of predicted from the simple model (without autoinduction).

Cheers,
Helmut Schütz

The quality of responses received is directly proportional to the quality of the question asked. ☼
Science Quotes
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