# Re: [NMusers] Population PKPD using hair drug concentration

From: Nick Holford <n.holford_at_auckland.ac.nz>
Date: Fri, 12 Jun 2015 17:19:41 +0200

Bernard,

An alternative approach would be consider hair "concentrations"
accumulating in an output compartment. Each time the hair is cut you
"empty" the compartment and reset it to accumulate until the next hair
cut. This is similar to using an output compartment to predict amounts
in urine.

NONMEM has a convenient way to obtain a prediction of the amount output
from a compartment (such as plasma or the end of transit chain). You
just need to estimate an output fraction to explain the actual amount
you measure.

Best wishes,

Nick

+--------------------------------------------------------------------+
| |
| OUTPUT FRACTION PARAMETER |
| |
+--------------------------------------------------------------------+

MEANING: Output fraction (F0) parameter for PREDPP

USAGE:
\$PK
F0= ....

DISCUSSION:

The output fraction parameter is used with PREDPP. It is an optional
additional PK parameter. With NM-TRAN, it are symbolized in the \$PK
block by any one of the reserved variables FO, F0, or Fn, where n is
the compartment number of the output compartment.

With any of the kinetic models a (peripheral) output compartment is
always present. Associated with this compartment is a PK parameter,
the output fraction , denoted here by Fo. Of the entire amount, Ao, of
drug introduced into the system by various dosage patterns and then
eliminated from the system during a given time interval, a fraction Fo
of
Ao goes into this output compartment.

If the output compartment is never turned on, the output fraction can
be ignored. If the value of the output fraction is not computed in PK,
it is always understood to be 1

The use of Fo depends on the assumption that the rate of change of
drug amount in the output compartment is linear in the other compart-
ment amounts. Other than this linearity restriction, the system can be
nonlinear.

On 12/06/2015 3:54 p.m., Leonid Gibiansky wrote:
> Dear Bernard,
>
> This looks like really interesting problem. Based on the idea that it
> should be a long delay, I would start with the transit compartment
> model (you can google for the references on this type of models) with
> the input from the plasma compartment. The last compartment will
> represent a barber shop. The number of transit compartment can be
> increased until you get a sufficiently long delay. Observation
> compartment can be either the last one, or the sum of several,
> depending on how measurements are done (at a particular hair length,
> or by grinding the hair together before measurement). Depending on
> whether hair can eliminate the drug (or it happens only in the barber
> shop), hair clearance can be assigned to all or only to the last of
> those transit compartments.
>
> It could be that a simple effect compartment model with a very slow
> ke0 could describe it as well but you should be able to see it by
> increasing or decreasing the number of transit compartments.
>
> Regards,
> Leonid
>
>
>
> --------------------------------------
> Leonid Gibiansky, Ph.D.
> President, QuantPharm LLC
> web: www.quantpharm.com
> e-mail: LGibiansky at quantpharm.com
> tel: (301) 767 5566
>
>
>
> On 6/12/2015 8:56 AM, Bernard Ngara wrote:
>> Dear all
>>
>> I am a working on a study that measures both short and long term
>> exposure to drug using plasma and hair drug concentration. What
>> methods can I use to model hair drug concentration. You can give
>> references so that I can read.
>>
>> Thanks once again.
>>
>> Regards
>>

--
Nick Holford, Professor Clinical Pharmacology
Dept Pharmacology & Clinical Pharmacology, Bldg 503 Room 302A
University of Auckland,85 Park Rd,Private Bag 92019,Auckland,New Zealand
office:+64(9)923-6730 mobile:NZ+64(21)46 23 53 FR+33(7)80 48 55 50
email: n.holford_at_auckland.ac.nz
http://holford.fmhs.auckland.ac.nz/

Holford SD, Allegaert K, Anderson BJ, Kukanich B, Sousa AB, Steinman A, Pypendop, B., Mehvar, R., Giorgi, M., Holford,N.H.G. Parent-metabolite pharmacokinetic models - tests of assumptions and predictions. Journal of Pharmacology & Clinical Toxicology. 2014;2(2):1023-34.
Holford N. Clinical pharmacology = disease progression + drug action. Br J Clin Pharmacol. 2015;79(1):18-27.

Received on Fri Jun 12 2015 - 11:19:41 EDT

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