# RE: Interoccation variation question

From: TKT <tkt>
Date: Mon, 6 Apr 2009 15:25:18 +0200

Dear Nick,

Thank you for this which answers the question re. how to parameterize and i=
s in line with what
I have been doing so far. Basically I was wondering if the fact that all su=
bjects in trial 1 only have one occasion could
in any way represent a problem for separation and estimation of the two ETA=
s for those subjects, and if it would make any sense to
only let subjects with data from >1 occasion contribute to the estimation o=
f Eta2 and Eta3 (in your version of the code).

BR
Thomas

________________________________
From: Nick Holford [mailto:n.holford
Sent: 6. april 2009 14:50
To: TKT (Thomas Klitgaard)
Subject: Re: [NMusers] Interoccation variation question

Thomas,

In trial 1 I would give all subjects an OCC=1. In trial 2 give each subje=
ct an OCC=1 for the first week of PK sampling and OCC=2 for the third w=
eek i.e. 2nd PK sampling occasion.

I would use this code (with KA as an example):

\$THETA
1 ; POPKA
\$OMEGA
0.5 ; BSVKA
\$OMEGA BLOCK(1)
0.5 ; BOVKA1
\$OMEGA BLOCK(1) SAME
;; BOVKA2

\$PK
BSVKA=ETA(1)
IF (OCC.EQ.1) THEN
BOVKA=ETA(2)
ENDIF
IF (OCC.EQ.2) THEN
BOVKA=ETA(3)
ENDIF
KA=THETA(1)*EXP(BSVKA + BOVKA)

You can use this code for estimation and simulation.

I don't really understand your questions so perhaps you could try asking th=
em again based on the above advice.

Nick

TKT (Thomas Klitgaard) wrote:
Dear colleagues,

I'm currently working on a population PK analysis where I probably need to =
incorporate interoccation variation on one or more parameters. However,
I'm wondering about one issue. To put it short, here's the problem:

Trial 1: 1 dosing occation, PK observed for 1 week
Trial 2: 3 dosing occation (1 x week), not full washout between, PK observe=
d for 1 week after dose 1 and after dose 3. PK varies betw. wk 1 and 3. wit=
hin subject.

Question: Should

1) occasion flag OCC=1 for all subject in trial 1 and OCC=1 (week1) and=
2 (week 3) in trial 2? Or should
2) occasion flag OCC be omitted for trial 1 subjects and set to 1 or 2 as i=
n 1) for trial 2.

On one hand, 1) would strictly speaking seem correct as these subjects have=
only a dose 1 occation. On the other hand, my feeling is that NONMEM would=
be
put in trouble with seemingly always two inseparable individual ETAs in tri=
al 1 subjects for parameters with IOV on. (I'm using FOCEI).

Ka = TVKA*EXP(ETA(IIV_Ka))
IF (OOC.EQ.1) Ka = Ka*EXP(ETA(Occ_1))
IF (OOC.EQ.2) Ka = Ka*EXP(ETA(Occ_2))
..
\$OMEGA
.1
.1 SAME

If 2) is the better approach of the two, would the simulation model not sti=
ll be Ka=TVKA*EXP(ETA(IIV_Ka)+ETA(Occ)) for any subject, regards of no. o=
f occasions?
(Ie. above manoeuvre would be only to avoid an estimation problem).

??

Thx. for any input

Thomas

____________________

Thomas Klitgaard
Principal Scientist
Biomodelling

Novo Nordisk A/S
Krogshøjvej 53 A
DK-2880 Bagsværd
Denmark
+45 4442 4960 (direct)
+45 3079 4960 (mobile)
tkt
www.novonordisk.com

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--
Nick Holford, Dept Pharmacology & Clinical Pharmacology
University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New Zealan=
d
n.holford
0 fax:+64(9)373-7090
http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford

Received on Mon Apr 06 2009 - 09:25:18 EDT

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