# question in Box-Cox Transformations in K-PD model

From: kehua wu <kehuawumail>
Date: Mon, 12 Aug 2013 14:36:25 -0500

Dear NONMEM users,

I am trying to build a model to describe the drug toxicity on neuropathy.
Since I am having dose and toxicity data, the K-PD model was applied in our
model. The distribution of baseline is heavily left skewed. So I am also
trying included the Box-cox transformation to get a accurate estimate of
baseline. I followed Prof. Karlsson's paper. (Petersson KJ, Hanze E, Savic
RM, Karlsson MO. Semiparametric distributions with estimated shape
parameters. Pharm Res. 2009;26(9):2174-85.)

My problem is that NONMEM never gave an estimate of BXPAR (I got the
initial value of BXPAR in the output file).

The control stream and a sample of data follows.

Many thanks in advance.

Kehua

*
control stream*:

\$MODEL

NCOMP=2
COMP=(DOSE)
COMP=(OBS)

\$PK

KIN=THETA(1)*EXP(ETA(1))
BXPAR=THETA(2)
PHI=EXP(ETA(2))
ETATR=(PHI**BXPAR-1)/BXPAR
BASELINE=THETA(3)+(PHI**BXPAR-1)/BXPAR
KDE=THETA(4)*EXP(ETA(3))
EDK50=THETA(5)*EXP(ETA(4))
EMAX=THETA(6)*EXP(ETA(5))
KOUT=KIN/(BASELINE)
F2=BASELINE
S2=1
(I also tried to estimate KIN and KOUT. BASELINE=KIN/KOUT. the BOX-cox
transformation was added on KOUT. But did not get any estimate on BXPAR
either.)
\$DES

VIR=A(1)*KDE
IRG=VIR
COEF=1-(IRG*EMAX/(EDK50+IRG))

\$ERROR
IPRED=F
IRES=DV-IPRED
IF (F.EQ.0) FX=1
W=F+FX
IWRES=IRES/W

Y = F + ERR(1)+F*ERR(2)

*data*:
PATID DAY amt fgsum4 addl II CMT 1 0
3

2 1 1 150.3704
3 7 1 1 29 155.5556
3 7 1 1 54
6

2 1 57 155.5556
3 7 1 1 85 155.5556
3 7 1 1 108
13

2 1 113 155.5556
3 7 1 1 135
12

2 1 141 155.5556
3 7 1 1 162
9

2 1 169 150
3 7 1 1 190
14

2 1 197 155.5556
3 7 1 1 217
16

2 1 225 73.7234
5 7 1 1 267 139.8674
0 0 1 2 0
0

2 2 1 113.5556
3 7 1 2 27
3

2 2 29 116.6667
3 7 1 2 54
0

2 2 57 113.8148
3 7 1 2 81
2

2 2 85 108
3 7 1 2 109
2

2 2 113 112.9633
0 0 1 3 0
2

2 3 1 126
3 7 1 3 27
4

2 3 29 126
3 7 1 3 54
4

2 3 57 126
3 7 1 3 81
5

2 3 85 126
3 7 1

Received on Mon Aug 12 2013 - 15:36:25 EDT

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