RE: Autoinduction model - An increased clearance(day 1- 14)
Dear Shankar,
As I read it, if your autoinduction is complete after 14 days, you do
not really have the data describing the autoinduction process, except
for a single trough sample, which is probably not enough considering the
inter-occasion variability in F and probably only a marginal or absent
autoinduction. Is the clearance statistically different from day 1 on
day 14 and onward? In the 2NN study (Antivir Ther. 2005;10(1):145-55.)
only a 10% difference in efavirenz clearance was found after
autoinduction. Perhaps you should pragmatically test if clearance on day
14 is different from clearance on day 1 by estimating
Clearance day 14 and onward = (clearance day 1)*Theta.
If it does not improve your model, the autoinduction is probably not
even there. Let the data decide.
Cheers,
Rob
----------
Rob ter Heine, PhD, PharmD
Hospital pharmacy resident
Meander Medical Center, Amersfoort, The Netherlands
T: +31-33-8502335
E: [email protected]
________________________________
Quoted reply history
Van: Shankar Lanke [mailto:[email protected]]
Verzonden: maandag 28 maart 2011 16:51
Aan: Heine, R. ter (Apotheek Algemeen/Management)
CC: [email protected]
Onderwerp: Re: [NMusers] Autoinduction model - An increased
clearance(day 1- 14)
Dear Rob ter Heine,
I am working with Efavirenz, I working with 66 patients, 924 data
points, intense on day 1 and 14 and a trough con in between the two
weeks.
I looked into the Physiological model presented by Dr. Karlsson earlier
but I did not used it since I dont have any information about ENZYME
comp or precursor.
I used the reasonable estimates based on earlier literature and aslo I
tried NPD approach.
Thank you very much Rob ter Heine, I appreciate your input.
On Mon, Mar 28, 2011 at 10:36 AM, <[email protected]> wrote:
Dear Shankar,
How rich is your dataset? In other words: do you have enough
data troughout the induction period to estimate the lagtime? You could,
for example try to fix the lagtime to a reasonable time and estimate the
inter-individual variability. Another way of estimating the
autoniduction is more physiologically based with a theoretical enzyme
compartment. For example, see:
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2014348/figure/fig01/
Which drug PK are you modelling? Most likely it is a
non-nucleoside reverse transcriptase inhibitor. The cyp3a4 autoinduction
with efavirenz is debatable and less profound than autoinduction with,
for example, nevirapine.
Sincerely,
Rob ter Heine
________________________________
Van: [email protected]
[mailto:[email protected]] Namens Shankar Lanke
Verzonden: maandag 28 maart 2011 15:53
Aan: [email protected]
Onderwerp: [NMusers] Autoinduction model - An increased
clearance(day 1- 14)
Dear All,
I am working on a Pop PK data where the patients are treated
with HIV drug. An autoinduction is involved with prolonged
administration of the drug. An increased CL is expected from day 1 to
day 14.
We have intense data on day 1 and day 14 with sparse data
between. Since a lag period is involved for the induction I used the
equation CL = CLinduced -(CLinduced - CLpre)*exp(-kout*(t-Tlag))
described by Johan Gabrielsson as more appropriate.
Also when I included a lag period for absorption in my earlier
model my fits are better and OBF decreased by 200.
However the final model with or without lag time for absorption
+ auto induction model is either terminated or covariance step is being
aborted.
I changed the initial estimates several times but still no luck.
Though the Auto induction model aborts the fits are better than the lag
time model however the estimates for Vd are 4 fold less than the
expected.
I appreciate your input and suggestions. Here is my code.
$SUBROUTINES ADVAN13 TRANS1 TOL=5 ;(I used ADVAN6 too)
$MODEL
NPAR=9 NCOMP=4
COMP=(DEPOT,DEFDOSE)
COMP=(LAG)
COMP=(OBSV,DEFOBS)
COMP=(PERIP)
$PK
CLP=THETA(1)
CLI=THETA(6)
KOUT=THETA(7)
TLAG=THETA(8)*EXP(ETA(6))
TVCL=CLI-(CLI-CLP)*EXP(-KOUT*(TIME-TLAG))
CL=TVCL*EXP(ETA(1))
TVV2=THETA(2)
V2=TVV2*EXP(ETA(2))
TVQ=THETA(3)
Q=TVQ*EXP(ETA(3))
TVV3=THETA(4)
V3=TVV3*EXP(ETA(4))
TVKA=THETA(5)
KA=TVKA*EXP(ETA(5))
TVALAG1=THETA(9)
ALAG1=TVALAG1*EXP(ETA(7))
S3=V2
$DES
K=CL/V2
K23=Q/V2
K32=Q/V3
DADT(1)=-KA*A(1)
DADT(2)=KA*A(1)-A(2)/ALAG1
DADT(3)=A(2)/ALAG1-K23*A(3)-K*A(3)+K32*A(4)
DADT(4)=K23*A(3)-K32*A(4)
$ERROR
DEL=0
IF (F.LE.0.0001) DEL=1
IPRE=F
W1= 1
W2= F
IRES= DV-IPRE
IWRE=IRES/(W1+W2)
Y = F + W1*ERR(1) + W2*ERR(2)
DV2=ABS(V2-TVV2)
$EST METHOD=1 INTERACTION PRINT=5 MAX=9999 SIG=3
MSFO=JLM.MSF
$THETA
(0, 6);[CLP]
(0, 90);[V2]
(0, 19);[Q]
(0, 200);[V3]
(0, 0.16);[KA]
(0, 8);[CLI]
(0, 0.001);[KOUT]
(0, 250);[TLAG]
(0, 0.3);[ALAG1]
$OMEGA
0.23 ;[CL] omega(1,1)
0.18;[V2] omega(2,2)
0 FIXED ;[Q] omega(3,3)
0.42;[V3] omega(4,4)
0.19;[KA] omega(5,5)
0.09;[TLAG for Ka]
0.1;[ALAG1 for CLI]
$SIGMA
0.06 ;[P] sigma(1,1)
0.09 ;[A] sigma(2,2)
$COV MATRIX=S
Regards,
Shankar Lanke Ph.D.
University at Buffalo
Office # 716-645-4853
Fax # 716-645-2886
Cell # 678-232-3567
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________________________________
--
Regards,
Shankar Lanke Ph.D.
University at Buffalo
Office # 716-645-4853
Fax # 716-645-2886
Cell # 678-232-3567
***************************DISCLAIMER****************************
De informatie in dit e-mail bericht is uitsluitend bestemd
voor de geadresseerde. Verstrekking aan en gebruik door
anderen is niet toegestaan. Door de elektronische verzending
van het bericht kunnen er geen rechten worden ontleend aan de
informatie.