RE: Antwort: [NMusers] PK/PD models to describe anti-ancer drug effect on the tumor volume

Dear All,


With respect to the second part of Patrick's question, you may want to chec=
k another reference from Simeoni´s group:

Rocchetti M, Simeoni M, Pesenti E, De Nicolao G, Poggesi I. Predicting the =
active doses in humans from animal studies: a novel approach in oncology.Eu=
r J Cancer. 2007 Aug;43(12):1862-8. Epub 2007 Jul 2.

Best regards,
Juan Jose Perez Ruixo.

-----Original Message-----
From: owner-nmusers_at_globomaxnm.com [mailto:owner-nmusers_at_globomaxnm.com] On=
 Behalf Of Bonate, Peter
Sent: Monday, January 07, 2008 7:52 AM
To: nele.plock_at_bayerhealthcare.com; patrickmzhou_at_yahoo.com
Cc: nmusers_at_globomaxnm.com
Subject: RE: Antwort: [NMusers] PK/PD models to describe anti-ancer drug ef=
fect on the tumor volume

I think it's worth mentioning here that Simeoni's model is just as empirica=
l as other tumor growth models. Patrick should also consider Gompertz or l=
ogisitic growth models. There is a large body of literature using these la=
tter models which oncologists and cancer pharmacologists are used to and fa=
miliar with. Simeoni's model is still relatively new and, while it is couc=
hed in terms of 'mechanistic' models, there is still an empirical component=
 to it. I would still use the Gompertz model.

The second part of Patrick's question was how do you use the output from th=
ese models to help guide human drug development. So here is what we have u=
sed. Typically you get pk in mice and rats from the ADME group. In a sepa=
rate study by the cancer pharmacology group, you get tumor growth in mice w=
ithout collecting pk. I then fix the pk and model the tumor growth under =
the dosing regimen in the xenograft study. The output from the Gompertz mo=
del is then an IC50. This is the target you need to acheive in humans, usu=
ally assuming trough. You could then allometrically scale the rodent model=
s to get pk in humans and simulate an approximate dosing regimen to acheive=
 a trough concentration or a 24 hour concentration above the IC50. And I d=
on't usually do this work in NONMEM. The mice pk data are usually single t=
ime-point studies so a naive pooled approach is reasonable. You could mode=
l the xenograft data in NONMEM, but I would expect that your IC50s would be=
 similar regardless of whether you model mean data or individual-level data=
.

Hope this helps

pete bonate


Peter L. Bonate, PhD, FCP
Genzyme Corporation
Senior Director
Clinical Pharmacology and Pharmacokinetics
4545 Horizon Hill Blvd
San Antonio, TX 78229 USA
peter.bonate_at_genzyme.com
phone: 210-949-8662
fax: 210-949-8219
crackberry: 210-315-2713

-----Original Message-----
From: owner-nmusers_at_globomaxnm.com [mailto:owner-nmusers_at_globomaxnm.com] On=
 Behalf Of nele.plock_at_bayerhealthcare.com
Sent: Monday, January 07, 2008 1:36 AM
To: patrickmzhou_at_yahoo.com
Cc: nmusers_at_globomaxnm.com
Subject: Antwort: [NMusers] PK/PD models to describe anti-ancer drug effect=
 on the tumor volume

Dear Patrick,

the Simeoni model works well:
Simeoni M, Magni P, Cammia C, De Nicolao G, Croci V, Pesenti E, Germani M,
Poggesi I, Rocchetti M.
Predictive pharmacokinetic-pharmacodynamic modeling of tumor growth
kinetics in xenograft models after administration of anticancer agents.
Cancer Res. 2004 Feb 1;64(3):1094-101.

I've attached a code using this model below. My code used the
concentrations in tumor tissue, but you can just as well use the serum
concentrations.
I also develowed a second model which uses linear tumor growth and
considers resistance development over time, which is less pronounced if
concentrations of the anti-tumor drug increase. I've attached that code as
well, maybe it is useful.
Considering the predictiveness of the model, in my case it seemed like the
use of physiological life-span seemed to be a good corrector (I got the
idea from Monro, Drug Toxicokinetics: Scope and Limitations that Arise
from Species Differences in Pharmacodynamic and Carcinogenic Responses, J
Pharmacokin Biopharm 22, 41-57, 1994). I.e. if you want your patients to
survive 6 months, then use human average age of 75 years and mouse age of
2 years, so a mouse would have to survive 6 months/75*2= 5 days. But this
might be different from drug to drug.

Best wishes
Nele

Simeoni:
$SUBROUTINES ADVAN6 TOL=3
$MODEL
  COMP=(GUT)
  COMP=(CENTRAL)
  COMP=(TUMOR)
  COMP=(PD)


$PK

TVCL=THETA(1)
CL=TVCL
;
TVV2=THETA(2)
V2=TVV2
;
TVKA=THETA(3)
KA=TVKA

TVF1=THETA(4)
F1=TVF1

TVPC=THETA(5)
PC=TVPC

TVKEO=THETA(6)
KEO=TVKEO

;
TVL0=THETA(7)
L0=TVL0*EXP(ETA(1))
;
TVL1=THETA(8)
L1=TVL1

TVK2=THETA(9)
K2=TVK2

W0=THETA(10)
F4=W0


S2=V2
K20=CL/V2
S4=1
PSI=20
;
$ERROR
  IPRED=F
  DEL=0
  IF (IPRED.EQ.0) DEL=0.0001
  W=F
  IRES=DV-IPRED
  IWRES=IRES/(W+DEL)
  Y=F+SQRT(THETA(12)*THETA(12)+THETA(11)*THETA(11)*F**2)*EPS(1)

;
$DES
DADT(1)= -KA*A(1)
DADT(2)= KA*A(1) -K20*A(2)
DADT(3)= KEO*(PC*A(2)/V2 - A(3))
DADT(4)= L0*A(4)/(1+(L0/L1*A(4))**PSI)**(1/PSI)-K2*A(3)*A(4)

own code:

$SUBROUTINES ADVAN8 TOL=3
$MODEL
  COMP=(GUT)
  COMP=(CENTRAL)
  COMP=(TUMOR)
  COMP=(PD)
  COMP=(AUC)

$PK

TVCL=THETA(1)
CL=TVCL*EXP(ETA(1))
;
TVV2=THETA(2)
V2=TVV2
;
TVKA=THETA(3)
KA=TVKA

TVF1=THETA(4)
F1=TVF1

TVPC=THETA(5)
PC=TVPC

TVKEO=THETA(6)
KEO=TVKEO

TVW0=THETA(7)
F4=TVW0
W0=F4 ; dataset: put a dummy dose of 1 into compartment 4, initial tumor
weight is then estimated as F4

TVKRES=THETA(8)
KRES=TVKRES

TVIC50=THETA(9)
IC50=TVIC50

TVKIN=THETA(10)
KIN=TVKIN

TVRED=THETA(13)
RED=TVRED


S2=V2
K20=CL/V2
S4=1


;
$ERROR
  IPRED=F
  DEL=0
  IF (IPRED.EQ.0) DEL=0.0001
  W=F
  IRES=DV-IPRED
  IWRES=IRES/(W+DEL)
  Y=F+SQRT(THETA(12)*THETA(12)+THETA(11)*THETA(11)*F**2)*EPS(1)

;
$DES
CAV=A(5)/(T+0.01)
RES=IC50*EXP(KRES*T*(1-CAV/(RED+CAV)))
DADT(1)= -KA*A(1)
DADT(2)= KA*A(1) -K20*A(2)
DADT(3)= KEO*(PC*A(2)/V2 - A(3))
DADT(4)= KIN*(1-A(3)/(RES+A(3)))
DADT(5)= A(3)
_________________________
Dr. Nele Plock
Bayer Schering Pharma AG
Drug Metabolism & Pharmacokinetics
Development Pharmacokinetics
Scientific Expert Development Pharmacokinetics
D- 13342 Berlin

Phone : +49-30-468 15146
Fax: +49-30-468 95146
nele.plock_at_bayerhealthcare.com
http://www.bayerscheringpharma.de

Vorstand: Arthur J. Higgins, Vorsitzender | Werner Baumann, Andreas Busch,
Ulrich Köstlin, Kemal Malik, Gunnar Riemann
Vorsitzender des Aufsichtsrats: Werner Wenning
Sitz der Gesellschaft: Berlin | Eintragung: Amtsgericht Charlottenburg 93
HRB 283



Patrick Zhou <patrickmzhou_at_yahoo.com>
Gesendet von: owner-nmusers_at_globomaxnm.com
06.01.2008 20:50

An
nmusers_at_globomaxnm.com
Kopie

Thema
[NMusers] PK/PD models to describe anti-ancer drug effect on the tumor
volume






Dear NMusers,
Does anyone aware any good published example (or non-public if you are
willing to share) of modeling the anti-cancer drug effect on the tumor
volume in nude mice model? And how this is normally used in the human dose
projection, and any published work of such? Please advice. Thank you very
much.

Patrick

 Be a better friend, newshound, and know-it-all with Yahoo! Mobile. Try it
now.

Received on Mon Jan 07 2008 - 11:02:48 EST