**From MAJ_MARK_MARINO@wrsmtp-ccmail.army.mil Fri Jul 12 14:43:55 1996
**

Dear NONMEM users,

I am working on a PK-PD model with a two step approach. First the PK is being done in adv4tr4. The parameters of clearance and volume are modeled as being dependent on weight and gender. I then take the results of the Bayesein PK parameters and feed them into the PD model to generate effect site amounts and effect using adv5tr1 fixing K1e to .001*K10. Since adv5tr1 uses amounts my EConc50 is truly an EAmount50. To back calculate a plasma EC50 I use the equation

K1e * A1 = Keo * Ae and since K1e = .001*K10

.001 * K10 * C * Vc = Keo * Ae

.001 * (CL / Vc) * C * Vc = Keo * Ae

EC50 = Keo * Ae / (.001 * CL)

My CL is dependent on both weight and gender giving me a EC50 that is dependent on weight and gender? Is this correct or is there something wrong with the way I am calculating my EC50? Any help would be appreciated.

Mark T. Marino

WRAIR

****

**From VPIOTROV@janbelc1.ssw.jnj.com Mon Jul 29 03:47:08 1996
**

Hello Mark,

The best way to get reliable estimates of EC50 and other PD parameters is to fit both PK and PD data simultaneously using the method developed by L. Sheiner and S. Beal and presented at the last NONMEM workshop in Uppsala. Your data file should contain both Cp and effect observations and should be organized in the following way: when DV is a CP observation, CMT = 2; when DV is an effect observation, CMT= 4. The following initial (without covariates) control stream could be proposed:

$PROBLEM PK-PD data: effect compartment model

$INPUT ID TIME DV DOSE=AMT CMT

$DATA yourdata

$SUBROUTINES ADVAN5 TRANS1

$MODEL

COMP=(DEPOT) ;1

COMP=(CENTRAL DEFOBS NOOFF) ;2

COMP=(PERIPH) ;3

COMP=(EFFECT) ;4

$PK

K12= THETA(1)*EXP(ETA(1)) ;Absorption

K20= THETA(2)*EXP(ETA(2)) ;Elimination

K23= THETA(3)*EXP(ETA(3)) ;To peripheral

K32= THETA(4)*EXP(ETA(4)) ;From peripheral

K24= .001*K20 ;To effect

K40= THETA(5)*EXP(ETA(5)) ;keo

S2= THETA(6)*EXP(ETA(6)) ;Central V

S4= S2*K24/K40 ;Preserves Cess = Cpss

EMAX=THETA(7)*EXP(ETA(7)) ;Emax

EC50=THETA(8)*EXP(ETA(8)) ;EC50

$ERROR

Y1=F*EXP(ERR(1))

Y2=EMAX*F/(EC50+F)*EXP(ERR(2))

Q=1 ;Cp

IF (CMT.EQ.4) Q=0 ;Effect

Y=Q*Y1+(1-Q)*Y2

$THETA

...

$OMEGA

...

$SIGMA

...

etc.

You can re-parameterize the PK model in terms of CL, Q and V1, V2. You can also add fixed effects of covariates and reduce the number of ETAs. Try and let me know if it works.

Yours,

Vladimir

----------------------------------------------------------------------

Vladimir Piotrovskij, Ph.D.

Janssen Research Foundation

Clinical Pharmacokinetics

B-2340 Beerse

Belgium

Fax: +32-14-603768

Email: vpiotrov@janbe.jnj.com