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. 2012 Jul 6;39(4):393–414. doi: 10.1007/s10928-012-9258-0
$PROBLEM SIM MODEL
$INPUT ID TIME AMT DV BMI HT CR AGE GEN WT BSA GFR CV1 CV2 CV3 CV4
$DATA DATA.PRN
$SUBROUTINE ADVAN1 TRANS2
$PK
CBMI = (BMI-26.29)/4.093
CHT = (HT-1.586)/0.2
CCR = (CR-0.985)/0117
CAGE = (AGE-38.81)/8.189
CWT = (WT-67.4)/21.2
CBSA = (BSA-1.713)/0.363
CGFR = (GFR-91.4)/37.9
CCV1 = (CV1-101.6)/30.7
CCV2 = (CV2-11)/4.33
CCV3 = (CV3-1.01)/0.209
CCV4 = (CV4-0.098)/0.0198
TVCL = THETA(1)*EXP(THETA(2)*BMI)*EXP(THETA(3)*GFR)
CL = TVCL*EXP(ETA(1))
TVV = THETA(4)*EXP(THETA(5)*BSA)*EXP((1-GEN)*THETA(6))
V = TVV*EXP(ETA(2))
S1 = V
$ERROR
Y = F*EXP(EPS(1)) +EPS(2)
IPRED = F*EXP(EPS(1)) +EPS(2); individual-specific prediction
$THETA (0,0.1); BASELINE CL
$THETA (0,0.04); BMI ON CL
$THETA (0,0.01); crcl oncl
$THETA (0,1); baseline volume
$THETA (0,0.3); bsa on V
$THETA (0,0.3); GEN ON V
$OMEGA BLOCK(2)
.2
0.05 .2
$SIGMA 0.1 0.001
$SIMULATION (12345) ONLYSIM
$TABLE ID TIME AMT IPRED BMI HT CR AGE GEN WT BSA GFR CV1 CV2 CV3 CV4
NOPRINT FILE = OUT.DAT ONEHEADER