Nothing
tests/testthat/test_doseoptim.R
In posologyr: Individual Dose Optimization using Population Pharmacokinetics
mod_tobramycin_2cpt_fictional <- list(
ppk_model = rxode2::rxode({
centr(0) = 0;
tTVke = log(THETA_ke)+log(CLCREAT/67.8)*0.89+log(WT/66.4)*(-1.09);
tTVV = log(THETA_V)+log(WT/66.4)*0.80;
tTVk12 = log(THETA_k12);
tTVk21 = log(THETA_k21);
ke = exp(tTVke+ETA_ke);
V = exp(tTVV+ETA_V);
k12 = exp(tTVk12);
k21 = exp(tTVk21);
Cc = centr/V;
d/dt(centr) = - ke*centr - k12*centr + k21*periph;
d/dt(periph) = + k12*centr - k21*periph;
d/dt(AUC) = Cc;
}),
error_model = function(f,sigma){
g <- sigma[1] + sigma[2]*f
return(g)
},
theta = c(THETA_ke=0.21, THETA_V=19.8,THETA_k12=0.041, THETA_k21=0.12),
omega = lotri::lotri({ETA_ke + ETA_V + ETA_k12 + ETA_k21 ~
c(0.08075,
0 , 0.01203,
0 , 0 , 0,
0 , 0 , 0, 0)}),
covariates = c("CLCREAT","WT"),
sigma = c(additive_a = 0, proportional_b = 0.198))
mod_vancomycin_2cpt_Goti2018 <- list(
ppk_model = rxode2::rxode({
centr(0) = 0;
TVCl = THETA_Cl*(CLCREAT/120)^0.8*(0.7^DIAL);
TVVc = THETA_Vc*(WT/70) *(0.5^DIAL);
TVVp = THETA_Vp;
TVQ = THETA_Q;
Cl = TVCl*exp(ETA_Cl);
Vc = TVVc*exp(ETA_Vc);
Vp = TVVp*exp(ETA_Vp);
Q = TVQ;
ke = Cl/Vc;
k12 = Q/Vc;
k21 = Q/Vp;
Cc = centr/Vc;
d/dt(centr) = - ke*centr - k12*centr + k21*periph;
d/dt(periph) = + k12*centr - k21*periph;
d/dt(AUC) = Cc;
}),
error_model = function(f,sigma){
g <- sigma[1] + sigma[2]*f
return(g)
},
theta = c(THETA_Cl=4.5, THETA_Vc=58.4, THETA_Vp=38.4,THETA_Q=6.5),
omega = lotri::lotri({ETA_Cl + ETA_Vc + ETA_Vp + ETA_Q ~
c(0.147,
0 , 0.510,
0 , 0, 0.282,
0 , 0, 0, 0)}),
covariates = c("CLCREAT","WT","DIAL"),
sigma = c(additive_a = 3.4, proportional_b = 0.227))
df_patient01_tobra <- data.frame(ID=1,TIME=c(0.0,1.0,14.0),
DV=c(NA,25.0,5.5),
AMT=c(500,0,0),
DUR=c(0.5,NA,NA),
EVID=c(1,0,0),
CLCREAT=80,WT=65)
df_patient04_vanco <- data.frame(ID=1,TIME=c(0.0,13.0,24.2,48),
DV=c(NA,12,NA,10.5),
AMT=c(2000,0,1400,0),
DUR=c(2,NA,2,NA),
EVID=c(1,0,1,0),
CLCREAT=65,WT=70,DIAL=0)
params_patient01_tobra_map <- c(THETA_ke=0.21,
CLCREAT=80,
WT=65,
THETA_V=19.8,
THETA_k12=0.041,
THETA_k21=0.12,
ETA_ke=-0.6828811,
ETA_V=-0.0663349)
params_patient04_vanco_map <- c(THETA_Cl=4.5,
CLCREAT=65,
DIAL=0,
THETA_Vc=58.4,
WT=70,
THETA_Vp=38.4,
THETA_Q=6.5,
ETA_Cl=0.10796221,
ETA_Vc=0.04643863,
ETA_Vp=0.06859768)
test_that("Same optimal dose with or without providing MAP estimates", {
expect_equal(poso_dose_conc(dat=df_patient01_tobra,
prior_model=mod_tobramycin_2cpt_fictional,
time_c=1,
duration=0.5,
target_conc=30,
indiv_param=params_patient01_tobra_map)$dose,
poso_dose_conc(dat=df_patient01_tobra,
prior_model=mod_tobramycin_2cpt_fictional,
time_c=1,
duration=0.5,
target_conc=30)$dose,
tolerance=1e-3)
expect_equal(poso_dose_auc(dat=df_patient01_tobra,
prior_model=mod_tobramycin_2cpt_fictional,
time_auc=12,
duration=0.5,
target_auc=200,
indiv_param=params_patient01_tobra_map)$dose,
poso_dose_auc(dat=df_patient01_tobra,
prior_model=mod_tobramycin_2cpt_fictional,
time_auc=12,
duration=0.5,
target_auc=200,
indiv_param=NULL)$dose,
tolerance=1e-3)
expect_equal(poso_time_cmin(dat=df_patient01_tobra,
prior_model=mod_tobramycin_2cpt_fictional,
dose=620,
duration=0.5,
target_cmin=0.5,
indiv_param=params_patient01_tobra_map)$time,
poso_time_cmin(dat=df_patient01_tobra,
prior_model=mod_tobramycin_2cpt_fictional,
dose=620,
duration=0.5,
target_cmin=0.5)$time,
tolerance=1e-3)
})
single_adm_cmin <- poso_time_cmin(dat=df_patient04_vanco,
prior_model=mod_vancomycin_2cpt_Goti2018,
from=2,
dose=1500,
duration=2,
target_cmin=10,
indiv_param=params_patient04_vanco_map)
single_adm_auc <- poso_dose_auc(dat=df_patient04_vanco,
prior_model=mod_vancomycin_2cpt_Goti2018,
time_auc=24,
duration=2,
target_auc=400,
indiv_param=params_patient04_vanco_map)
single_adm_conc <- poso_dose_conc(dat=df_patient04_vanco,
prior_model=mod_vancomycin_2cpt_Goti2018,
time_c=24,
duration=2,
target_conc=11.04931,
indiv_param=params_patient04_vanco_map)
test_that("Optimization results do not deviate from known values
for single dose administration", {
#also test for issue #43
expect_equal(single_adm_cmin$time,11.2)
expect_equal(single_adm_cmin$cmin_estimate,10,tolerance=1e-1)
expect_equal(single_adm_auc$dose,2377.758,tolerance=1e-3)
expect_equal(single_adm_auc$auc_estimate,400)
expect_equal(single_adm_conc$dose,2530.699,tolerance=1e-3)
expect_equal(single_adm_conc$conc_estimate,11.05,tolerance=1e-2)
})
test_that("Optimization results do not deviate from known values
for multiple dose regimen", {
expect_equal(poso_time_cmin(dat=df_patient04_vanco,
prior_model=mod_vancomycin_2cpt_Goti2018,
from=2,
dose=1500,
interdose_interval=24,
add_dose=10,
duration=2,
target_cmin=10,
indiv_param=params_patient04_vanco_map)$time,
34.8)
expect_equal(poso_dose_auc(dat=df_patient04_vanco,
prior_model=mod_vancomycin_2cpt_Goti2018,
time_auc=24,
starting_time=24*9,
interdose_interval=24,
add_dose=10,
duration=2,
target_auc=400,
indiv_param=params_patient04_vanco_map)$dose,
1229.366,
tolerance=1e-3)
expect_equal(poso_dose_conc(dat=df_patient04_vanco,
prior_model=mod_vancomycin_2cpt_Goti2018,
time_c=24*9.9,
interdose_interval=24,
add_dose=10,
duration=24,
target_conc=400/24,
indiv_param=params_patient04_vanco_map)$dose,
1229.426,
tolerance=1e-3)
expect_equal(poso_inter_cmin(dat=df_patient04_vanco,
prior_model=mod_vancomycin_2cpt_Goti2018,
indiv_param=params_patient04_vanco_map,
dose=2000,
add_dose=10,
duration=2,
target_cmin=10)$interval,
35.9,
tolerance=1e-3)
expect_equal(poso_time_cmin(dat=df_patient04_vanco,
prior_model=mod_vancomycin_2cpt_Goti2018,
from=2,
dose=1500,
interdose_interval=24,
add_dose=10,
duration=2,
target_cmin=10)$time,34.8)
expect_equal(poso_dose_auc(dat=df_patient04_vanco,
prior_model=mod_vancomycin_2cpt_Goti2018,
time_auc=24,
starting_time=24*9,
interdose_interval=24,
add_dose=10,
duration=2,
target_auc=400)$dose,1229.366,tolerance=1e-3)
expect_equal(poso_dose_conc(dat=df_patient04_vanco,
prior_model=mod_vancomycin_2cpt_Goti2018,
time_c=24*9.9,
interdose_interval=24,
add_dose=10,
duration=24,
target_conc=400/24)$dose,1229.426,tolerance=1e-3)
expect_equal(poso_inter_cmin(dat=df_patient04_vanco,
prior_model=mod_vancomycin_2cpt_Goti2018,
dose=2000,
add_dose=10,
duration=2,
target_cmin=10)$interval,35.9,tolerance=1e-3)
})
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posologyr documentation built on April 3, 2025, 10:39 p.m.
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mod_tobramycin_2cpt_fictional <- list(
ppk_model = rxode2::rxode({
centr(0) = 0;
tTVke = log(THETA_ke)+log(CLCREAT/67.8)*0.89+log(WT/66.4)*(-1.09);
tTVV = log(THETA_V)+log(WT/66.4)*0.80;
tTVk12 = log(THETA_k12);
tTVk21 = log(THETA_k21);
ke = exp(tTVke+ETA_ke);
V = exp(tTVV+ETA_V);
k12 = exp(tTVk12);
k21 = exp(tTVk21);
Cc = centr/V;
d/dt(centr) = - ke*centr - k12*centr + k21*periph;
d/dt(periph) = + k12*centr - k21*periph;
d/dt(AUC) = Cc;
}),
error_model = function(f,sigma){
g <- sigma[1] + sigma[2]*f
return(g)
},
theta = c(THETA_ke=0.21, THETA_V=19.8,THETA_k12=0.041, THETA_k21=0.12),
omega = lotri::lotri({ETA_ke + ETA_V + ETA_k12 + ETA_k21 ~
c(0.08075,
0 , 0.01203,
0 , 0 , 0,
0 , 0 , 0, 0)}),
covariates = c("CLCREAT","WT"),
sigma = c(additive_a = 0, proportional_b = 0.198))
mod_vancomycin_2cpt_Goti2018 <- list(
ppk_model = rxode2::rxode({
centr(0) = 0;
TVCl = THETA_Cl*(CLCREAT/120)^0.8*(0.7^DIAL);
TVVc = THETA_Vc*(WT/70) *(0.5^DIAL);
TVVp = THETA_Vp;
TVQ = THETA_Q;
Cl = TVCl*exp(ETA_Cl);
Vc = TVVc*exp(ETA_Vc);
Vp = TVVp*exp(ETA_Vp);
Q = TVQ;
ke = Cl/Vc;
k12 = Q/Vc;
k21 = Q/Vp;
Cc = centr/Vc;
d/dt(centr) = - ke*centr - k12*centr + k21*periph;
d/dt(periph) = + k12*centr - k21*periph;
d/dt(AUC) = Cc;
}),
error_model = function(f,sigma){
g <- sigma[1] + sigma[2]*f
return(g)
},
theta = c(THETA_Cl=4.5, THETA_Vc=58.4, THETA_Vp=38.4,THETA_Q=6.5),
omega = lotri::lotri({ETA_Cl + ETA_Vc + ETA_Vp + ETA_Q ~
c(0.147,
0 , 0.510,
0 , 0, 0.282,
0 , 0, 0, 0)}),
covariates = c("CLCREAT","WT","DIAL"),
sigma = c(additive_a = 3.4, proportional_b = 0.227))
df_patient01_tobra <- data.frame(ID=1,TIME=c(0.0,1.0,14.0),
DV=c(NA,25.0,5.5),
AMT=c(500,0,0),
DUR=c(0.5,NA,NA),
EVID=c(1,0,0),
CLCREAT=80,WT=65)
df_patient04_vanco <- data.frame(ID=1,TIME=c(0.0,13.0,24.2,48),
DV=c(NA,12,NA,10.5),
AMT=c(2000,0,1400,0),
DUR=c(2,NA,2,NA),
EVID=c(1,0,1,0),
CLCREAT=65,WT=70,DIAL=0)
params_patient01_tobra_map <- c(THETA_ke=0.21,
CLCREAT=80,
WT=65,
THETA_V=19.8,
THETA_k12=0.041,
THETA_k21=0.12,
ETA_ke=-0.6828811,
ETA_V=-0.0663349)
params_patient04_vanco_map <- c(THETA_Cl=4.5,
CLCREAT=65,
DIAL=0,
THETA_Vc=58.4,
WT=70,
THETA_Vp=38.4,
THETA_Q=6.5,
ETA_Cl=0.10796221,
ETA_Vc=0.04643863,
ETA_Vp=0.06859768)
test_that("Same optimal dose with or without providing MAP estimates", {
expect_equal(poso_dose_conc(dat=df_patient01_tobra,
prior_model=mod_tobramycin_2cpt_fictional,
time_c=1,
duration=0.5,
target_conc=30,
indiv_param=params_patient01_tobra_map)$dose,
poso_dose_conc(dat=df_patient01_tobra,
prior_model=mod_tobramycin_2cpt_fictional,
time_c=1,
duration=0.5,
target_conc=30)$dose,
tolerance=1e-3)
expect_equal(poso_dose_auc(dat=df_patient01_tobra,
prior_model=mod_tobramycin_2cpt_fictional,
time_auc=12,
duration=0.5,
target_auc=200,
indiv_param=params_patient01_tobra_map)$dose,
poso_dose_auc(dat=df_patient01_tobra,
prior_model=mod_tobramycin_2cpt_fictional,
time_auc=12,
duration=0.5,
target_auc=200,
indiv_param=NULL)$dose,
tolerance=1e-3)
expect_equal(poso_time_cmin(dat=df_patient01_tobra,
prior_model=mod_tobramycin_2cpt_fictional,
dose=620,
duration=0.5,
target_cmin=0.5,
indiv_param=params_patient01_tobra_map)$time,
poso_time_cmin(dat=df_patient01_tobra,
prior_model=mod_tobramycin_2cpt_fictional,
dose=620,
duration=0.5,
target_cmin=0.5)$time,
tolerance=1e-3)
})
single_adm_cmin <- poso_time_cmin(dat=df_patient04_vanco,
prior_model=mod_vancomycin_2cpt_Goti2018,
from=2,
dose=1500,
duration=2,
target_cmin=10,
indiv_param=params_patient04_vanco_map)
single_adm_auc <- poso_dose_auc(dat=df_patient04_vanco,
prior_model=mod_vancomycin_2cpt_Goti2018,
time_auc=24,
duration=2,
target_auc=400,
indiv_param=params_patient04_vanco_map)
single_adm_conc <- poso_dose_conc(dat=df_patient04_vanco,
prior_model=mod_vancomycin_2cpt_Goti2018,
time_c=24,
duration=2,
target_conc=11.04931,
indiv_param=params_patient04_vanco_map)
test_that("Optimization results do not deviate from known values
for single dose administration", {
#also test for issue #43
expect_equal(single_adm_cmin$time,11.2)
expect_equal(single_adm_cmin$cmin_estimate,10,tolerance=1e-1)
expect_equal(single_adm_auc$dose,2377.758,tolerance=1e-3)
expect_equal(single_adm_auc$auc_estimate,400)
expect_equal(single_adm_conc$dose,2530.699,tolerance=1e-3)
expect_equal(single_adm_conc$conc_estimate,11.05,tolerance=1e-2)
})
test_that("Optimization results do not deviate from known values
for multiple dose regimen", {
expect_equal(poso_time_cmin(dat=df_patient04_vanco,
prior_model=mod_vancomycin_2cpt_Goti2018,
from=2,
dose=1500,
interdose_interval=24,
add_dose=10,
duration=2,
target_cmin=10,
indiv_param=params_patient04_vanco_map)$time,
34.8)
expect_equal(poso_dose_auc(dat=df_patient04_vanco,
prior_model=mod_vancomycin_2cpt_Goti2018,
time_auc=24,
starting_time=24*9,
interdose_interval=24,
add_dose=10,
duration=2,
target_auc=400,
indiv_param=params_patient04_vanco_map)$dose,
1229.366,
tolerance=1e-3)
expect_equal(poso_dose_conc(dat=df_patient04_vanco,
prior_model=mod_vancomycin_2cpt_Goti2018,
time_c=24*9.9,
interdose_interval=24,
add_dose=10,
duration=24,
target_conc=400/24,
indiv_param=params_patient04_vanco_map)$dose,
1229.426,
tolerance=1e-3)
expect_equal(poso_inter_cmin(dat=df_patient04_vanco,
prior_model=mod_vancomycin_2cpt_Goti2018,
indiv_param=params_patient04_vanco_map,
dose=2000,
add_dose=10,
duration=2,
target_cmin=10)$interval,
35.9,
tolerance=1e-3)
expect_equal(poso_time_cmin(dat=df_patient04_vanco,
prior_model=mod_vancomycin_2cpt_Goti2018,
from=2,
dose=1500,
interdose_interval=24,
add_dose=10,
duration=2,
target_cmin=10)$time,34.8)
expect_equal(poso_dose_auc(dat=df_patient04_vanco,
prior_model=mod_vancomycin_2cpt_Goti2018,
time_auc=24,
starting_time=24*9,
interdose_interval=24,
add_dose=10,
duration=2,
target_auc=400)$dose,1229.366,tolerance=1e-3)
expect_equal(poso_dose_conc(dat=df_patient04_vanco,
prior_model=mod_vancomycin_2cpt_Goti2018,
time_c=24*9.9,
interdose_interval=24,
add_dose=10,
duration=24,
target_conc=400/24)$dose,1229.426,tolerance=1e-3)
expect_equal(poso_inter_cmin(dat=df_patient04_vanco,
prior_model=mod_vancomycin_2cpt_Goti2018,
dose=2000,
add_dose=10,
duration=2,
target_cmin=10)$interval,35.9,tolerance=1e-3)
})
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