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caffsim R package: Simulation of Plasma Caffeine Concentrations by Using Population Pharmacokinetic Model
Simulate plasma caffeine concentrations using population pharmacokinetic model described in Lee, Kim, Perera, McLachlan and Bae (2015) doi:10.1007/s00431-015-2581-x.
install.pacakges(" devtools" devtools :: install_github(" asancpt/caffsim" # Simply create single dose datasetcaffsim :: caffPkparam(Weight = 20 , Dose = 200 , N = 20 )
# Simply create multiple dose datasetcaffsim :: caffPkparamMulti(Weight = 20 , Dose = 200 , N = 20 , Tau = 12 )
library(caffsim )
MyDataset <- caffPkparam(Weight = 20 , Dose = 200 , N = 20 )
knitr :: kable(head(MyDataset ), format = ' markdown'
subjid
Tmax
Cmax
AUC
Half_life
CL
V
Ka
Ke
1
2.9003970
12.734147
169.58615
6.895391
1.1793416
11.73452
0.8272927
0.1005019
2
1.5941340
16.584026
224.44514
8.196288
0.8910863
10.53911
2.0995056
0.0845505
3
1.7302444
11.044962
88.01492
4.131165
2.2723420
13.54606
1.3897981
0.1677493
4
0.4804426
11.266602
96.16397
5.571876
2.0797811
16.72191
9.0472181
0.1243746
5
1.0591154
8.077437
52.87396
3.725028
3.7825806
20.33221
2.7180825
0.1860389
6
0.2847157
12.728310
65.24625
3.349133
3.0653101
14.81404
15.3275430
0.2069192
MyConcTime <- caffConcTime(Weight = 20 , Dose = 200 , N = 20 )
knitr :: kable(head(MyConcTime ), format = ' markdown'
Subject
Time
Conc
1
0.0
0.00000
1
0.1
17.66372
1
0.2
19.40917
1
0.3
19.37823
1
0.4
19.15167
1
0.5
18.90612
cowplot package is required
# install.packages("cowplot") # if you don't have itcowplot )
MyPlotPub <- lapply(
c(seq(100 , 800 , by = 100 )),
function (x ) caffPlotMulti(caffConcTime(20 , x , 20 )) +
theme(legend.position = " none" +
labs(title = paste0(" Single Dose " x , " mg" MyPlotPub [[1 ]], MyPlotPub [[2 ]],
MyPlotPub [[3 ]], MyPlotPub [[4 ]],
MyPlotPub [[5 ]], MyPlotPub [[6 ]],
MyPlotPub [[7 ]], MyPlotPub [[8 ]],
labels = LETTERS [1 : 8 ], ncol = 2 , nrow = 4 )
MyDatasetMulti <- caffPkparamMulti(Weight = 20 , Dose = 200 , N = 20 , Tau = 12 )
knitr :: kable(head(MyDatasetMulti ), format = ' markdown'
subjid
TmaxS
CmaxS
AUCS
AI
Aavss
Cavss
Cmaxss
Cminss
1
1.6342263
16.124255
323.02779
2.081215
304.77046
26.918982
36.68836
19.060022
2
0.2280164
11.513295
92.47913
1.273485
129.74616
7.706594
15.09689
3.242108
3
0.5284876
11.809599
82.99510
1.185982
107.72745
6.916258
15.19668
2.383098
4
0.6356576
20.062061
312.47832
1.810135
248.25251
26.039860
37.89499
16.960094
5
0.9068711
9.236732
55.60042
1.101123
83.58654
4.633368
12.18209
1.118752
6
1.7245049
11.479680
136.29292
1.430291
166.15773
11.357743
19.51289
5.870285
MyConcTimeMulti <- caffConcTimeMulti(Weight = 20 , Dose = 200 , N = 20 , Tau = 12 , Repeat = 10 )
knitr :: kable(head(MyConcTimeMulti ), format = ' markdown'
Subject
Time
Conc
1
0.0
0.000000
1
0.1
5.744079
1
0.2
9.105649
1
0.3
11.044072
1
0.4
12.132754
1
0.5
12.714412
caffPlotMulti(MyConcTimeMulti )
cowplot package is required
# install.packages("cowplot") # if you don't have itcowplot )
MyPlotMultiPub <- lapply(
c(seq(4 , 32 , by = 4 )),
function (x ) caffPlotMulti(caffConcTimeMulti(20 , 250 , 20 , x , 15 )) +
theme(legend.position = " none" +
labs(title = paste0(" q" x , " hr" MyPlotMultiPub [[1 ]], MyPlotMultiPub [[2 ]],
MyPlotMultiPub [[3 ]], MyPlotMultiPub [[4 ]],
MyPlotMultiPub [[5 ]], MyPlotMultiPub [[6 ]],
MyPlotMultiPub [[7 ]], MyPlotMultiPub [[8 ]],
labels = LETTERS [1 : 8 ], ncol = 2 , nrow = 4 )
