Examples simplify understanding. Below is an example of how to use the theophylline dataset to generate NCA parameters.
Load the data
## It is always a good idea to look at the data
knitr::kable(head(datasets::Theoph))
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79.6 |
4.02 |
0.00 |
0.74 |
1 |
79.6 |
4.02 |
0.25 |
2.84 |
1 |
79.6 |
4.02 |
0.57 |
6.57 |
1 |
79.6 |
4.02 |
1.12 |
10.50 |
1 |
79.6 |
4.02 |
2.02 |
9.66 |
1 |
79.6 |
4.02 |
3.82 |
8.58 |
The columns that we will be interested in for our analysis are conc, Time, and Subject in the concentration data set and Dose, Time, and Subject for the dosing data set.
## By default it is groupedData; convert it to a data frame for use
my.conc <- PKNCAconc(as.data.frame(datasets::Theoph), conc~Time|Subject)
## Dosing data needs to only have one row per dose, so subset for
## that first.
d.dose <- unique(datasets::Theoph[datasets::Theoph$Time == 0,
c("Dose", "Time", "Subject")])
knitr::kable(d.dose,
caption="Example dosing data extracted from theophylline data set")
Example dosing data extracted from theophylline data set
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4.40 |
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4.53 |
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5.86 |
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67 |
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78 |
4.53 |
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89 |
3.10 |
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100 |
5.50 |
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111 |
4.92 |
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122 |
5.30 |
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12 |
my.dose <- PKNCAdose(d.dose, Dose~Time|Subject)
## Assuming route of administration is extravascular
## Assuming instant dosing (duration=0)
Merge the Concentration and Dose
After loading the data, they must be combined to prepare for parameter calculation. Intervals for calculation will automatically be selected based on the single.dose.aucs setting
in PKNCA.options
my.data.automatic <- PKNCAdata(my.conc, my.dose)
knitr::kable(PKNCA.options("single.dose.aucs"))
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knitr::kable(my.data.automatic$intervals)
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12 |
Intervals for calculation can also be specified manually. Manual specification requires at least columns for start
time, end
time, and the parameters requested. The manual specification can also include any grouping factors from the concentration data set. Column order of the intervals is not important. When intervals are manually specified, they are expanded to the full interval set when added to a PKNCAdata object (in other words, a column is created for each parameter. Also, PKNCA automatically calculates parameters required for the NCA, so while lambda.z is required for calculating AUC0-\(\infinity\), you do not have to specify it in the parameters requested.
my.intervals <- data.frame(start=0,
end=Inf,
cmax=TRUE,
tmax=TRUE,
aucinf.obs=TRUE,
auclast=TRUE)
my.data.manual <- PKNCAdata(my.conc, my.dose,
intervals=my.intervals)
knitr::kable(my.data.manual$intervals)
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Compute the parameters
Parameter calculation will automatically split the data by the grouping factor(s), subset by the interval, calculate all required parameters, record all options used for the calculations, and include data provenance to show that the calculation was performed as described. For all this, just call the pk.nca
function with your PKNCAdata object.
my.results.automatic <- pk.nca(my.data.automatic)
knitr::kable(head(my.results.automatic$result))
0 |
24 |
1 |
auclast |
92.365442 |
NA |
0 |
Inf |
1 |
cmax |
10.500000 |
NA |
0 |
Inf |
1 |
tmax |
1.120000 |
NA |
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Inf |
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tlast |
24.370000 |
NA |
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Inf |
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clast.obs |
3.280000 |
NA |
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Inf |
1 |
lambda.z |
0.048457 |
NA |
summary(my.results.automatic)
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12 |
74.6 [24.3] |
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8.65 [17.0] |
1.14 [0.630, 3.55] |
8.18 [2.12] |
115 [28.4] |
my.results.manual <- pk.nca(my.data.manual)
knitr::kable(head(my.results.manual$result))
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1 |
auclast |
147.234748 |
NA |
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1 |
cmax |
10.500000 |
NA |
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1 |
tmax |
1.120000 |
NA |
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tlast |
24.370000 |
NA |
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clast.obs |
3.280000 |
NA |
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1 |
lambda.z |
0.048457 |
NA |
summary(my.results.manual)
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12 |
98.7 [22.5] |
8.65 [17.0] |
1.14 [0.630, 3.55] |
115 [28.4] |