# Selection of Calculation Intervals

#### Bill Denney

# Introduction

PKNCA considers two types of data grouping within data sets: the group and the interval. A group typically identifies a single subject given a single intervention type (a “treatment”) with a single analyte. An interval subsets a group by times within the group, and primary noncompartmental analysis (NCA) calculations are performed within an interval.

As a concrete example, consider the figure below shows the concentration-time profile of a study subject in a multiple-dose study. The group is all points in the figure, and the interval for the last day (144 to 168 hr) is the area with blue shading.

    ## Formula for concentration:
    ##  conc ~ time | treatment + ID
    ## Data are dense PK.
    ## With 1 subjects defined in the 'ID' column.
    ## Nominal time column is not specified.
    ##
    ## First 6 rows of concentration data:
    ##    study treatment ID time      conc   analyte exclude volume duration
    ##  Study 1     Trt 1  1    0 0.0000000 Analyte 1    <NA>     NA        0
    ##  Study 1     Trt 1  1    1 0.6140526 Analyte 1    <NA>     NA        0
    ##  Study 1     Trt 1  1    2 0.8100022 Analyte 1    <NA>     NA        0
    ##  Study 1     Trt 1  1    4 0.8425422 Analyte 1    <NA>     NA        0
    ##  Study 1     Trt 1  1    6 0.7771994 Analyte 1    <NA>     NA        0
    ##  Study 1     Trt 1  1    8 0.7052469 Analyte 1    <NA>     NA        0

    # Plot the concentration-time data and the interval
    ggplot(d_conc_multi, aes(x=time, y=conc)) +
      geom_ribbon(data=d_conc_multi[d_conc_multi$time >= 144,],
                  aes(ymax=conc, ymin=0),
                  fill="skyblue") +
      geom_point() + geom_line() +
      scale_x_continuous(breaks=seq(0, 168, by=12)) +
      scale_y_continuous(limits=c(0, NA)) +
      labs(x="Time Since First Dose (hr)",
           y="Concentration\n(arbitrary units)")

    intervals_manual <- data.frame(start=144, end=168, auclast=TRUE)
    knitr::kable(intervals_manual)

start | end | auclast
--- | --- | ---
144 | 168 | TRUE

    PKNCAdata(d_conc, intervals=intervals_manual)

    ## Formula for concentration:
    ##  conc ~ time | treatment + ID
    ## Data are dense PK.
    ## With 1 subjects defined in the 'ID' column.
    ## Nominal time column is not specified.
    ##
    ## First 6 rows of concentration data:
    ##    study treatment ID time      conc   analyte exclude volume duration
    ##  Study 1     Trt 1  1    0 0.0000000 Analyte 1    <NA>     NA        0
    ##  Study 1     Trt 1  1    1 0.6140526 Analyte 1    <NA>     NA        0
    ##  Study 1     Trt 1  1    2 0.8100022 Analyte 1    <NA>     NA        0
    ##  Study 1     Trt 1  1    4 0.8425422 Analyte 1    <NA>     NA        0
    ##  Study 1     Trt 1  1    6 0.7771994 Analyte 1    <NA>     NA        0
    ##  Study 1     Trt 1  1    8 0.7052469 Analyte 1    <NA>     NA        0
    ## No dosing information.
    ##
    ## With 1 rows of interval specifications.
    ## With imputation: NA
    ## No options are set differently than default.

# Group Matching

Group matching occurs by matching all overlapping column names between the groups and the interval data.frame. (Note that grouping columns cannot be the word `start`, `end`, or share a name with an NCA parameter.)

## Selecting the Subjects for an Interval

The groups for an interval prepare for summarization. Typically the groups will take a structure similar to the preferred summarization structure with groups nested in the logical method for summary. As an example, the group structure may be: study, treatment, day, analyte, and subject. The grouping names for an interval must be the same as or a subset of the grouping names used for the concentration data.

As the matching occurs with all available columns, the grouping columns names are only required to the level of specificity for the calculations desired. As an example, if you want AUCinf,obs in subjects who received single doses and AUClast on days 1 (0 to 24 hours) and 10 (216 to 240 hours) in subjects who received multiple doses, with treatment defined as “Drug 1 Single” or “Drug 1 Multiple”, the intervals could be defined as below.

    intervals_manual <-
      data.frame(
        treatment=c("Drug 1 Single", "Drug 1 Multiple", "Drug 1 Multiple"),
        start=c(0, 0, 216),
        end=c(Inf, 24, 240),
        aucinf.obs=c(TRUE, FALSE, FALSE),
        auclast=c(FALSE, TRUE, TRUE)
      )
    knitr::kable(intervals_manual)

treatment | start | end | aucinf.obs | auclast
--- | --- | --- | --- | ---
Drug 1 Single | 0 | Inf | TRUE | FALSE
Drug 1 Multiple | 0 | 24 | FALSE | TRUE
Drug 1 Multiple | 216 | 240 | FALSE | TRUE

# Intervals

Intervals are defined by `data.frame`s with one row per interval, zero or more columns to match the groups from the `PKNCAdata` object, and one or more NCA parameters to calculate.

Selection of points within an interval occurs by choosing any point at or after the `start` and at or before the `end`.

## To Infinity

The end of an interval may be infinity. An interval to infinity works the same as any other interval in that points are selected by being at or after the `start` and at or before the `end` of the interval. Selecting `Inf` or any value at or after the maximum time yields no difference in effect, but `Inf` is simpler when scripting to ensure that all points are selected.

    ## Formula for concentration:
    ##  conc ~ time | treatment + ID
    ## Data are dense PK.
    ## With 1 subjects defined in the 'ID' column.
    ## Nominal time column is not specified.
    ##
    ## First 6 rows of concentration data:
    ##    study treatment ID time      conc   analyte exclude volume duration
    ##  Study 1     Trt 1  1    0 0.0000000 Analyte 1    <NA>     NA        0
    ##  Study 1     Trt 1  1    1 0.6140526 Analyte 1    <NA>     NA        0
    ##  Study 1     Trt 1  1    2 0.8100022 Analyte 1    <NA>     NA        0
    ##  Study 1     Trt 1  1    4 0.8425422 Analyte 1    <NA>     NA        0
    ##  Study 1     Trt 1  1    6 0.7771994 Analyte 1    <NA>     NA        0
    ##  Study 1     Trt 1  1    8 0.7052469 Analyte 1    <NA>     NA        0

    # Use superposition to simulate multiple doses
    ggplot(as.data.frame(d_conc)[as.data.frame(d_conc)$time <= 48,], aes(x=time, y=conc)) +
      geom_ribbon(data=as.data.frame(d_conc),
                  aes(ymax=conc, ymin=0),
                  fill="skyblue") +
      geom_point() + geom_line() +
      scale_x_continuous(breaks=seq(0, 72, by=12)) +
      scale_y_continuous(limits=c(0, NA)) +
      labs(x="Time Since First Dose (hr)",
           y="Concentration\n(arbitrary units)")

    intervals_manual <-
      data.frame(
        start=0,
        end=Inf,
        auclast=TRUE,
        aucinf.obs=TRUE
      )
    print(intervals_manual)

    ##   start end auclast aucinf.obs
    ## 1     0 Inf    TRUE       TRUE

    my.data <- PKNCAdata(d_conc, intervals=intervals_manual)

## Multiple Intervals

More than one interval may be specified for the same subject or group of subjects by providing more than one row of interval specifications. In the figure below, the blue and green shaded regions indicate the first and second rows of the intervals, respectively.

    ## Formula for concentration:
    ##  conc ~ time | treatment + ID
    ## Data are dense PK.
    ## With 1 subjects defined in the 'ID' column.
    ## Nominal time column is not specified.
    ##
    ## First 6 rows of concentration data:
    ##    study treatment ID time      conc   analyte exclude volume duration
    ##  Study 1     Trt 1  1    0 0.0000000 Analyte 1    <NA>     NA        0
    ##  Study 1     Trt 1  1    1 0.6140526 Analyte 1    <NA>     NA        0
    ##  Study 1     Trt 1  1    2 0.8100022 Analyte 1    <NA>     NA        0
    ##  Study 1     Trt 1  1    4 0.8425422 Analyte 1    <NA>     NA        0
    ##  Study 1     Trt 1  1    6 0.7771994 Analyte 1    <NA>     NA        0
    ##  Study 1     Trt 1  1    8 0.7052469 Analyte 1    <NA>     NA        0

    # Plot the concentration-time data and the interval
    ggplot(d_conc_multi, aes(x=time, y=conc)) +
      geom_ribbon(data=d_conc_multi[d_conc_multi$time <= 24,],
                  aes(ymax=conc, ymin=0),
                  fill="skyblue") +
      geom_ribbon(data=d_conc_multi[d_conc_multi$time >= 144,],
                  aes(ymax=conc, ymin=0),
                  fill="lightgreen") +
      geom_point() + geom_line() +
      scale_x_continuous(breaks=seq(0, 168, by=12)) +
      scale_y_continuous(limits=c(0, NA)) +
      labs(x="Time Since First Dose (hr)",
           y="Concentration\n(arbitrary units)")

    intervals_manual <-
      data.frame(
        start=c(0, 144),
        end=c(24, 168),
        auclast=TRUE
      )
    knitr::kable(intervals_manual)

start | end | auclast
--- | --- | ---
0 | 24 | TRUE
144 | 168 | TRUE

    my.data <- PKNCAdata(d_conc, intervals=intervals_manual)

# Overlapping Intervals and Different Calculations by Interval

In some scenarios, multiple intervals may be needed where some intervals overlap. There is no issue with an interval specification that has two rows with overlapping times; the rows are considered separately. In the example below, the 0-24 interval is shared between both the first and second (shaded blue-green).

The example of overlapping intervals also illustrates that different calculations can be performed in different intervals. In this case, `auclast` is calculated in both intervals while `aucinf.obs` is only calculated in the 0-Inf interval.

    ## Formula for concentration:
    ##  conc ~ time | treatment + ID
    ## Data are dense PK.
    ## With 1 subjects defined in the 'ID' column.
    ## Nominal time column is not specified.
    ##
    ## First 6 rows of concentration data:
    ##    study treatment ID time      conc   analyte exclude volume duration
    ##  Study 1     Trt 1  1    0 0.0000000 Analyte 1    <NA>     NA        0
    ##  Study 1     Trt 1  1    1 0.6140526 Analyte 1    <NA>     NA        0
    ##  Study 1     Trt 1  1    2 0.8100022 Analyte 1    <NA>     NA        0
    ##  Study 1     Trt 1  1    4 0.8425422 Analyte 1    <NA>     NA        0
    ##  Study 1     Trt 1  1    6 0.7771994 Analyte 1    <NA>     NA        0
    ##  Study 1     Trt 1  1    8 0.7052469 Analyte 1    <NA>     NA        0

    # Use superposition to simulate multiple doses
    ggplot(as.data.frame(d_conc), aes(x=time, y=conc)) +
      geom_ribbon(data=as.data.frame(d_conc),
                  aes(ymax=conc, ymin=0),
                  fill="lightgreen",
                  alpha=0.5) +
      geom_ribbon(data=as.data.frame(d_conc)[as.data.frame(d_conc)$time <= 24,],
                  aes(ymax=conc, ymin=0),
                  fill="skyblue",
                  alpha=0.5) +
      geom_point() + geom_line() +
      scale_x_continuous(breaks=seq(0, 168, by=12)) +
      scale_y_continuous(limits=c(0, NA)) +
      labs(x="Time Since First Dose (hr)",
           y="Concentration\n(arbitrary units)")

    intervals_manual <-
      data.frame(
        start=0,
        end=c(24, Inf),
        auclast=TRUE,
        aucinf.obs=c(FALSE, TRUE)
      )
    knitr::kable(intervals_manual)

start | end | auclast | aucinf.obs
--- | --- | --- | ---
0 | 24 | TRUE | FALSE
0 | Inf | TRUE | TRUE

    my.data <- PKNCAdata(d_conc, intervals=intervals_manual)

# Intervals with Duration

Some events have durations of times rather than instants in time associated with them. Two typical examples of duration data in NCA are intravenous infusions and urine or fecal sample collections. Inform PKNCA of durations with the `duration` argument to the `PKNCAdose` and `PKNCAconc` functions.

Durations data are selected based on both the beginning and ending of the duration existing within the interval.

# Parameters Available for Calculation in an Interval

The following parameters are available in an interval. For more information about the parameter, see the documentation for the function.

Parameter Name | Unit Type | Parameter Description | Function for Calculation
--- | --- | --- | ---
adj.r.squared | unitless | The adjusted r^2 value of the half-life calculation | See the parameter name half.life
ae | amount | The amount excreted (typically into urine or feces) | pk.calc.ae
aucabove.predose.all | auc | The area under the concentration time the beginning of the interval to the last concentration above the limit of quantification plus the triangle from that last concentration to 0 at the first concentration below the limit of quantification, with a concentration subtracted from all concentrations and values below zero after subtraction set to zero | pk.calc.aucabove
aucabove.trough.all | auc | The area under the concentration time the beginning of the interval to the last concentration above the limit of quantification plus the triangle from that last concentration to 0 at the first concentration below the limit of quantification, with a concentration subtracted from all concentrations and values below zero after subtraction set to zero | pk.calc.aucabove
aucall | auc | The area under the concentration time curve from the beginning of the interval to the last concentration above the limit of quantification plus the triangle from that last concentration to 0 at the first concentration below the limit of quantification | pk.calc.auc.all
aucall.dn | auc_dosenorm | Dose normalized aucall | pk.calc.dn
aucinf.obs | auc | The area under the concentration time curve from the beginning of the interval to infinity with extrapolation to infinity from the observed Clast | pk.calc.auc.inf.obs
aucinf.obs.dn | auc_dosenorm | Dose normalized aucinf.obs | pk.calc.dn
aucinf.pred | auc | The area under the concentration time curve from the beginning of the interval to infinity with extrapolation to infinity from the predicted Clast | pk.calc.auc.inf.pred
aucinf.pred.dn | auc_dosenorm | Dose normalized aucinf.pred | pk.calc.dn
aucint.all | auc | The area under the concentration time curve in the interval extrapolating from Tlast to infinity with the triangle from Tlast to the next point and zero thereafter (matching AUCall) | pk.calc.aucint.all
aucint.all.dose | auc | The area under the concentration time curve in the interval extrapolating from Tlast to infinity with the triangle from Tlast to the next point and zero thereafter (matching AUCall) with dose-aware interpolation/extrapolation of concentrations | pk.calc.aucint.all
aucint.inf.obs | auc | The area under the concentration time curve in the interval extrapolating from Tlast to infinity with zeros (matching AUClast) | pk.calc.aucint.inf.obs
aucint.inf.obs.dose | auc | The area under the concentration time curve in the interval extrapolating from Tlast to infinity with zeros (matching AUClast) with dose-aware interpolation/extrapolation of concentrations | pk.calc.aucint.inf.obs
aucint.inf.pred | auc | The area under the concentration time curve in the interval extrapolating from Tlast to infinity with the triangle from Tlast to the next point and zero thereafter (matching AUCall) | pk.calc.aucint.inf.pred
aucint.inf.pred.dose | auc | The area under the concentration time curve in the interval extrapolating from Tlast to infinity with the triangle from Tlast to the next point and zero thereafter (matching AUCall) with dose-aware interpolation/extrapolation of concentrations | pk.calc.aucint.inf.pred
aucint.last | auc | The area under the concentration time curve in the interval extrapolating from Tlast to infinity with zeros (matching AUClast) | pk.calc.aucint.last
aucint.last.dose | auc | The area under the concentration time curve in the interval extrapolating from Tlast to infinity with zeros (matching AUClast) with dose-aware interpolation/extrapolation of concentrations | pk.calc.aucint.last
aucivall | auc | The AUCall calculated with back-extrapolation for intravenous dosing using extrapolated C0 | pk.calc.auciv
aucivinf.obs | auc | The AUCinf,obs calculated with back-extrapolation for intravenous dosing using extrapolated C0 | pk.calc.auciv
aucivinf.pred | auc | The calculated with back-extrapolation for intravenous dosing using extrapolated C0 | pk.calc.auciv
aucivint.all | auc | The AUCint,all calculated with back-extrapolation for intravenous dosing using extrapolated C0 | pk.calc.auciv
aucivint.last | auc | The AUCint,last calculated with back-extrapolation for intravenous dosing using extrapolated C0 | pk.calc.auciv
aucivlast | auc | The AUClast calculated with back-extrapolation for intravenous dosing using extrapolated C0 | pk.calc.auciv
aucivpbextall | % | The back-extrapolation percent for intravenous dosing based on AUCall | pk.calc.auciv_pbext
aucivpbextinf.obs | % | The back-extrapolation percent for intravenous dosing based on AUCinf,obs | pk.calc.auciv_pbext
aucivpbextinf.pred | % | The back-extrapolation percent for intravenous dosing based on AUCinf,pred | pk.calc.auciv_pbext
aucivpbextint.all | % | The back-extrapolation percent for intravenous dosing based on AUCint,all | pk.calc.auciv_pbext
aucivpbextint.last | % | The back-extrapolation percent for intravenous dosing based on AUCint,last | pk.calc.auciv_pbext
aucivpbextlast | % | The back-extrapolation percent for intravenous dosing based on AUClast | pk.calc.auciv_pbext
auclast | auc | The area under the concentration time curve from the beginning of the interval to the last concentration above the limit of quantification | pk.calc.auc.last
auclast.dn | auc_dosenorm | Dose normalized auclast | pk.calc.dn
aucpext.obs | % | Percent of the AUCinf that is extrapolated after Tlast calculated from the observed Clast | pk.calc.aucpext
aucpext.pred | % | Percent of the AUCinf that is extrapolated after Tlast calculated from the predicted Clast | pk.calc.aucpext
aumcall | aumc | The area under the concentration time moment curve from the beginning of the interval to the last concentration above the limit of quantification plus the moment of the triangle from that last concentration to 0 at the first concentration below the limit of quantification | pk.calc.aumc.all
aumcall.dn | aumc_dosenorm | Dose normalized aumcall | pk.calc.dn
aumcinf.obs | aumc | The area under the concentration time moment curve from the beginning of the interval to infinity with extrapolation to infinity from the observed Clast | pk.calc.aumc.inf.obs
aumcinf.obs.dn | aumc_dosenorm | Dose normalized aumcinf.obs | pk.calc.dn
aumcinf.pred | aumc | The area under the concentration time moment curve from the beginning of the interval to infinity with extrapolation to infinity from the predicted Clast | pk.calc.aumc.inf.pred
aumcinf.pred.dn | aumc_dosenorm | Dose normalized aumcinf.pred | pk.calc.dn
aumclast | aumc | The area under the concentration time moment curve from the beginning of the interval to the last concentration above the limit of quantification | pk.calc.aumc.last
aumclast.dn | aumc_dosenorm | Dose normalized aumclast | pk.calc.dn
c0 | conc | Initial concentration after an IV bolus | pk.calc.c0
cav | conc | The average concentration during an interval (calculated with AUClast) | pk.calc.cav
cav.dn | conc_dosenorm | Dose normalized cav | pk.calc.dn
cav.int.all | conc | The average concentration during an interval (calculated with AUCint.all) | pk.calc.cav
cav.int.inf.obs | conc | The average concentration during an interval (calculated with AUCint.inf.obs) | pk.calc.cav
cav.int.inf.pred | conc | The average concentration during an interval (calculated with AUCint.inf.pred) | pk.calc.cav
cav.int.last | conc | The average concentration during an interval (calculated with AUCint.last) | pk.calc.cav
ceoi | conc | Concentration at the end of infusion | pk.calc.ceoi
cl.all | clearance | Clearance or observed oral clearance calculated with AUCall | pk.calc.cl
cl.last | clearance | Clearance or observed oral clearance calculated to Clast | pk.calc.cl
cl.obs | clearance | Clearance or observed oral clearance calculated with observed Clast | pk.calc.cl
cl.pred | clearance | Clearance or observed oral clearance calculated with predicted Clast | pk.calc.cl
clast.obs | conc | The last concentration observed above the limit of quantification | pk.calc.clast.obs
clast.obs.dn | conc_dosenorm | Dose normalized clast.obs | pk.calc.dn
clast.pred | conc | The concentration at Tlast as predicted by the half-life | See the parameter name half.life
clast.pred.dn | conc_dosenorm | Dose normalized clast.pred | pk.calc.dn
clr.last | renal_clearance | The renal clearance calculated using AUClast | pk.calc.clr
clr.obs | renal_clearance | The renal clearance calculated using AUCinf,obs | pk.calc.clr
clr.pred | renal_clearance | The renal clearance calculated using AUCinf,pred | pk.calc.clr
cmax | conc | Maximum observed concentration | pk.calc.cmax
cmax.dn | conc_dosenorm | Dose normalized cmax | pk.calc.dn
cmin | conc | Minimum observed concentration | pk.calc.cmin
cmin.dn | conc_dosenorm | Dose normalized cmin | pk.calc.dn
count_conc | count | Number of non-missing concentrations for an interval | pk.calc.count_conc
count_conc_measured | count | Number of measured and non BLQ/ALQ concentrations for an interval | pk.calc.count_conc_measured
cstart | conc | The predose concentration | pk.calc.cstart
ctrough | conc | The trough (end of interval) concentration | pk.calc.ctrough
ctrough.dn | conc_dosenorm | Dose normalized ctrough | pk.calc.dn
deg.fluc | % | Degree of fluctuation | pk.calc.deg.fluc
end | time | Ending time of the interval (potentially infinity) | (none)
f | fraction | Bioavailability or relative bioavailability | pk.calc.f
fe | amount_dose | The fraction of the dose excreted | pk.calc.fe
half.life | time | The (terminal) half-life | pk.calc.half.life
kel.iv.last | inverse_time | Elimination rate (as calculated from the intravenous MRTlast) | pk.calc.kel
kel.iv.obs | inverse_time | Elimination rate (as calculated from the intravenous MRTobs) | pk.calc.kel
kel.iv.pred | inverse_time | Elimination rate (as calculated from the intravenous MRTpred) | pk.calc.kel
kel.last | inverse_time | Elimination rate (as calculated from the MRT using AUClast) | pk.calc.kel
kel.obs | inverse_time | Elimination rate (as calculated from the MRT with observed Clast) | pk.calc.kel
kel.pred | inverse_time | Elimination rate (as calculated from the MRT with predicted Clast) | pk.calc.kel
lambda.z | inverse_time | The elimination rate of the terminal half-life | See the parameter name half.life
lambda.z.n.points | count | The number of points used for the calculation of half-life | See the parameter name half.life
lambda.z.time.first | time | The first time point used for the calculation of half-life | See the parameter name half.life
lambda.z.time.last | time | The last time point used for the calculation of half-life | See the parameter name half.life
mrt.iv.last | time | The mean residence time to the last observed concentration above the LOQ correcting for dosing duration | pk.calc.mrt.iv
mrt.iv.obs | time | The mean residence time to infinity using observed Clast correcting for dosing duration | pk.calc.mrt.iv
mrt.iv.pred | time | The mean residence time to infinity using predicted Clast correcting for dosing duration | pk.calc.mrt.iv
mrt.last | time | The mean residence time to the last observed concentration above the LOQ | pk.calc.mrt
mrt.md.obs | time | The mean residence time with multiple dosing and nonlinear kinetics using observed Clast | pk.calc.mrt.md
mrt.md.pred | time | The mean residence time with multiple dosing and nonlinear kinetics using predicted Clast | pk.calc.mrt.md
mrt.obs | time | The mean residence time to infinity using observed Clast | pk.calc.mrt
mrt.pred | time | The mean residence time to infinity using predicted Clast | pk.calc.mrt
ptr | fraction | Peak-to-Trough ratio (fraction) | pk.calc.ptr
r.squared | unitless | The r^2 value of the half-life calculation | See the parameter name half.life
span.ratio | fraction | The ratio of the half-life to the duration used for half-life calculation | See the parameter name half.life
sparse_auc_df | count | For sparse PK sampling, the standard error degrees of freedom of the area under the concentration time curve from the beginning of the interval to the last concentration above the limit of quantification | See the parameter name sparse_auclast
sparse_auc_se | auc | For sparse PK sampling, the standard error of the area under the concentration time curve from the beginning of the interval to the last concentration above the limit of quantification | See the parameter name sparse_auclast
sparse_auclast | auc | For sparse PK sampling, the area under the concentration time curve from the beginning of the interval to the last concentration above the limit of quantification | pk.calc.sparse_auclast
start | time | Starting time of the interval | (none)
swing | % | Swing relative to Cmin | pk.calc.swing
tfirst | time | Time of the first concentration above the limit of quantification | pk.calc.tfirst
thalf.eff.iv.last | time | The effective half-life (as determined from the intravenous MRTlast) | pk.calc.thalf.eff
thalf.eff.iv.obs | time | The effective half-life (as determined from the intravenous MRTobs) | pk.calc.thalf.eff
thalf.eff.iv.pred | time | The effective half-life (as determined from the intravenous MRTpred) | pk.calc.thalf.eff
thalf.eff.last | time | The effective half-life (as determined from the MRTlast) | pk.calc.thalf.eff
thalf.eff.obs | time | The effective half-life (as determined from the MRTobs) | pk.calc.thalf.eff
thalf.eff.pred | time | The effective half-life (as determined from the MRTpred) | pk.calc.thalf.eff
time_above | time | Time above a given concentration | pk.calc.time_above
tlag | time | Lag time | pk.calc.tlag
tlast | time | Time of the last concentration observed above the limit of quantification | pk.calc.tlast
tmax | time | Time of the maximum observed concentration | pk.calc.tmax
totdose | dose | Total dose administered during an interval | pk.calc.totdose
vss.iv.last | volume | The steady-state volume of distribution with intravenous infusion calculating through Tlast | pk.calc.vss
vss.iv.obs | volume | The steady-state volume of distribution with intravenous infusion using observed Clast | pk.calc.vss
vss.iv.pred | volume | The steady-state volume of distribution with intravenous infusion using predicted Clast | pk.calc.vss
vss.last | volume | The steady-state volume of distribution calculating through Tlast | pk.calc.vss
vss.md.obs | volume | The steady-state volume of distribution for nonlinear multiple-dose data using observed Clast | pk.calc.vss
vss.md.pred | volume | The steady-state volume of distribution for nonlinear multiple-dose data using predicted Clast | pk.calc.vss
vss.obs | volume | The steady-state volume of distribution using observed Clast | pk.calc.vss
vss.pred | volume | The steady-state volume of distribution using predicted Clast | pk.calc.vss
vz.obs | volume | The terminal volume of distribution using observed Clast | pk.calc.vz
vz.pred | volume | The terminal volume of distribution using predicted Clast | pk.calc.vz