# A minimal interval: AUClast over the first 24 hours
my_intervals <- data.frame(
start = 0,
end = 24,
auclast = TRUE
)
my_intervals start end auclast
1 0 24 TRUE3 Interval Selection and Parameter Catalogue
Intervals tell PKNCA when to calculate and what to calculate. Every NCA parameter is associated with exactly one interval row, and each row is independent of all others.
3.1 1. The Interval Data Frame Structure
An interval specification is a plain R data.frame with one row per calculation window. Two columns are required:
| Column | Type | Meaning |
|---|---|---|
start |
numeric | Start of the calculation window (same units as time) |
end |
numeric | End of the calculation window; use Inf for open-ended windows |
Every remaining column is a parameter flag: its name must match a known PKNCA parameter name and its value must be TRUE (calculate) or FALSE (skip). Columns set to FALSE are simply ignored, so you only need to list the parameters you actually want.
You can also request multiple parameters in a single row:
data.frame(
start = 0,
end = Inf,
cmax = TRUE,
tmax = TRUE,
half.life = TRUE,
aucinf.obs = TRUE
) start end cmax tmax half.life aucinf.obs
1 0 Inf TRUE TRUE TRUE TRUEColumn names cannot overlap with start, end, or any grouping variable name you use in PKNCAconc().
3.2 2. Group Matching
PKNCA matches interval rows to concentration data by comparing the shared column names between the interval data frame and the grouping columns of the concentration object. Any column that appears in both is used as a matching key.
data("Theoph")
d_conc <- PKNCAconc(Theoph, conc ~ Time | Subject)
# Intervals with a Subject column — each row applies to exactly one subject
subject_intervals <- data.frame(
Subject = c("1", "2"),
start = c(0, 0),
end = c(24, 24),
auclast = TRUE
)
# Intervals without Subject — this row applies to ALL subjects (default interval)
default_interval <- data.frame(
start = 0,
end = 24,
auclast = TRUE
)If an interval row has no group columns, it is a default interval and is applied to every group present in the concentration data that does not have a more specific match. This is useful when the same calculation windows apply to all subjects and analytes.
3.3 3. Default Intervals via PKNCAdata() with No intervals Argument
When you call PKNCAdata() without an explicit intervals argument, PKNCA substitutes the built-in default single-dose intervals. These are stored in PKNCA.options("single.dose.aucs"):
PKNCA.options("single.dose.aucs") start end auclast aucall aumclast aumcall aucint.last aucint.last.dose
1 0 24 TRUE FALSE FALSE FALSE FALSE FALSE
2 0 Inf FALSE FALSE FALSE FALSE FALSE FALSE
aucint.all aucint.all.dose c0 cmax cmin tmax tmin tlast tfirst
1 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE TRUE FALSE TRUE FALSE FALSE FALSE
clast.obs cl.last cl.all f mrt.last mrt.iv.last vss.last vss.iv.last
1 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
cav cav.int.last cav.int.all ctrough cstart ptr tlag deg.fluc swing
1 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
ceoi aucabove.predose.all aucabove.trough.all count_conc count_conc_measured
1 FALSE FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE FALSE FALSE
totdose volpk ae clr.last clr.obs clr.pred fe ertlst ermax ertmax
1 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
sparse_auclast sparse_auc_se sparse_auc_df sparse_aumclast sparse_aumc_se
1 FALSE FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE FALSE FALSE
sparse_aumc_df time_above aucivlast aucivall aucivint.last aucivint.all
1 FALSE FALSE FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE FALSE FALSE FALSE
aucivpbextlast aucivpbextall aucivpbextint.last aucivpbextint.all half.life
1 FALSE FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE FALSE TRUE
r.squared adj.r.squared lambda.z.corrxy lambda.z lambda.z.time.first
1 FALSE FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE FALSE FALSE
lambda.z.time.last lambda.z.n.points clast.pred span.ratio tobit_residual
1 FALSE FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE FALSE FALSE
adj_tobit_residual lambda.z.n.points_blq thalf.eff.last thalf.eff.iv.last
1 FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE FALSE
kel.last kel.iv.last cl.sparse.last mrt.sparse.last vss.sparse.last
1 FALSE FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE FALSE FALSE
aucinf.obs aucinf.pred aumcinf.obs aumcinf.pred aucint.inf.obs
1 FALSE FALSE FALSE FALSE FALSE
2 TRUE FALSE FALSE FALSE FALSE
aucint.inf.obs.dose aucint.inf.pred aucint.inf.pred.dose aucivinf.obs
1 FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE FALSE
aucivinf.pred aucivpbextinf.obs aucivpbextinf.pred aucpext.obs aucpext.pred
1 FALSE FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE FALSE FALSE
kel.sparse.last cl.obs cl.pred mrt.obs mrt.pred mrt.iv.obs mrt.iv.pred
1 FALSE FALSE FALSE FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE FALSE FALSE FALSE FALSE
mrt.md.obs mrt.md.pred vz.obs vz.pred vz.sparse.last vss.obs vss.pred
1 FALSE FALSE FALSE FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE FALSE FALSE FALSE FALSE
vss.iv.obs vss.iv.pred vss.md.obs vss.md.pred cav.int.inf.obs
1 FALSE FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE FALSE FALSE
cav.int.inf.pred thalf.eff.obs thalf.eff.pred thalf.eff.iv.obs
1 FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE FALSE
thalf.eff.iv.pred kel.obs kel.pred kel.iv.obs kel.iv.pred auclast.dn
1 FALSE FALSE FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE FALSE FALSE FALSE
aucall.dn aucinf.obs.dn aucinf.pred.dn aumclast.dn aumcall.dn aumcinf.obs.dn
1 FALSE FALSE FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE FALSE FALSE FALSE
aumcinf.pred.dn cmax.dn cmin.dn clast.obs.dn clast.pred.dn cav.dn ctrough.dn
1 FALSE FALSE FALSE FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE FALSE FALSE FALSE FALSE
clr.last.dn clr.obs.dn clr.pred.dn
1 FALSE FALSE FALSE
2 FALSE FALSE FALSEThe two default rows are:
- Row 1 (
end = 24): calculatesauclastonly — the workhorse for most single-dose studies. - Row 2 (
end = Inf): calculatescmax,tmax,half.life, andaucinf.obs.
These defaults are suitable for a single-dose extravascular study with at least 24 hours of sampling. For any other design (multiple dose, IV, urine, etc.) you should supply explicit intervals.
d_dose <- PKNCAdose(
Theoph |> group_by(Subject) |>
summarise(Dose = Dose[1] * Wt[1], .groups = "drop") |>
mutate(Time = 0),
Dose ~ Time | Subject
)
# No intervals argument — uses PKNCA.options("single.dose.aucs") automatically
d_data_default <- PKNCAdata(
PKNCAconc(Theoph, conc ~ Time | Subject),
d_dose
)
d_data_default$intervals# A tibble: 24 × 144
start end auclast aucall aumclast aumcall aucint.last aucint.last.dose
<dbl> <dbl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl>
1 0 24 TRUE FALSE FALSE FALSE FALSE FALSE
2 0 Inf FALSE FALSE FALSE FALSE FALSE FALSE
3 0 24 TRUE FALSE FALSE FALSE FALSE FALSE
4 0 Inf FALSE FALSE FALSE FALSE FALSE FALSE
5 0 24 TRUE FALSE FALSE FALSE FALSE FALSE
6 0 Inf FALSE FALSE FALSE FALSE FALSE FALSE
7 0 24 TRUE FALSE FALSE FALSE FALSE FALSE
8 0 Inf FALSE FALSE FALSE FALSE FALSE FALSE
9 0 24 TRUE FALSE FALSE FALSE FALSE FALSE
10 0 Inf FALSE FALSE FALSE FALSE FALSE FALSE
# ℹ 14 more rows
# ℹ 136 more variables: aucint.all <lgl>, aucint.all.dose <lgl>, c0 <lgl>,
# cmax <lgl>, cmin <lgl>, tmax <lgl>, tmin <lgl>, tlast <lgl>, tfirst <lgl>,
# clast.obs <lgl>, cl.last <lgl>, cl.all <lgl>, f <lgl>, mrt.last <lgl>,
# mrt.iv.last <lgl>, vss.last <lgl>, vss.iv.last <lgl>, cav <lgl>,
# cav.int.last <lgl>, cav.int.all <lgl>, ctrough <lgl>, cstart <lgl>,
# ptr <lgl>, tlag <lgl>, deg.fluc <lgl>, swing <lgl>, ceoi <lgl>, …3.4 4. Multiple Intervals per Group
Each row of the interval data frame is applied independently. A single subject (or group) can have any number of interval rows, each with its own time window and parameter set. PKNCA applies every matching row and collects the results.
# Two windows for the same subjects:
# 0–24 h for early exposure; 0–Inf for terminal parameters
multi_intervals <- data.frame(
start = c(0, 0),
end = c(24, Inf),
auclast = c(TRUE, FALSE),
cmax = c(FALSE, TRUE),
half.life = c(FALSE, TRUE),
aucinf.obs = c(FALSE, TRUE)
)
multi_intervals start end auclast cmax half.life aucinf.obs
1 0 24 TRUE FALSE FALSE FALSE
2 0 Inf FALSE TRUE TRUE TRUEPKNCA processes each row separately: the first row restricts data to \(t \in [0, 24]\) for the auclast calculation, while the second row uses all available data to derive terminal parameters.
Overlapping intervals are allowed and do not interfere with each other.
3.5 5. Duration-Based Events
Some sampling designs record a duration rather than an instantaneous sample — for example, urine collection periods or IV infusions. PKNCA tracks these via the duration argument in PKNCAconc() and PKNCAdose().
When a concentration object carries duration information, PKNCA selects samples for an interval based on both the start and end of the collection period. The collection end time must fall at or before the interval end for the sample to be included:
# Urine example: each row covers a collection period
urine_conc <- data.frame(
Subject = rep(1, 4),
Time = c(0, 4, 8, 24), # collection start times
duration = c(4, 4, 16, 0), # collection lengths (hours)
conc = c(0.5, 1.2, 0.9, 0.3)
)
d_urine_conc <- PKNCAconc(
urine_conc,
conc ~ Time | Subject,
duration = "duration"
)
# The interval end must align with a collection end time
urine_intervals <- data.frame(
start = 0,
end = 24, # matches the end of the 8-h collection (8 + 16 = 24)
ae = TRUE,
clr.last = TRUE
)For IV infusions, setDuration() on the dose object sets the infusion duration, and ceoi (concentration at end of infusion) becomes calculable within an interval whose end matches the infusion end time.
3.6 6. Full Parameter Catalogue
The complete list of calculable parameters is available programmatically via get.interval.cols(). Each entry carries a description, the calculation function, unit type, and dependency information.
cols <- get.interval.cols()
param_table <- data.frame(
parameter = names(cols),
description = sapply(cols, function(x) x$desc),
stringsAsFactors = FALSE
)
# Exclude the structural columns start/end from the display
param_table <- param_table[!param_table$parameter %in% c("start", "end"), ]
rownames(param_table) <- NULL
knitr::kable(
param_table,
col.names = c("Parameter", "Description"),
caption = paste0(
"All ", nrow(param_table),
" calculable parameters in PKNCA ", packageVersion("PKNCA")
)
)| Parameter | Description |
|---|---|
| auclast | The area under the concentration time curve from the beginning of the interval to the last concentration above the limit of quantification |
| aucall | 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 |
| aumclast | The area under the concentration time moment curve from the beginning of the interval to the last concentration above the limit of quantification |
| aumcall | 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 |
| aucint.last | The area under the concentration time curve in the interval extrapolating from Tlast to infinity with zeros (matching AUClast) |
| aucint.last.dose | 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 |
| aucint.all | 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) |
| aucint.all.dose | 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 |
| c0 | Initial concentration after an IV bolus |
| cmax | Maximum observed concentration |
| cmin | Minimum observed concentration |
| tmax | Time of the maximum observed concentration |
| tmin | Time of the minimum observed concentration |
| tlast | Time of the last concentration observed above the limit of quantification |
| tfirst | Time of the first concentration above the limit of quantification |
| clast.obs | The last concentration observed above the limit of quantification |
| cl.last | Clearance or observed oral clearance calculated to Clast |
| cl.all | Clearance or observed oral clearance calculated with AUCall |
| f | Bioavailability or relative bioavailability |
| mrt.last | The mean residence time to the last observed concentration above the LOQ |
| mrt.iv.last | The mean residence time to the last observed concentration above the LOQ correcting for dosing duration |
| vss.last | The steady-state volume of distribution calculating through Tlast |
| vss.iv.last | The steady-state volume of distribution with intravenous infusion calculating through Tlast |
| cav | The average concentration during an interval (calculated with AUClast) |
| cav.int.last | The average concentration during an interval (calculated with AUCint.last) |
| cav.int.all | The average concentration during an interval (calculated with AUCint.all) |
| ctrough | The trough (end of interval) concentration |
| cstart | The predose concentration |
| ptr | Peak-to-Trough ratio (fraction) |
| tlag | Lag time |
| deg.fluc | Degree of fluctuation |
| swing | Swing relative to Cmin |
| ceoi | Concentration at the end of infusion |
| aucabove.predose.all | 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 |
| aucabove.trough.all | 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 |
| count_conc | Number of non-missing concentrations for an interval |
| count_conc_measured | Number of measured and non BLQ/ALQ concentrations for an interval |
| totdose | Total dose administered during an interval |
| volpk | The sum of urine volumes for the interval |
| ae | The amount excreted (typically into urine or feces) |
| clr.last | The renal clearance calculated using AUClast |
| clr.obs | The renal clearance calculated using AUCinf,obs |
| clr.pred | The renal clearance calculated using AUCinf,pred |
| fe | The fraction of the dose excreted |
| ertlst | The midpoint collection time of the last measurable excretion rate (typically in urine or feces) |
| ermax | The maximum excretion rate (typically in urine or feces) |
| ertmax | The midpoint collection time of the maximum excretion rate (typically in urine or feces) |
| sparse_auclast | 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 |
| sparse_auc_se | 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 |
| sparse_auc_df | 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 |
| sparse_aumclast | For sparse PK sampling, the area under the moment curve from the beginning of the interval to the last concentration above the limit of quantification |
| sparse_aumc_se | For sparse PK sampling, the standard error of the area under the moment curve |
| sparse_aumc_df | For sparse PK sampling, the degrees of freedom for the AUMC variance estimate |
| time_above | Time above a given concentration |
| aucivlast | The AUClast calculated with back-extrapolation for intravenous dosing using extrapolated C0 |
| aucivall | The AUCall calculated with back-extrapolation for intravenous dosing using extrapolated C0 |
| aucivint.last | The AUCint,last calculated with back-extrapolation for intravenous dosing using extrapolated C0 |
| aucivint.all | The AUCint,all calculated with back-extrapolation for intravenous dosing using extrapolated C0 |
| aucivpbextlast | The back-extrapolation percent for intravenous dosing based on AUClast |
| aucivpbextall | The back-extrapolation percent for intravenous dosing based on AUCall |
| aucivpbextint.last | The back-extrapolation percent for intravenous dosing based on AUCint,last |
| aucivpbextint.all | The back-extrapolation percent for intravenous dosing based on AUCint,all |
| half.life | The (terminal) half-life |
| r.squared | The r^2 value of the half-life calculation |
| adj.r.squared | The adjusted r^2 value of the half-life calculation |
| lambda.z.corrxy | Correlation between time and log-concentration for lambda.z points |
| lambda.z | The elimination rate of the terminal half-life |
| lambda.z.time.first | The first time point used for the calculation of half-life |
| lambda.z.time.last | The last time point used for the calculation of half-life |
| lambda.z.n.points | The number of points used for the calculation of half-life |
| clast.pred | The concentration at Tlast as predicted by the half-life |
| span.ratio | The ratio of the half-life to the duration used for half-life calculation |
| tobit_residual | The estimated residual standard deviation (on the log-concentration scale) from the Tobit half-life fit |
| adj_tobit_residual | The adjusted Tobit residual standard deviation (analogous to adjusted r-squared; penalizes smaller windows) |
| lambda.z.n.points_blq | The number of BLQ points included in the Tobit half-life calculation |
| thalf.eff.last | The effective half-life (as determined from the MRTlast) |
| thalf.eff.iv.last | The effective half-life (as determined from the intravenous MRTlast) |
| kel.last | Elimination rate (as calculated from the MRT using AUClast) |
| kel.iv.last | Elimination rate (as calculated from the intravenous MRTlast) |
| cl.sparse.last | Clearance from sparse sampling calculated with population AUClast |
| mrt.sparse.last | Mean residence time from sparse sampling |
| vss.sparse.last | Steady-state volume of distribution from sparse sampling |
| aucinf.obs | The area under the concentration time curve from the beginning of the interval to infinity with extrapolation to infinity from the observed Clast |
| aucinf.pred | The area under the concentration time curve from the beginning of the interval to infinity with extrapolation to infinity from the predicted Clast |
| aumcinf.obs | The area under the concentration time moment curve from the beginning of the interval to infinity with extrapolation to infinity from the observed Clast |
| aumcinf.pred | The area under the concentration time moment curve from the beginning of the interval to infinity with extrapolation to infinity from the predicted Clast |
| aucint.inf.obs | The area under the concentration time curve in the interval extrapolating from Tlast to infinity with zeros (matching AUClast) |
| aucint.inf.obs.dose | 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 |
| aucint.inf.pred | 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) |
| aucint.inf.pred.dose | 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 |
| aucivinf.obs | The AUCinf,obs calculated with back-extrapolation for intravenous dosing using extrapolated C0 |
| aucivinf.pred | The AUCinf,pred calculated with back-extrapolation for intravenous dosing using extrapolated C0 |
| aucivpbextinf.obs | The back-extrapolation percent for intravenous dosing based on AUCinf,obs |
| aucivpbextinf.pred | The back-extrapolation percent for intravenous dosing based on AUCinf,pred |
| aucpext.obs | Percent of the AUCinf that is extrapolated after Tlast calculated from the observed Clast |
| aucpext.pred | Percent of the AUCinf that is extrapolated after Tlast calculated from the predicted Clast |
| kel.sparse.last | Elimination rate (as calculated from the MRTsparse.last) |
| cl.obs | Clearance or observed oral clearance calculated with observed Clast |
| cl.pred | Clearance or observed oral clearance calculated with predicted Clast |
| mrt.obs | The mean residence time to infinity using observed Clast |
| mrt.pred | The mean residence time to infinity using predicted Clast |
| mrt.iv.obs | The mean residence time to infinity using observed Clast correcting for dosing duration |
| mrt.iv.pred | The mean residence time to infinity using predicted Clast correcting for dosing duration |
| mrt.md.obs | The mean residence time with multiple dosing and nonlinear kinetics using observed Clast |
| mrt.md.pred | The mean residence time with multiple dosing and nonlinear kinetics using predicted Clast |
| vz.obs | The terminal volume of distribution using observed Clast |
| vz.pred | The terminal volume of distribution using predicted Clast |
| vz.sparse.last | Terminal volume of distribution from sparse sampling |
| vss.obs | The steady-state volume of distribution using observed Clast |
| vss.pred | The steady-state volume of distribution using predicted Clast |
| vss.iv.obs | The steady-state volume of distribution with intravenous infusion using observed Clast |
| vss.iv.pred | The steady-state volume of distribution with intravenous infusion using predicted Clast |
| vss.md.obs | The steady-state volume of distribution for nonlinear multiple-dose data using observed Clast |
| vss.md.pred | The steady-state volume of distribution for nonlinear multiple-dose data using predicted Clast |
| cav.int.inf.obs | The average concentration during an interval (calculated with AUCint.inf.obs) |
| cav.int.inf.pred | The average concentration during an interval (calculated with AUCint.inf.pred) |
| thalf.eff.obs | The effective half-life (as determined from the MRTobs) |
| thalf.eff.pred | The effective half-life (as determined from the MRTpred) |
| thalf.eff.iv.obs | The effective half-life (as determined from the intravenous MRTobs) |
| thalf.eff.iv.pred | The effective half-life (as determined from the intravenous MRTpred) |
| kel.obs | Elimination rate (as calculated from the MRT with observed Clast) |
| kel.pred | Elimination rate (as calculated from the MRT with predicted Clast) |
| kel.iv.obs | Elimination rate (as calculated from the intravenous MRTobs) |
| kel.iv.pred | Elimination rate (as calculated from the intravenous MRTpred) |
| auclast.dn | Dose normalized auclast |
| aucall.dn | Dose normalized aucall |
| aucinf.obs.dn | Dose normalized aucinf.obs |
| aucinf.pred.dn | Dose normalized aucinf.pred |
| aumclast.dn | Dose normalized aumclast |
| aumcall.dn | Dose normalized aumcall |
| aumcinf.obs.dn | Dose normalized aumcinf.obs |
| aumcinf.pred.dn | Dose normalized aumcinf.pred |
| cmax.dn | Dose normalized cmax |
| cmin.dn | Dose normalized cmin |
| clast.obs.dn | Dose normalized clast.obs |
| clast.pred.dn | Dose normalized clast.pred |
| cav.dn | Dose normalized cav |
| ctrough.dn | Dose normalized ctrough |
| clr.last.dn | Dose normalized clr.last |
| clr.obs.dn | Dose normalized clr.obs |
| clr.pred.dn | Dose normalized clr.pred |
Parameters fall into broad families:
- AUC / AUMC —
auclast,aucall,aucinf.obs,aucinf.pred,aumclast, and interval-restrictedaucint.*variants - Concentration —
cmax,cmin,ctrough,clast.obs,clast.pred,c0,cstart,ceoi - Time —
tmax,tlast,tfirst,tlag - Clearance / Volume —
cl.obs,cl.pred,vz.obs,vz.pred,vss.obs,vss.iv.obs, renalclr.* - Elimination —
half.life,lambda.z,lambda.z.n.points,span.ratio,r.squared,adj.r.squared - Excretion —
ae,fe - Steady-state / MD —
deg.fluc,swing,ptr,cav,mrt.*,thalf.eff.* - Sparse sampling —
sparse_auclast,sparse_auc_se,sparse_auc_df - IV-specific —
aucivlast,aucivpbext*,aucivinf.* - Dose-normalized —
auclast.dn,cmax.dn, and other*.dnvariants
3.7 7. Checking Parameter Dependencies with get.parameter.deps()
Some parameters depend on others being computed first. get.parameter.deps() returns all parameters that use a given parameter as an input:
# Which parameters depend on auclast?
get.parameter.deps("auclast") [1] "aucivlast" "aucivpbextlast" "auclast"
[4] "auclast.dn" "aucpext.obs" "aucpext.pred"
[7] "cav" "cav.dn" "cl.last"
[10] "deg.fluc" "kel.iv.last" "kel.last"
[13] "mrt.iv.last" "mrt.last" "mrt.md.obs"
[16] "mrt.md.pred" "thalf.eff.iv.last" "thalf.eff.last"
[19] "vss.iv.last" "vss.last" "vss.md.obs"
[22] "vss.md.pred" This is useful when you enable a high-level parameter and want to know which intermediate quantities will also be computed. Dependencies are resolved automatically — you do not need to set dependency flags to TRUE manually.
3.8 8. Validating Custom Intervals with check.interval.specification()
Before passing intervals to PKNCAdata(), you can validate them with check.interval.specification(). It verifies that all column names are recognized parameters, that start < end, and that logical values are used correctly.
# A valid interval
valid_int <- data.frame(
start = c(0, 0),
end = c(24, Inf),
auclast = c(TRUE, FALSE),
aucinf.obs = c(FALSE, TRUE),
cmax = c(FALSE, TRUE)
)
check.interval.specification(valid_int) start end auclast aucall aumclast aumcall aucint.last aucint.last.dose
1 0 24 TRUE FALSE FALSE FALSE FALSE FALSE
2 0 Inf FALSE FALSE FALSE FALSE FALSE FALSE
aucint.all aucint.all.dose c0 cmax cmin tmax tmin tlast tfirst
1 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE
clast.obs cl.last cl.all f mrt.last mrt.iv.last vss.last vss.iv.last
1 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
cav cav.int.last cav.int.all ctrough cstart ptr tlag deg.fluc swing
1 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
ceoi aucabove.predose.all aucabove.trough.all count_conc count_conc_measured
1 FALSE FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE FALSE FALSE
totdose volpk ae clr.last clr.obs clr.pred fe ertlst ermax ertmax
1 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
sparse_auclast sparse_auc_se sparse_auc_df sparse_aumclast sparse_aumc_se
1 FALSE FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE FALSE FALSE
sparse_aumc_df time_above aucivlast aucivall aucivint.last aucivint.all
1 FALSE FALSE FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE FALSE FALSE FALSE
aucivpbextlast aucivpbextall aucivpbextint.last aucivpbextint.all half.life
1 FALSE FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE FALSE FALSE
r.squared adj.r.squared lambda.z.corrxy lambda.z lambda.z.time.first
1 FALSE FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE FALSE FALSE
lambda.z.time.last lambda.z.n.points clast.pred span.ratio tobit_residual
1 FALSE FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE FALSE FALSE
adj_tobit_residual lambda.z.n.points_blq thalf.eff.last thalf.eff.iv.last
1 FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE FALSE
kel.last kel.iv.last cl.sparse.last mrt.sparse.last vss.sparse.last
1 FALSE FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE FALSE FALSE
aucinf.obs aucinf.pred aumcinf.obs aumcinf.pred aucint.inf.obs
1 FALSE FALSE FALSE FALSE FALSE
2 TRUE FALSE FALSE FALSE FALSE
aucint.inf.obs.dose aucint.inf.pred aucint.inf.pred.dose aucivinf.obs
1 FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE FALSE
aucivinf.pred aucivpbextinf.obs aucivpbextinf.pred aucpext.obs aucpext.pred
1 FALSE FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE FALSE FALSE
kel.sparse.last cl.obs cl.pred mrt.obs mrt.pred mrt.iv.obs mrt.iv.pred
1 FALSE FALSE FALSE FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE FALSE FALSE FALSE FALSE
mrt.md.obs mrt.md.pred vz.obs vz.pred vz.sparse.last vss.obs vss.pred
1 FALSE FALSE FALSE FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE FALSE FALSE FALSE FALSE
vss.iv.obs vss.iv.pred vss.md.obs vss.md.pred cav.int.inf.obs
1 FALSE FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE FALSE FALSE
cav.int.inf.pred thalf.eff.obs thalf.eff.pred thalf.eff.iv.obs
1 FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE FALSE
thalf.eff.iv.pred kel.obs kel.pred kel.iv.obs kel.iv.pred auclast.dn
1 FALSE FALSE FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE FALSE FALSE FALSE
aucall.dn aucinf.obs.dn aucinf.pred.dn aumclast.dn aumcall.dn aumcinf.obs.dn
1 FALSE FALSE FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE FALSE FALSE FALSE
aumcinf.pred.dn cmax.dn cmin.dn clast.obs.dn clast.pred.dn cav.dn ctrough.dn
1 FALSE FALSE FALSE FALSE FALSE FALSE FALSE
2 FALSE FALSE FALSE FALSE FALSE FALSE FALSE
clr.last.dn clr.obs.dn clr.pred.dn
1 FALSE FALSE FALSE
2 FALSE FALSE FALSE# An invalid interval — start >= end
bad_int <- data.frame(
start = 24,
end = 0,
auclast = TRUE
)
check.interval.specification(bad_int)Error in `check.interval.specification()`:
! start must be < endcheck.interval.specification() returns the interval data frame invisibly on success, making it safe to use inline before passing to PKNCAdata():
d_conc <- PKNCAconc(Theoph, conc ~ Time | Subject)
d_dose <- PKNCAdose(
Theoph |> group_by(Subject) |>
summarise(Dose = Dose[1] * Wt[1], .groups = "drop") |>
mutate(Time = 0),
Dose ~ Time | Subject
)
my_intervals <- check.interval.specification(
data.frame(
start = c(0, 0),
end = c(24, Inf),
auclast = c(TRUE, FALSE),
aucinf.obs = c(FALSE, TRUE),
cmax = c(FALSE, TRUE),
half.life = c(FALSE, TRUE)
)
)
d_data <- PKNCAdata(d_conc, d_dose, intervals = my_intervals)
suppressMessages(o_nca <- pk.nca(d_data))
as.data.frame(o_nca) |> head(8)# A tibble: 8 × 6
Subject start end PPTESTCD PPORRES exclude
<ord> <dbl> <dbl> <chr> <dbl> <chr>
1 6 0 24 auclast 71.7 <NA>
2 6 0 Inf cmax 6.44 <NA>
3 6 0 Inf tmax 1.15 <NA>
4 6 0 Inf tlast 23.8 <NA>
5 6 0 Inf clast.obs 0.92 <NA>
6 6 0 Inf lambda.z 0.0878 <NA>
7 6 0 Inf r.squared 0.998 <NA>
8 6 0 Inf adj.r.squared 0.998 <NA>