Perform Pharmacokinetic Non-Compartmental Analysis

Documentation for package ‘PKNCA’ version 0.11.0

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Compute noncompartmental pharmacokinetics

-- A --

add.interval.col	Add columns for calculations within PKNCA intervals
addProvenance	Add a hash and associated information to enable checking object provenance.
adj.r.squared	Calculate the adjusted r-squared value
any_sparse_dense_in_interval	Determine if there are any sparse or dense calculations requested within an interval
as.data.frame.PKNCAresults	Extract the parameter results from a PKNCAresults and return them as a data.frame.
assert_aucmethod	Assert that a value is a valid AUC method
assert_conc	Verify that concentration measurements are valid
assert_conc_time	Verify that concentration measurements are valid
assert_dosetau	Assert that a value is a dosing interval
assert_intervaltime_single	Assert that an interval is accurately defined as an interval, and return the interval
assert_lambdaz	Assert that a lambda.z value is valid
assert_number_between	Confirm that a value is greater than another value
assert_numeric_between	Confirm that a value is greater than another value
assert_PKNCAdata	Assert that an object is a PKNCAdata object
assert_time	Verify that concentration measurements are valid
as_PKNCAconc	Convert an object into a PKNCAconc object
as_PKNCAdata	Convert an object into a PKNCAconc object
as_PKNCAdose	Convert an object into a PKNCAconc object
as_PKNCAresults	Convert an object into a PKNCAconc object
as_sparse_pk	Generate a sparse_pk object
auc_integrate	Support function for AUC integration

-- B --

business.cv	Generate functions to do the named function (e.g. mean) applying the business rules.
business.geocv	Generate functions to do the named function (e.g. mean) applying the business rules.
business.geomean	Generate functions to do the named function (e.g. mean) applying the business rules.
business.max	Generate functions to do the named function (e.g. mean) applying the business rules.
business.mean	Generate functions to do the named function (e.g. mean) applying the business rules.
business.median	Generate functions to do the named function (e.g. mean) applying the business rules.
business.min	Generate functions to do the named function (e.g. mean) applying the business rules.
business.range	Generate functions to do the named function (e.g. mean) applying the business rules.
business.sd	Generate functions to do the named function (e.g. mean) applying the business rules.

-- C --

check.conc.time	The following functions are defunct
check.conversion	Check that the conversion to a data type does not change the number of NA values
check.interval.deps	Take in a single row of an interval specification and return that row updated with any additional calculations that must be done to fulfill all dependencies.
check.interval.specification	Check the formatting of a calculation interval specification data frame.
checkProvenance	Check the hash of an object to confirm its provenance.
choose.auc.intervals	Choose intervals to compute AUCs from time and dosing information
choose_interval_method	Choose how to interpolate, extrapolate, or integrate data in each concentration interval
clean.conc.blq	Handle BLQ values in the concentration measurements as requested by the user.
clean.conc.na	Handle NA values in the concentration measurements as requested by the user.
cov_holder	Calculate the covariance for two time points with sparse sampling

-- D --

defunct

The following functions are defunct

-- E --

exclude	Exclude data points or results from calculations or summarization.
exclude.default	Exclude data points or results from calculations or summarization.
exclude_nca	Exclude NCA parameters based on examining the parameter set.
exclude_nca_max.aucinf.pext	Exclude NCA parameters based on examining the parameter set.
exclude_nca_min.hl.r.squared	Exclude NCA parameters based on examining the parameter set.
exclude_nca_span.ratio	Exclude NCA parameters based on examining the parameter set.
extrapolate.conc	Interpolate concentrations between measurements or extrapolate concentrations after the last measurement.
extrapolate_conc_lambdaz	Interpolate or extrapolate concentrations using the provided method

-- F --

filter.PKNCAconc	dplyr filtering for PKNCA
filter.PKNCAdose	dplyr filtering for PKNCA
filter.PKNCAresults	dplyr filtering for PKNCA
find.tau	Find the repeating interval within a vector of doses
findOperator	Find the first occurrence of an operator in a formula and return the left, right, or both sides of the operator.
fit_half_life	Perform the half-life fit given the data. The function simply fits the data without any validation. No selection of points or any other components are done.
formula.PKNCAconc	Extract the formula from a PKNCAconc object.
formula.PKNCAdose	Extract the formula from a PKNCAconc object.
full_join.PKNCAconc	dplyr joins for PKNCA
full_join.PKNCAdose	dplyr joins for PKNCA
full_join.PKNCAresults	dplyr joins for PKNCA

-- G --

geocv	Compute the geometric mean, sd, and CV
geomean	Compute the geometric mean, sd, and CV
geosd	Compute the geometric mean, sd, and CV
get.best.model	Extract the best model from a list of models using the AIC.
get.first.model	Get the first model from a list of models
get.interval.cols	Get the columns that can be used in an interval specification
get.parameter.deps	Get all columns that depend on a parameter
getAttributeColumn	Retrieve the value of an attribute column.
getColumnValueOrNot	Get the value from a column in a data frame if the value is a column there, otherwise, the value should be a scalar or the length of the data.
getDataName	Get the name of the element containing the data for the current object.
getDataName.default	Get the name of the element containing the data for the current object.
getDataName.PKNCAconc	Get the name of the element containing the data for the current object.
getDataName.PKNCAdose	Get the name of the element containing the data for the current object.
getDataName.PKNCAresults	Get the name of the element containing the data for the current object.
getDepVar	Get the dependent variable (left hand side of the formula) from a PKNCA object.
getGroups.PKNCAconc	Get the groups (right hand side after the '\|' from a PKNCA object).
getGroups.PKNCAdose	Get the groups (right hand side after the '\|' from a PKNCA object).
getGroups.PKNCAresults	Get the groups (right hand side after the '\|' from a PKNCA object).
getIndepVar	Get the independent variable (right hand side of the formula) from a PKNCA object.
get_impute_method	Get the impute function from either the intervals column or from the method
group_by.PKNCAconc	dplyr grouping for PKNCA
group_by.PKNCAdose	dplyr grouping for PKNCA
group_by.PKNCAresults	dplyr grouping for PKNCA
group_vars.PKNCAconc	Get grouping variables for a PKNCA object
group_vars.PKNCAdose	Get grouping variables for a PKNCA object

-- I --

inner_join.PKNCAconc	dplyr joins for PKNCA
inner_join.PKNCAdose	dplyr joins for PKNCA
inner_join.PKNCAresults	dplyr joins for PKNCA
interp.extrap.conc	Interpolate concentrations between measurements or extrapolate concentrations after the last measurement.
interp.extrap.conc.dose	Interpolate concentrations between measurements or extrapolate concentrations after the last measurement.
interpolate.conc	Interpolate concentrations between measurements or extrapolate concentrations after the last measurement.
interpolate_conc_linear	Interpolate or extrapolate concentrations using the provided method
interpolate_conc_log	Interpolate or extrapolate concentrations using the provided method
interp_extrap_conc_method	Interpolate or extrapolate concentrations using the provided method
is_sparse_pk	Is a PKNCA object used for sparse PK?
is_sparse_pk.PKNCAconc	Is a PKNCA object used for sparse PK?
is_sparse_pk.PKNCAdata	Is a PKNCA object used for sparse PK?
is_sparse_pk.PKNCAresults	Is a PKNCA object used for sparse PK?

-- L --

left_join.PKNCAconc	dplyr joins for PKNCA
left_join.PKNCAdose	dplyr joins for PKNCA
left_join.PKNCAresults	dplyr joins for PKNCA

-- M --

model.frame.PKNCAconc	Extract the columns used in the formula (in order) from a PKNCAconc or PKNCAdose object.
model.frame.PKNCAdose	Extract the columns used in the formula (in order) from a PKNCAconc or PKNCAdose object.
mutate.PKNCAconc	dplyr mutate-based modification for PKNCA
mutate.PKNCAdose	dplyr mutate-based modification for PKNCA
mutate.PKNCAresults	dplyr mutate-based modification for PKNCA

-- N --

normalize_exclude

Normalize the exclude column by setting blanks to NA

-- P --

parse_formula_to_cols	Convert a formula representation to the columns for input data
pk.business	Run any function with a maximum missing fraction of X and 0s possibly counting as missing. The maximum fraction missing comes from 'PKNCA.options("max.missing")'.
pk.calc.ae	Calculate amount excreted (typically in urine or feces)
pk.calc.auc	A compute the Area Under the (Moment) Curve
pk.calc.auc.all	A compute the Area Under the (Moment) Curve
pk.calc.auc.inf	A compute the Area Under the (Moment) Curve
pk.calc.auc.inf.obs	A compute the Area Under the (Moment) Curve
pk.calc.auc.inf.pred	A compute the Area Under the (Moment) Curve
pk.calc.auc.last	A compute the Area Under the (Moment) Curve
pk.calc.aucabove	Calculate the AUC above a given concentration
pk.calc.aucint	Calculate the AUC over an interval with interpolation and/or extrapolation of concentrations for the beginning and end of the interval.
pk.calc.aucint.all	Calculate the AUC over an interval with interpolation and/or extrapolation of concentrations for the beginning and end of the interval.
pk.calc.aucint.inf.obs	Calculate the AUC over an interval with interpolation and/or extrapolation of concentrations for the beginning and end of the interval.
pk.calc.aucint.inf.pred	Calculate the AUC over an interval with interpolation and/or extrapolation of concentrations for the beginning and end of the interval.
pk.calc.aucint.last	Calculate the AUC over an interval with interpolation and/or extrapolation of concentrations for the beginning and end of the interval.
pk.calc.auciv	Calculate AUC for intravenous dosing
pk.calc.auciv_pbext	Calculate AUC for intravenous dosing
pk.calc.aucpext	Calculate the AUC percent extrapolated
pk.calc.aumc	A compute the Area Under the (Moment) Curve
pk.calc.aumc.all	A compute the Area Under the (Moment) Curve
pk.calc.aumc.inf	A compute the Area Under the (Moment) Curve
pk.calc.aumc.inf.obs	A compute the Area Under the (Moment) Curve
pk.calc.aumc.inf.pred	A compute the Area Under the (Moment) Curve
pk.calc.aumc.last	A compute the Area Under the (Moment) Curve
pk.calc.auxc	A compute the Area Under the (Moment) Curve
pk.calc.c0	Estimate the concentration at dosing time for an IV bolus dose.
pk.calc.c0.method.c0	Estimate the concentration at dosing time for an IV bolus dose.
pk.calc.c0.method.c1	Estimate the concentration at dosing time for an IV bolus dose.
pk.calc.c0.method.cmin	Estimate the concentration at dosing time for an IV bolus dose.
pk.calc.c0.method.logslope	Estimate the concentration at dosing time for an IV bolus dose.
pk.calc.c0.method.set0	Estimate the concentration at dosing time for an IV bolus dose.
pk.calc.cav	Calculate the average concentration during an interval.
pk.calc.ceoi	Determine the concentration at the end of infusion
pk.calc.cl	Calculate the (observed oral) clearance
pk.calc.clast.obs	Determine the last observed concentration above the limit of quantification (LOQ).
pk.calc.clr	Calculate renal clearance
pk.calc.cmax	Determine maximum observed PK concentration
pk.calc.cmin	Determine maximum observed PK concentration
pk.calc.count_conc	Count the number of concentration measurements in an interval
pk.calc.cstart	Determine the concentration at the beginning of the interval
pk.calc.ctrough	Determine the trough (end of interval) concentration
pk.calc.deg.fluc	Determine the degree of fluctuation
pk.calc.dn	Determine dose normalized NCA parameter
pk.calc.f	Calculate the absolute (or relative) bioavailability
pk.calc.fe	Calculate fraction excreted (typically in urine or feces)
pk.calc.half.life	Compute the half-life and associated parameters
pk.calc.kel	Calculate the elimination rate (Kel)
pk.calc.mrt	Calculate the mean residence time (MRT) for single-dose data or linear multiple-dose data.
pk.calc.mrt.iv	Calculate the mean residence time (MRT) for single-dose data or linear multiple-dose data.
pk.calc.mrt.md	Calculate the mean residence time (MRT) for multiple-dose data with nonlinear kinetics.
pk.calc.ptr	Determine the peak-to-trough ratio
pk.calc.sparse_auc	Calculate AUC and related parameters using sparse NCA methods
pk.calc.sparse_auclast	Calculate AUC and related parameters using sparse NCA methods
pk.calc.swing	Determine the PK swing
pk.calc.tfirst	Determine time of last observed concentration above the limit of quantification.
pk.calc.thalf.eff	Calculate the effective half-life
pk.calc.time_above	Determine time at or above a set value
pk.calc.tlag	Determine the observed lag time (time before the first concentration above the limit of quantification or above the first concentration in the interval)
pk.calc.tlast	Determine time of last observed concentration above the limit of quantification.
pk.calc.tmax	Determine time of maximum observed PK concentration
pk.calc.totdose	Extract the dose used for calculations
pk.calc.vss	Calculate the steady-state volume of distribution (Vss)
pk.calc.vz	Calculate the terminal volume of distribution (Vz)
pk.nca	Compute NCA parameters for each interval for each subject.
pk.nca.interval	Compute all PK parameters for a single concentration-time data set
pk.nca.intervals	Compute NCA for multiple intervals
pk.tss	Compute the time to steady-state (tss)
pk.tss.data.prep	Clean up the time to steady-state parameters and return a data frame for use by the tss calculators.
pk.tss.monoexponential	Compute the time to steady state using nonlinear, mixed-effects modeling of trough concentrations.
pk.tss.monoexponential.individual	A helper function to estimate individual and single outputs for monoexponential time to steady-state.
pk.tss.monoexponential.population	A helper function to estimate population and popind outputs for monoexponential time to steady-state.
pk.tss.stepwise.linear	Compute the time to steady state using stepwise test of linear trend
PKNCA	Compute noncompartmental pharmacokinetics
PKNCA.choose.option	Choose either the value from an option list or the current set value for an option.
PKNCA.options	Set default options for PKNCA functions
PKNCA.options.describe	Describe a PKNCA.options option by name.
PKNCA.set.summary	Define how NCA parameters are summarized.
PKNCAconc	Create a PKNCAconc object
PKNCAconc.data.frame	Create a PKNCAconc object
PKNCAconc.default	Create a PKNCAconc object
PKNCAconc.tbl_df	Create a PKNCAconc object
PKNCAdata	Create a PKNCAdata object.
PKNCAdata.default	Create a PKNCAdata object.
PKNCAdata.PKNCAconc	Create a PKNCAdata object.
PKNCAdata.PKNCAdose	Create a PKNCAdata object.
PKNCAdose	Create a PKNCAdose object
PKNCAdose.data.frame	Create a PKNCAdose object
PKNCAdose.default	Create a PKNCAdose object
PKNCAdose.tbl_df	Create a PKNCAdose object
PKNCAresults	Generate a PKNCAresults object
pknca_find_units_param	Find NCA parameters with a given unit type
PKNCA_impute_fun_list	Separate out a vector of PKNCA imputation methods into a list of functions
PKNCA_impute_method	Methods for imputation of data with PKNCA
PKNCA_impute_method_start_cmin	Methods for imputation of data with PKNCA
PKNCA_impute_method_start_conc0	Methods for imputation of data with PKNCA
PKNCA_impute_method_start_predose	Methods for imputation of data with PKNCA
pknca_units_add_paren	Add parentheses to a unit value, if needed
pknca_units_table	Create a unit assignment and conversion table
pknca_unit_conversion	Perform unit conversion (if possible) on PKNCA results
pk_nca_result_to_df	Convert the grouping info and list of results for each group into a results data.frame
print.PKNCAconc	Print and/or summarize a PKNCAconc or PKNCAdose object.
print.PKNCAdata	Print a PKNCAdata object
print.PKNCAdose	Print and/or summarize a PKNCAconc or PKNCAdose object.
print.provenance	Print the summary of a provenance object
print.summary_PKNCAresults	Print the results summary

-- R --

right_join.PKNCAconc	dplyr joins for PKNCA
right_join.PKNCAdose	dplyr joins for PKNCA
right_join.PKNCAresults	dplyr joins for PKNCA
roundingSummarize	During the summarization of PKNCAresults, do the rounding of values based on the instructions given.
roundString	Round a value to a defined number of digits printing out trailing zeros, if applicable.

-- S --

setAttributeColumn	Add an attribute to an object where the attribute is added as a name to the names of the object.
setDuration	Set the duration of dosing or measurement
setDuration.PKNCAconc	Set the duration of dosing or measurement
setDuration.PKNCAdose	Set the duration of dosing or measurement
setExcludeColumn	Set the exclude parameter on an object
setRoute	Set the dosing route
setRoute.PKNCAdose	Set the dosing route
signifString	Round a value to a defined number of significant digits printing out trailing zeros, if applicable.
signifString.data.frame	Round a value to a defined number of significant digits printing out trailing zeros, if applicable.
signifString.default	Round a value to a defined number of significant digits printing out trailing zeros, if applicable.
sort.interval.cols	Sort the interval columns by dependencies.
sparse_auc_weight_linear	Calculate the weight for sparse AUC calculation with the linear-trapezoidal rule
sparse_mean	Calculate the mean concentration at all time points for use in sparse NCA calculations
sparse_pk_attribute	Set or get a sparse_pk object attribute
sparse_to_dense_pk	Extract the mean concentration-time profile as a data.frame
summary.PKNCAconc	Print and/or summarize a PKNCAconc or PKNCAdose object.
summary.PKNCAdata	Summarize a PKNCAdata object showing important details about the concentration, dosing, and interval information.
summary.PKNCAdose	Print and/or summarize a PKNCAconc or PKNCAdose object.
summary.PKNCAresults	Summarize PKNCA results
superposition	Compute noncompartmental superposition for repeated dosing
superposition.numeric	Compute noncompartmental superposition for repeated dosing
superposition.PKNCAconc	Compute noncompartmental superposition for repeated dosing

-- T --

time_calc	Times relative to an event (typically dosing)
tss.monoexponential.generate.formula	A helper function to generate the formula and starting values for the parameters in monoexponential models.

-- U --

ungroup.PKNCAconc	dplyr grouping for PKNCA
ungroup.PKNCAdose	dplyr grouping for PKNCA
ungroup.PKNCAresults	dplyr grouping for PKNCA

-- V --

var_sparse_auc

Calculate the variance for the AUC of sparsely sampled PK