knitr::opts_chunk$set( collapse = TRUE, comment = "#>" )
library(PKNCA)
PKNCA can assign and convert units for reporting.
A unit assignment and conversion table can be generated as a data.frame to use with the pknca_units_table()
function or manually.
The simplest method each of the types of units for inputs and automatically generates the units for each NCA parameter.
d_units_auto <- pknca_units_table(concu="ng/mL", doseu="mg", amountu="mg", timeu="hr") # Show a selection of the units generated d_units_auto[d_units_auto$PPTESTCD %in% c("cmax", "tmax", "auclast", "cl.obs", "vd.obs"), ]
As you see above, the default units table has a column for the PPTESTCD
indicating the parameter. And, the column PPORRESU
indicates what the default units are.
Without unit conversion, the units for some parameters (notably clearances and volumes) are not so useful. You can add a conversion table to make any units into the desired units. For automatic conversion to work, the units must always be convertible (by the units
library). Notably for automatic conversion, you cannot go from mass to molar units since there is not a unique conversion from mass to moles.
d_units_clean <- pknca_units_table( concu="ng/mL", doseu="mg", amountu="mg", timeu="hr", conversions= data.frame( PPORRESU=c("mg/(hr*ng/mL)", "mg/(ng/mL)", "hr"), PPSTRESU=c("L/hr", "L", "day") ) ) # Show a selection of the units generated d_units_clean[d_units_clean$PPTESTCD %in% c("cmax", "tmax", "auclast", "cl.obs", "vd.obs"), ]
Now, the units are much cleaner to look at.
To do a conversion that is not possible directly with the units
library, you can add the conversion factor manually by adding the conversion_factor
column. You can mix-and-match manual and automatic modification by setting the conversion_factor
column to NA
when you want automatic conversion. In the example below, we convert concentration units to molar. Note that AUC units are not set to molar because we did not specify that conversion; all conversions must be specified.
d_units_clean_manual <- pknca_units_table( concu="ng/mL", doseu="mg", amountu="mg", timeu="hr", conversions= data.frame( PPORRESU=c("mg/(hr*ng/mL)", "mg/(ng/mL)", "hr", "ng/mL"), PPSTRESU=c("L/hr", "L", "day", "nmol/L"), conversion_factor=c(NA, NA, NA, 1000/123) ) ) # Show a selection of the units generated d_units_clean_manual[d_units_clean_manual$PPTESTCD %in% c("cmax", "tmax", "auclast", "cl.obs", "vd.obs"), ]
For more details on parts of this NCA calculation example unrelated to units, see the theophylline example vignette.
conc_obj <- PKNCAconc(as.data.frame(datasets::Theoph), conc~Time|Subject) d_dose <- unique(datasets::Theoph[datasets::Theoph$Time == 0, c("Dose", "Time", "Subject")]) dose_obj <- PKNCAdose(d_dose, Dose~Time|Subject)
The difference from a calculation without units comes when setting up the PKNCAdata
object. You will add the units with the units
argument.
Since no urine or other similar collection is performed, the amountu
argument is omitted for pknca_units_table()
.
d_units <- pknca_units_table( concu="mg/L", doseu="mg/kg", timeu="hr", # use molar units for concentrations and AUCs conversions= data.frame( PPORRESU=c("(mg/kg)/(hr*mg/L)", "(mg/kg)/(mg/L)", "mg/L", "hr*mg/L"), PPSTRESU=c("L/hr/kg", "L/kg", "mmol/L", "hr*mmol/L"), conversion_factor=c(NA, NA, 1/180.164, 1/180.164) ) ) data_obj <- PKNCAdata(conc_obj, dose_obj, units=d_units) result_obj <- pk.nca(data_obj) summary(result_obj)
Sometimes, when multiple analytes are used and, for example, molar outputs are desired while inputs are in mass units. Different unit conversions may be required for different inputs.
Different unit conversions can be used by adding the grouping column to the units specification.
Start by setting up a concentration dataset with two analytes. Since the dosing doesn't have an "Analyte" column, it will be matched to all concentration measures for the subject.
d_conc_theoph <- as.data.frame(datasets::Theoph) d_conc_theoph$Analyte <- "Theophylline" # Approximately 6% of theophylline is metabolized to caffeine # (https://www.pharmgkb.org/pathway/PA165958541). Let's pretend that means it # has 6% of the theophylline concentration at all times. d_conc_caffeine <- as.data.frame(datasets::Theoph) d_conc_caffeine$conc <- 0.06*d_conc_caffeine$conc d_conc_caffeine$Analyte <- "Caffeine" d_conc <- rbind(d_conc_theoph, d_conc_caffeine) d_dose <- unique(datasets::Theoph[datasets::Theoph$Time == 0, c("Dose", "Time", "Subject")])
Setup the units with an "Analyte" column to separate the units used.
d_units_theoph <- pknca_units_table( concu="mg/L", doseu="mg/kg", timeu="hr", # use molar units for concentrations and AUCs conversions= data.frame( PPORRESU=c("(mg/kg)/(hr*mg/L)", "(mg/kg)/(mg/L)", "mg/L", "hr*mg/L"), PPSTRESU=c("L/hr/kg", "L/kg", "mmol/L", "hr*mmol/L"), conversion_factor=c(NA, NA, 1/180.164, 1/180.164) ) ) d_units_theoph$Analyte <- "Theophylline" d_units_caffeine <- pknca_units_table( concu="mg/L", doseu="mg/kg", timeu="hr", # use molar units for concentrations and AUCs conversions= data.frame( PPORRESU=c("(mg/kg)/(hr*mg/L)", "(mg/kg)/(mg/L)", "mg/L", "hr*mg/L"), PPSTRESU=c("L/hr/kg", "L/kg", "mmol/L", "hr*mmol/L"), conversion_factor=c(NA, NA, 1/194.19, 1/194.19) ) ) d_units_caffeine$Analyte <- "Caffeine" d_units <- rbind(d_units_theoph, d_units_caffeine)
Now, calculate adding the different units per analyte to the data object.
conc_obj <- PKNCAconc(d_conc, conc~Time|Subject/Analyte) dose_obj <- PKNCAdose(d_dose, Dose~Time|Subject) data_obj <- PKNCAdata(conc_obj, dose_obj, units=d_units) result_obj <- pk.nca(data_obj) summary(result_obj)
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