humanpred / pknca

The PKNCA R Package 
=====
The PKNCA R package is designed to perform all noncompartmental
analysis (NCA) calculations for pharmacokinetic (PK) data. The
package is broadly separated into two parts (calculation and summary)
with some additional housekeeping functions.
Along with dense-sampling NCA and its summaries, PKNCA supports:
* sparse sampling designs (`vignette("v04-sparse")`)
* units, including automatic conversion to preferred reporting units
* imputation of missing or unmeasured data
 (`vignette("v08-data-imputation")`)
* CDISC-formatted output (`as.data.frame(out_format = "cdisc")`)
* bioequivalence assessment (`vignette("v50-bioequivalence")`)
The primary and secondary goals of the PKNCA package are to 1) only
give correct answers to the specific questions being asked and 2)
automate as much as possible to simplify the task of the analyst. When
automation would leave ambiguity or make a choice that the analyst may
have an alternate preference for, it is either not used, is possible
to override or raises an error message.
Note that backward compatibility will not be guaranteed until version
1.0. Argument and function changes will continue until then. These
will be especially noticeable around the inclusion of IV NCA parameters and additional specifications of the drug, which include dose amount and route of administration.
# Citation
Citation information for the PKNCA package is available with a call to
`citation(package="PKNCA")`. The preferred citation until publication
of version 1.0 is below:
Denney W, Duvvuri S and Buckeridge C (2015). "Simple, Automatic
Noncompartmental Analysis: The PKNCA R Package." _Journal of
Pharmacokinetics and Pharmacodynamics_, *42*(1), pp. 11-107,S65. ISSN
1573-8744, doi: 10.1007/s10928-015-9432-2, .
# Installation
## From CRAN
The current stable version of PKNCA is available on CRAN. You can
install it and its dependencies using the following command:
 install.packages("PKNCA")
## From GitHub
To install the development version from GitHub, type the following commands:
 install.packages("pak")
 pak::pak("humanpred/pknca")
# Documentation
* Function reference and articles:
 https://humanpred.github.io/pknca/
* User Guide (book): https://humanpred.github.io/pknca-book/
* Vignettes: `vignette(package = "PKNCA")`, starting with
 `vignette("v01-introduction-and-usage", package = "PKNCA")`
# Calculating parameters
 # Load the package
 library(PKNCA)
 # Set the business rule options with the PKNCA.options() function
 # Load your concentration-time data
 conc_raw <- read.csv("myconc.csv")
 # Load your dose data
 dose_raw <- read.csv("mydose.csv")
 # Put your concentration data into a PKNCAconc object
 o_conc <- PKNCAconc(data=conc_raw,
 formula=conc~time|treatment+subject/analyte)
 # Put your dose data into a PKNCAdose object
 o_dose <- PKNCAdose(data=dose_raw,
 formula=dose~time|treatment+subject)
 # Combine the two (and automatically determine the intervals of
 # interest
 o_data <- PKNCAdata(o_conc, o_dose)