NCA Docstrings

NCADose

NCADose takes the following arguments

• time: time of the dose
• amt: The amount of dosage
• route: Type of route, NCA.IVBolus, NCA.IVInfusion or NCA.EV
• ii: interdose interval
• ss: steady-state

NCASubject(conc, time; start_time=nothing, end_time=nothing, volume=nothing, concu=true, timeu=true, volumeu=true,
                        id=1, group=nothing, dose=nothing, llq=nothing,
                        lambdaz=nothing, clean=true, check=true, lambdazslopetimes = nothing, lambdazidxs = nothing, num_blqs_df = 0,  kwargs...)

Constructs a NCASubject

Note that llq keyword argument still takes effects with the presence of the blq data column, and llq defaults to 0.

Setting clean=false disables all checks on conc and time to remove the cost of checking and cleaning data. It should only be used when the data is for sure "clean".

read_nca(df::Union{DataFrame,AbstractString}; id=:id, time=:time, observations=:conc,
                                              start_time=:start_time, end_time=:end_time, volume=:volume,
                                              amt=:amt, route=:route, duration=:duration, blq=:blq,
                                              ii=:ii, ss=:ss, group=nothing, concu=true, timeu=true, amtu=true, volumeu=true,
                                              verbose=true, lambdazidxs = nothing, lambdazslopetimes = nothing, kwargs...)

Parse a DataFrame object or a CSV file to NCAPopulation. NCAPopulation holds an array of NCASubjects which can cache certain results to achieve efficient NCA calculation.

For details about the handling of concentration values below the lower limit of quantification, please check out the documentation of NCA.cleanblq. All the keyword arguments of NCA.cleanblq are applicable to read_nca, too.

  run_nca(pop::NCAPopulation;
              parameters = nothing,
              studyid::String="",
              studytitle::String="",
              author=[],
              sponsor::String = "",
              date::DateTime=Dates.now(),
              conclabel::String="",
              timelabel::String="",
              grouplabels::Array=String[],
              groupsizes::NamedTuple=NamedTuple(),
              versionnumber::Union{String, VersionNumber}=v"0.1",
              sigdigits=nothing,
              kwargs...)

The primary function in NCA.jl, to run NCA analysis on a population. Returns a NCAReport object that has a data frame of parameters computed in the analysis and other metadata information passed when run_nca is called.

showunits(nca:NCASubject[, indent])

Prints the units of concentration, time, auc, aumc, λz, and dose for nca. The optional argument indent adds indent number of spaces to the left of the list.

  summarize(data::AbstractDataFrame;
              stratify_by::AbstractVector{<:Union{Symbol,Integer,AbstractString}} = Symbol[],
              parameters::AbstractVector{<:Union{Symbol,Integer,AbstractString}} = [:cmax, :tmax, :half_life, :aucinf_obs, :auclast, :cl, :vz],
              stats::AbstractVector{<:Function} = [numsamples, extrema, mean, std, geomean, geostd, geomeanCV])

Computes summary statistics specified by stats kwarg for parameters obtained from NCA analysis with run_nca. stratify_by allows you to group your computations.