Performs non-compartmental analysis on pooled data

Implements pooled concentration–time profiling followed by non-compartmental analysis (NCA) to derive pharmacokinetic parameters across single-dose, multiple-dose, or combined dosing scenarios under bolus, oral, or infusion routes.

Usage

run_pooled_nca(
  dat,
  route = c("bolus", "oral", "infusion"),
  dose_type = c("first_dose", "repeated_doses", "combined_doses"),
  pooled = NULL,
  pooled_ctrl = pooled_control(),
  nca_ctrl = nca_control()
)

Arguments

dat: A data frame containing raw time–concentration data in the standard nlmixr2 format.
route: Route of administration. Must be one of bolus, oral, or infusion.
dose_type: Classified as first_dose, repeated_doses, or combined_doses based on whether observed concentrations occur following the first administration, during repeated dosing, or across both contexts.
pooled: Optional pre-pooled data returned by get_pooled_data.
pooled_ctrl: Optional list of control parameters used by get_pooled_data() for pooling observations. Defaults to output from pooled_control().
nca_ctrl: List of options created by nca_control for NCA settings.

Value

A list containing NCA results according to the selected dose_type.

Details

The function first pools individual subject data into representative concentration–time profiles using get_pooled_data based on the settings in pooled_ctrl. The pooled profiles are then passed to getnca, which computes non-compartmental parameters using rules specified in nca_ctrl.

Author

Zhonghui Huang

Examples

out   <- processData(Bolus_1CPT)
#> 
#> 
#> Infometrics                               Value          
#> ----------------------------------------  ---------------
#> Dose Route                                bolus          
#> Dose Type                                 combined_doses 
#> Number of Subjects                        120            
#> Number of Observations                    6951           
#> Subjects with First-Dose Interval Data    120            
#> Observations in the First-Dose Interval   2276           
#> Subjects with Multiple-Dose Data          120            
#> Observations after Multiple Doses         4675           
#> ----------------------------------------  ------
dat   <- out$dat
route <- out$Datainfo$Value[out$Datainfo$Infometrics == "Dose Route"]

run_pooled_nca(
  dat       = dat,
  dose_type = "first_dose",
  route     = route
)$nca.fd.results
#> $clobs
#> [1] 4.168867
#> 
#> $vzobs
#> [1] 66.19907
#> 
#> $half_life
#> [1] 11.00676
#> 
#> $auct
#> [1] 0.2349507
#> 
#> $auc0_inf
#> [1] 0.2398733
#> 
#> $C_last
#> [1] 0.00031
#> 
#> $lambdaz
#> [1] 0.0629747
#> 
#> $aumc_0_t
#> [1] 3.479866
#> 
#> $aumc_0_inf
#> [1] 3.853391
#> 
#> $used_points
#> [1] 10
#> 
#> $adj.r.squared
#> [1] 0.9975843
#> 
#> $messages
#> [1] "[Message]: 1: Selected 10 points (higher Rsquare) Rsquare=0.9976 lambdaz=0.0630"
#> 
#> $time.spent
#> [1] 0.006
#>