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Calculate the absorption rate constant using the Wagner-Nelson method

Source: R/extra_ka.R
ka_wanger_nelson.Rd

Calculates absorption rate constant using the Wagner–Nelson method for single-dose extravascular pharmacokinetics.

Usage

ka_wanger_nelson(dat, nca.out = NULL)

Arguments

dat

A data frame containing two columns: 'TIME' for sampling time points and 'DV' for observed plasma drug concentrations.

nca.out

Optional object containing results from a previous noncompartmental analysis. It must include 'auc0_inf' for the area under the concentration-time curve extrapolated to infinity and 'lambdaz' for the terminal elimination rate constant. If not provided, the function calls 'getnca' internally using the input data.

Value

A list containing:

  • ka: Estimated absorption rate constant

  • dat_out_wanger_nelson: Input data frame augmented with calculated pharmacokinetic variables including cumulative AUC, fraction absorbed, and fraction remaining

Details

The Wagner-Nelson method estimates the fraction of drug absorbed over time based on the principle of mass balance, where the unabsorbed fraction is quantified as the proportion of the administered dose that has not yet entered systemic circulation. A linear regression is applied to the natural logarithm of the unabsorbed fraction versus time, and the negative slope of this regression corresponds to the first-order absorption rate constant 'ka'.

Key assumptions:

  • Single-dose oral or extravascular administration

  • First-order absorption and first-order elimination

  • Linear pharmacokinetics with 'ka' greater than 'ke'

Computational steps:

  • AUC is calculated using trapezoidal integration.

  • The fraction absorbed is calculated from AUC and the terminal elimination rate constant.

  • The remaining fraction is transformed using the natural logarithm.

  • Linear regression of log(remaining fraction) against time yields 'ka'.

References

Wagner JG and Nelson E (1963). Percent absorbed time plots derived from blood level and/or urinary excretion data. Journal of Pharmaceutical Sciences, 52(6), 610-611.

Author

Zhonghui Huang

Examples

# Simulated one-compartment oral absorption data
Dose <- 100
Fbio <- 1
Vd   <- 70
CL   <- 4
ka   <- 1.2
ke   <- CL / Vd
t  <- seq(0.5, 8, by = 0.5)
Ct <- (Fbio * Dose * ka) / (Vd * (ka - ke)) * (exp(-ke * t) - exp(-ka * t))

dat <- data.frame(TIME = t, DV = Ct)

ka_wanger_nelson(dat)
#> $ka
#> [1] 1.220523
#> 
#> $dat_out_wanger_nelson
#>    TIME        DV auc_intervals auc_accumulate  frac_abs frac_remained
#> 1   0.5 0.6345319     0.1586330      0.1586330 0.4536953  0.5463047204
#> 2   1.0 0.9648974     0.3998573      0.5584903 0.7024742  0.2975257803
#> 3   1.5 1.1288363     0.5234334      1.0819237 0.8387987  0.1612012752
#> 4   2.0 1.2019277     0.5826910      1.6646147 0.9134128  0.0865872063
#> 5   2.5 1.2256362     0.6068910      2.2715057 0.9541652  0.0458348416
#> 6   3.0 1.2227051     0.6120853      2.8835910 0.9763394  0.0236606336
#> 7   3.5 1.2056028     0.6070770      3.4906680 0.9883231  0.0116769496
#> 8   4.0 1.1811596     0.5966906      4.0873586 0.9947193  0.0052807108
#> 9   4.5 1.1531117     0.5835678      4.6709264 0.9980542  0.0019458416
#> 10  5.0 1.1234978     0.5691524      5.2400788 0.9997139  0.0002861454
#> 11  5.5 1.0934250     0.5542307      5.7943095 1.0004590 -0.0004589994
#> 12  6.0 1.0634895     0.5392286      6.3335381 1.0007069 -0.0007068955
#> 13  6.5 1.0340078     0.5243743      6.8579124 1.0006864 -0.0006864320
#> 14  7.0 1.0051428     0.5097876      7.3677001 1.0005231 -0.0005230981
#> 15  7.5 0.9769735     0.4955291      7.8632291 1.0002856 -0.0002856395
#> 16  8.0 0.9495332     0.4816267      8.3448558 1.0000117 -0.0000116642
#>