Bioequivalence and Bioavailability Forum • PKNCA calculation of AUC

jag009
★★★

NJ,
2024-05-20 01:45
(356 d 08:06 ago)

Posting: # 24001
Views: 2,900

PKNCA calculation of AUC [🇷 for BE/BA]

Hi all,

I am getting some weird results when I tried to use PKNCA...

1) I followed the instructions from the following link and the AUC calculated from the PKNCA example was close to my Excel AUClast calculation. PKNCA's AUClast value was 12.9965842 and my excel calculated value (using the AUC equation) was 13.05000. The values were not far off from each others.

PKNAC example

2) I modified the PKNCA codes from the example above to calculate PK parameters for the following dataset. PKNCA's AUClast value was 5997.7885480, but my excel calculated value was 6825.422.???? I am not sure what went wrong. Below is the dataset. Can anyone give it a try and let me know?

Here are the codes I updated from the link above and used to run the computation (I didn't include the ggplot routine here since that part ran fine)

suppressPackageStartupMessages({

library(PKNCA)

library(dplyr)

library(cowplot)

library(knitr)

library(ggplot2)

})

scale_colour_discrete <- scale_colour_hue

scale_fill_discrete <- scale_fill_hue

my_conc <- data.frame(read.csv("Data.csv"))

my_conc$BLQ <- my_conc$Concentration == 0

my_conc$measured <- TRUE



conc_obj <- PKNCAconc(my_conc, Concentration~Time|Subject)

data_obj <- PKNCAdata(data.conc=conc_obj,

                      intervals=data.frame(start=0, end=72,

                      auclast=TRUE, aucinf.pred=TRUE, aucinf.obs=TRUE))



results_obj <- pk.nca(data_obj)



kable(as.data.frame(results_obj))

Here is the DATA.CSV


Subject   Time   Concentration

273      0           0

273      0.5       307.838

273      1         467.58

273      2         439.886

273      4         489.621

273      8         306.011

273     24          54.424

273     48          3.628

273     72          0

Thx
J

Helmut
★★★

Vienna, Austria,
2024-05-20 09:39
(356 d 00:11 ago)

@ jag009
Posting: # 24003
Views: 2,462

PKNCA defaults to the linear-up/log-down rule

Post reply

Hi John,

❝ I modified the PKNCA codes from the example above to calculate PK parameters for the following dataset. PKNCA's AUClast value was 5997.7885480, but my excel calculated value was 6825.422.???? I am not sure what went wrong.

In PKNCA the linear-up/log-down rule is the default (see this article). Let’s go for a second opinion:

calc.AUC <- function(t, C, rule = "linlog", digits = 5) { # if nonnumeric codes like BQL or NR are used, they # must be enclosed in 'single' or "double" quotes if (!length(C) == length(t)) stop ("Both vectors must have the same number of elements.") if (!length(unique(t)) == length(t)) stop ("Values in t-vector are not unique.") if (!rule %in% c("lin", "linlog")) stop ("rule must be either \"lin\" or \"linlog\".") # convert eventual nonnumerics to NAs C <- unlist(suppressWarnings(lapply(C, as.numeric))) tmax <- min(t[C == max(C, na.rm = TRUE)], na.rm = TRUE) C[t < tmax & is.na(C)] <- 0 # set NAs prior to tmax to zero x <- NULL y <- data.frame(t = t, C = C, section = "", pAUC = 0) y <- y[with(y, order(t)), ] # belt plus suspenders NAs <- which(is.na(C)) # location of eventual NAs if (sum(NAs) > 0) { # remove NAs temporarily x <- y[!complete.cases(y), ] x$pAUC <- x$AUC <- NA y <- y[complete.cases(y), ] } for (i in 1:(nrow(y) - 1)) { if (rule == "linlog") { y$section[1] <- "up" if (y$C[i+1] < y$C[i]) { # decreasing y$pAUC[i+1] <- (y$t[i+1] - y$t[i]) * (y$C[i+1] - y$C[i]) / log(y$C[i+1] / y$C[i]) y$section[i+1] <- "down" } else { # increasing or equal y$pAUC[i+1] <- 0.5 * (y$t[i+1] - y$t[i]) * (y$C[i+1] + y$C[i]) y$section[i+1] <- "up" } } else { y$pAUC[i+1] <- 0.5 * (y$t[i+1] - y$t[i]) * (y$C[i+1] + y$C[i]) } } y$AUC <- cumsum(y$pAUC) # sum partial AUCs y <- rbind(x, y) # get the NAs back y <- y[with(y, order(t)), ] # sort by time y[, 4:5] <- round(y[, 4:5], digits) if (rule == "lin") y <- y[, -3] # not needed if (rule == "linlog") { attr(y, "rule") <- "linear-up/log-down rule" } else { attr(y, "rule") <- "linear rule" } return(y) }

Now your data (IMHO, zero at the end doesn’t make sense):

t <- c(0, 0.5, 1, 2, 4, 8, 24, 48, 72) C <- c(0, 307.838, 467.58, 439.886, 489.621, 306.011, 54.424, 3.628, 'BQL')

With my homebrew:

df <- calc.AUC(t, C, rule = "linlog", digits = 6) cat(attr(df, "rule"), "\n"); print(df, row.names = FALSE) linear-up/log-down rule t C section pAUC AUC 0.0 0.000 up 0.0000 0.0000 0.5 307.838 up 76.9595 76.9595 1.0 467.580 up 193.8545 270.8140 2.0 439.886 down 453.5921 724.4061 4.0 489.621 up 929.5070 1653.9131 8.0 306.011 down 1562.6031 3216.5162 24.0 54.424 down 2331.1067 5547.6230 48.0 3.628 down 450.1656 5997.7885 72.0 NA NA NA df <- calc.AUC(t, C, rule = "lin", digits = 6) cat(attr(df, "rule"), "\n"); print(df, row.names = FALSE) linear rule t C pAUC AUC 0.0 0.000 0.0000 0.0000 0.5 307.838 76.9595 76.9595 1.0 467.580 193.8545 270.8140 2.0 439.886 453.7330 724.5470 4.0 489.621 929.5070 1654.0540 8.0 306.011 1591.2640 3245.3180 24.0 54.424 2883.4800 6128.7980 48.0 3.628 696.6240 6825.4220 72.0 NA NA NA

Confirmed that PKNCA is using the linear-up/log-down and you the linear trapezoidal in bloody Excel. If you really want to do that (I hope, you don’t), see there.
Note: If you give 0 at 72, you will get the same result with the lin-up/log-down, but 6868.958 with the linear rule. That’s Pharsight’s crappy AUCall.

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Helmut Schütz

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