Hi everyone
I'm doing a NCA for a MAD study using both Winnonlin and PKNCA
One of the subjects is missing a concentration at the beginning of the last interval at steady state (predose), Winnonlin estimates a concentration at the start of the interval (time of dosing) and computes the parameters accordingly
PKNCA request a concentration at the start of the interval for AUC ( Requesting an AUC range starting (0) before the first measurement (1) is not allowed ), in this case I have tried to use the imputation function, and calculate the auc.int instead:
df <- data.frame(time=c(312, 313, 313.5, 314, 314.5, 315, 316, 318, 320, 322, 326, 336),
conc=c(NA, 9.69, 10.2, 10, 10.1, 10.1, 10.6, 10.9, 9.92, 8.22, 7.73, 6.39),
subject=1)
conc_obj <- PKNCAconc(as.data.frame(df), conc ~ time)
intervals <- data.frame(start = 312, end = 336,
aucinf.obs=TRUE,
half.life = TRUE,
lambda.z = TRUE,
auclast=TRUE,
aucint.inf.obs =TRUE,
aucint.all =TRUE,
aucint.last =TRUE,
impute = "start_cmin, start_conc0"
)
#Using PKNCA package
PKNCA.options(auc.method = "lin up/log down")
data_obj <- PKNCAdata(conc_obj, intervals = intervals, impute="impute")
results_obj <- pk.nca(data_obj)
results <- as.data.frame(results_obj)
I don't get the same results as winnonlin naturally, I tried the PKNCA::interpolate.conc function to calculate a concentration at 312h, it either returns 0, or if I include the concentration immediately before (at 290.5h) I have an estimate that is slightly higher than what I would expect, and again the AUC parameters don't match those from winnonlin
For the record with Winnonlin I get auc.inf = 552.4472 and auc.last = 201.1562 for this subject
Any clue on the best way to proceed to get the same results without removing the interval between the dose and first concentration?
Thank you
Hi everyone
I'm doing a NCA for a MAD study using both Winnonlin and PKNCA
One of the subjects is missing a concentration at the beginning of the last interval at steady state (predose), Winnonlin estimates a concentration at the start of the interval (time of dosing) and computes the parameters accordingly
PKNCA request a concentration at the start of the interval for AUC ( Requesting an AUC range starting (0) before the first measurement (1) is not allowed ), in this case I have tried to use the imputation function, and calculate the auc.int instead:
df <- data.frame(time=c(312, 313, 313.5, 314, 314.5, 315, 316, 318, 320, 322, 326, 336),
conc=c(NA, 9.69, 10.2, 10, 10.1, 10.1, 10.6, 10.9, 9.92, 8.22, 7.73, 6.39),
subject=1)
conc_obj <- PKNCAconc(as.data.frame(df), conc ~ time)
intervals <- data.frame(start = 312, end = 336,
aucinf.obs=TRUE,
half.life = TRUE,
lambda.z = TRUE,
auclast=TRUE,
aucint.inf.obs =TRUE,
aucint.all =TRUE,
aucint.last =TRUE,
impute = "start_cmin, start_conc0"
)
#Using PKNCA package
PKNCA.options(auc.method = "lin up/log down")
data_obj <- PKNCAdata(conc_obj, intervals = intervals, impute="impute")
results_obj <- pk.nca(data_obj)
results <- as.data.frame(results_obj)
I don't get the same results as winnonlin naturally, I tried the PKNCA::interpolate.conc function to calculate a concentration at 312h, it either returns 0, or if I include the concentration immediately before (at 290.5h) I have an estimate that is slightly higher than what I would expect, and again the AUC parameters don't match those from winnonlin
For the record with Winnonlin I get auc.inf = 552.4472 and auc.last = 201.1562 for this subject
Any clue on the best way to proceed to get the same results without removing the interval between the dose and first concentration?
Thank you