calc.par.th {qpNCA} | R Documentation |
Calculate Lambda_z Parameters
Description
Calculates PK parameters that need lambda_z.
Usage
calc.par.th(
x,
by = character(0),
th = th,
covariates = NA,
dose = "dose",
factor = 1,
reg = "SD",
ss = "N",
route = "EV"
)
Arguments
x |
result parameter dataset from |
by |
column names in x indicating grouping variables |
th |
result dataset from |
covariates |
covariates dataset (containing at least dose for CL calculation); defaults to unique combinations of |
dose |
variable containing the dose amount; default 'dose' set to 1 if not in |
factor |
conversion factor for CL and V calculation (e.g. dose in mg, conc in ng/mL, factor=1000); x$factor overrides |
reg |
regimen, "sd" or "md"; x$reg overrides |
ss |
is steady state reached (y/n); x$ss overrides |
route |
of drug administration ("EV","IVB","IVI"); x$route overrides |
Value
A dataset containing all parameters calculated in est.thalf
and calc.par
with estimates for the following parameters added, one observation per subject:
Parameter | Description |
clast.pred | predicted concentration at tlast |
aucinf.obs | aucinf based on observed concentration at tlast |
aucinf.pred | aucinf based on predicted concentration at tlast |
aumcinf.obs | area under the first moment curve extrapolated to infinity, based on observed concentration at tlast |
aumcinf.pred | area under the first moment curve extrapolated to infinity, based on predicted concentration at tlast |
cl.obs, cl.f.obs | clearance based on aucinf.obs, at steady state based on auctau |
cl.pred, cl.f.pred | clearance based on aucinf.pred |
cl.ss, cl.f.ss | clearance at steady state, based on auctau |
mrt.obs | mean residence time based on aumcinf.obs and aucinf.obs |
mrt.pred | mean residence time based on aumcinf.pred and aucinf.pred |
vz.obs, vz.f.obs | distribution volume based on cl.f.obs, at steady state based on auctau |
vz.pred, vz.f.pred | distribution based on cl.pred/cl.f.pred |
vss.obs | steady-state volume based on cl.obs and mrt.obs |
vss.pred | steady-state volume based on cl.pred and mrt.pred |
pctextr.pred | percentage of AUC extrapolated to infinity, based on aucinf.pred |
pctextr.obs | percentage of AUC extrapolated to infinity, based on aucinf.obs |
pctback.pred | percentage of AUC extrapolated back to 0, based on aucinf.pred |
pctback.obs | percentage of AUC extrapolated back to 0, based on aucinf.obs |
Note: ctmax must be merged separately as those were calculated from uncorrected data.
Examples
example(calc.par) # creates par
# notice x includes (optional) loqrule, includeCmax, reg, method, route, ss
covs <- Theoph %>%
select(subject = Subject, Wt, dose = Dose) %>%
unique %>%
mutate(dose = dose * Wt, subject=as.numeric(as.character(subject))) # see ?Theoph
y <- x %>% select(subject, reg, ss, loqrule) %>% unique
y %<>% mutate(factor = 1)
par %<>% left_join(y, by = 'subject')
par %<>% calc.par.th(by = 'subject', th = th, covariates = covs)
par %<>% left_join(ctmax, ., by = 'subject')
par %>% head
par %>% data.frame %>% head(2)