Structure
Data for input into posologyr is the same type of data
input for rxode2. As stated in the rxode2
documentation (rxode2 datasets), it is also similar to data for NONMEM.
The patient dataset is a table of sequential event records, in which each line is an event. A description of the different event types is available in the rxode2 documentation (rxode2 Event Types).
Below is a minimal working example:
data.frame(ID=1,
TIME=c(0.0,3),
DV=c(NA,60.0),
AMT=c(1000,0),
EVID=c(101,0))
#> ID TIME DV AMT EVID
#> 1 1 0 NA 1000 101
#> 2 1 3 60 0 0Required fields and data
- TIME
- Dosing times, and sampling times of therapeutic drug monitoring (TDM). The units depend on the specification of the population pharmacokinetics (ppk) model.
- AMT
- Amount of drug administered. The units depend on the specification of the ppk model.
- EVID
- Event type. Must be 0 for all observations (concentrations from TDM).
- DV
- For concentrations. Must be NA when EVID is not 0.
- Covariates
-
Every covariate defined in the prior
posologyrmodel. The column names must match the covariate vector from the ppk model. - OCC
- Occasions. Required for models with inter-occasion variability.
- DVID
- Observation type. Required for models with multiple endpoints.
- CMT
-
Name (or number) of the compartment where the dose is administered, see
vignette("route_of_administration").
Common use cases
A priori dose adjustment
Before dosing: the simplest patient record is a single line dataframe, with individual patient covariates, and all other columns (TIME, DV, AMT, EVID) set to zero.
data.frame(ID=1,
TIME=0,
DV=0,
AMT=0,
EVID=0,
COVAR1=c("X"),
COVAR2=c("Y"))
#> ID TIME DV AMT EVID COVAR1 COVAR2
#> 1 1 0 0 0 0 X YOral administration or IV bolus
EVID = 1 for an instantaneous administration in the
first compartment defined in the ppk model: either the central
compartment for an IV bolus, or a depot compartment for an oral
administration.
Intermittent infusion
EVID = 1 for a bolus infusion, administered in the first
compartment defined in the ppk model.
DUR defines its duration.
AMT is the amount administered over the duration
DUR.
Inter-occasion variability
For a given occasion, the value of OCC must be repeated
for each row. OCC must be specified for all the rows in the
table.
data.frame(ID=1,
TIME=c(0.0,1.0,14.0,24.0,25.0,36.0),
DV=c(NA,25.0,5.5,NA,30.0,6.0),
AMT=c(1000,0,0,1000,0,0),
DUR=c(0.5,NA,NA,0.5,NA,NA),
EVID=c(1,0,0,1,0,0),
OCC=c(1,1,1,2,2,2),
COVAR1=c("X"),
COVAR2=c("Y"))
#> ID TIME DV AMT DUR EVID OCC COVAR1 COVAR2
#> 1 1 0 NA 1000 0.5 1 1 X Y
#> 2 1 1 25.0 0 NA 0 1 X Y
#> 3 1 14 5.5 0 NA 0 1 X Y
#> 4 1 24 NA 1000 0.5 1 2 X Y
#> 5 1 25 30.0 0 NA 0 2 X Y
#> 6 1 36 6.0 0 NA 0 2 X YMultiple endpoints
DVID is used to specify the type of each observation.
The values of DVID in the dataset must match the names of
the residual error models, see
vignette("multiple_endpoints").
data.frame(ID=1,
TIME=c(0.0,1.0,14.0,24.0,25.0,36.0),
DV=c(NA,20.0,80,35.5,60.0,40.0),
AMT=c(1000,0,0,0,0,0),
EVID=c(1,0,0,0,0,0),
DVID=c("parent","parent","metabolite","parent","metabolite","metabolite"),
COVAR1=c("X"),
COVAR2=c("Y"))
#> ID TIME DV AMT EVID DVID COVAR1 COVAR2
#> 1 1 0 NA 1000 1 parent X Y
#> 2 1 1 20.0 0 0 parent X Y
#> 3 1 14 80.0 0 0 metabolite X Y
#> 4 1 24 35.5 0 0 parent X Y
#> 5 1 25 60.0 0 0 metabolite X Y
#> 6 1 36 40.0 0 0 metabolite X Y