This building block declares a three compartment distribution component for a pharmacokinetic model.
pk_distribution_3cmp(
prm_vc = prm_log_normal("vc", median = 100, var_log = 0.1),
prm_vp1 = prm_log_normal("vp1", median = 5, var_log = 0.1),
prm_vp2 = prm_log_normal("vp2", median = 5, var_log = 0.1),
prm_q1 = prm_log_normal("q1", median = 25, var_log = 0.1),
prm_q2 = prm_log_normal("q2", median = 25, var_log = 0.1)
)
Parameter model for the central volume of distribution
Parameter model for the volume of the first peripheral compartment
Parameter model for the volume of the second peripheral compartment
Parameter model for the inter-compartmental clearance between central and first peripheral compartment
Parameter model for the inter-compartmental clearance between central and second peripheral compartment
A building block of type 'pk_component'
PK components can be added to a pk_model and exist in three different types: absorption, distribution, and elimination. The absorption component is optional, distribution and elimination are not and need to be added for the PK model to be valid.
A PK model can only have one component of each type and adding a component with an already existing type will replace the previous definition. For example, the distribution component will be a two compartment model in the following snippet:
pkm <- pk_model() + pk_absorption_fo() + pk_distribution_1cmp() + pk_distribution_2cmp() + pk_elimination_linear() + obs_additive(conc~C["central"]) pkm
All PK component functions allow the specification of the parameter
model via their arguments. Arguments that refer to a parameter start
with the prefix prm_
. The default parameter model can be deduced from
the default arguments in the usage section of the help entry. The
parameter name, specified via the name=
argument of the parameter
model building block allows the renaming of the model parameters.
For example, the parameter prm_vc=
refers to the central volume of
distribution parameter in the one compartment distribution PK component
and the default parameter model is a log-normal distribution. The
following code block specifies a normal distribution parameter model and
names the parameter v
:
pk_distribution_1cmp( prm_vc = prm_normal("v", mean = 50, var = 25) )
pk_model()
for the creation of PK models
Other distribution components:
pk_distribution_1cmp()
,
pk_distribution_2cmp()