getLibraryModelName

Get the name of a library model given a list of library filters.

Usage

        R
    
getLibraryModelName(library, filters = list())

Arguments

library: (character) One of the MonolixSuite library of models. Possible values are "pk", "pd", "pkpd", "pkdoubleabs", "pm", "tmdd", "tte", "count" and "tgi".
filters: (list(name = character)) Named list of filters (optional), format: list(filterKey = "filterValue", ...). Default empty list. Since available filters are not in any particular order, filterKey should always be stated.

Value

Name of the filtered model, or vector of names of the available models if not all filters were selected. Names start with "lib:".

Details

Models can be loaded from a library based on a selection of filters as in PKanalix, Monolix and Simulx GUI. For a complete description of each model library, and guidelines on how to select models, please visit https://mlxtran.lixoft.com/model-libraries/.

getLibraryModelName enables to get the name of the model to be loaded. You can then use it in setStructuralModel or newProject to load the model in an existing or in a new project.

All possible keys and values for each of the libraries are listed below.

PK library

key		values
administration		bolus, infusion, oral, oralBolus
delay		noDelay, lagTime, transitCompartments
absorption		zeroOrder, firstOrder
distribution		1compartment, 2compartments, 3compartments
elimination		linear, MichaelisMenten
parametrization		rate, clearance, hybridConstants
bioavailability		true, false

PD library

key		values
response		immediate, turnover
drugAction		linear, logarithmic, quadratic, Emax, Imax, productionInhibition,
		degradationInhibition, degradationStimulation, productionStimulation
baseline		const, 1-exp, exp, linear, null
inhibition		partialInhibition, fullInhibition
sigmoidicity		true, false

PKPD library

key		values
administration		bolus, infusion, oral, oralBolus
delay		noDelay, lagTime, transitCompartments
absorption		zeroOrder, firstOrder
distribution		1compartment, 2compartments, 3compartments
elimination		linear, MichaelisMenten
parametrization		rate, clearance
bioavailability		true, false
response		direct, effectCompartment, turnover
drugAction		Emax, Imax, productionInhibition, degradationInhibition,
		degradationStimulation, productionStimulation
baseline		const, null
inhibition		partialInhibition, fullInhibition
sigmoidicity		true, false

PK double absorption library

key		values
firstAbsorption		zeroOrder, firstOrder
firstDelay		noDelay, lagTime, transitCompartments
secondAbsorption		zeroOrder, firstOrder
secondDelay		noDelay, lagTime, transitCompartments
absorptionOrder		simultaneous, sequential
forceLongerDelay		true, false
distribution		1compartment, 2compartments, 3compartments
elimination		linear, MichaelisMenten
parametrization		rate, clearance

Parent-metabolite library

key		values
administration		bolus, infusion, oral, oralBolus
firstPassEffect		noFirstPassEffect, withDoseApportionment,
		withoutDoseApportionment
delay		noDelay, lagTime, transitCompartments
absorption		zeroOrder, firstOrder
transformation		unidirectional, bidirectional
parametrization		rate, clearance
parentDistribution		1compartment, 2compartments, 3compartments
parentElimination		linear, MichaelisMenten
metaboliteDistribution		1compartment, 2compartments, 3compartments
metaboliteElimination		linear, MichaelisMenten

TMDD library

key		values
administration		bolus, infusion, oral, oralBolus
delay		noDelay, lagTime, transitCompartments
absorption		zeroOrder, firstOrder
distribution		1compartment, 2compartments, 3compartments
tmddApproximation		MichaelisMenten, QE, QSS, full, Wagner,
		constantRtot, constantRtotIB, irreversibleBinding
output		totalLigandLtot, freeLigandL
parametrization		rate, clearance

TTE library

key		values
tteModel		exponential, Weibull, Gompertz, loglogistic,
		uniform, gamma, generalizedGamma
delay		true, false
numberOfEvents		singleEvent, repeatedEvents
typeOfEvent		intervalCensored, exact
dummyParameter		true, false

Count library

key		values
countDistribution		Poisson, binomial, negativeBinomial, betaBinomial,
		generalizedPoisson, geometric, hypergeometric,
		logarithmic, Bernoulli
zeroInflation		true, false
timeEvolution		constant, linear, exponential, Emax, Hill
parametrization		probabilityOfSuccess, averageNumberOfCounts

TGI library

key		values
shortcut		ClaretExponential, Simeoni, Stein, Wang,
		Bonate, Ribba, twoPopulation
initialTumorSize		asParameter, asRegressor
kinetics		true, false
model		linear, quadratic, exponential, generalizedExponential,
		exponentialLinear, Simeoni, Koch, logistic,
		generalizedLogistic, SimeoniLogisticHybrid, Gompertz,
		exponentialGompertz, vonBertalanffy, generalizedVonBertalanffy
additionalFeature		none, angiogenesis, immuneDynamics
treatment		none, pkModel, exposureAsRegressor, startAtZero,
		startTimeAsRegressor, armAsRegressor
killingHypothesis		logKill, NortonSimon
dynamics		firstOrder, MichaelisMenten, MichaelisMentenHill,
		exponentialKill, constant
resistance		ClaretExponential, resistantCells, none
delay		signalDistribution, cellDistribution, none
additionalTreatmentEffect		none, angiogenesisInhibition, immuneEffectorDecay

Examples

        R
    
if (FALSE) {
getLibraryModelName(library = "pk", filters = list(administration = "oral", delay = "lagTime", absorption = "firstOrder", distribution = "1compartment", elimination = "linear", parametrization = "clearance"))
# returns "lib:oral1_1cpt_TlagkaVCl.txt"
getLibraryModelName("pd", list(response = "turnover", drugAction = "productionStimulation"))
# returns c("lib:turn_input_Emax.txt", "lib:turn_input_gammaEmax.txt")
}

[Monolix - PKanalix - Simulx] Get the name of a library model given a list of library filters.