Voriconazole » Bayesian » fAUC/MIC

Voriconazole » Bayesian adaptive dosing » fAUC to MIC ratio

simulate_voriconazole_bayesian_fauc_mic_ratio(
  PATID,
  AGE,
  HEIGHT,
  WEIGHT,
  GENDER,
  MODEL,
  RIFAMPICIN,
  SEVEREHEPATICCHOLESTASIS,
  AUCPERMIC,
  ORALORIVBAREHISTORY,
  ORALORIVORKGREGIMENS
)

Arguments

PATID	Patient Identifier. User-provided free text (such as patient id, name or alias) to identify related simulations. Must be provided as string.
AGE	Age. Age of the patient in years. Must be provided as numeric (min. 18, max. 120 year).
HEIGHT	Height. Height of the patient. Must be provided as numeric (min. 100, max. 250 cm).
WEIGHT	Weight. Actual body weight of the patient. Must be provided as numeric (min. 20, max. 500 kg).
GENDER	Sex. Patient's sex for clinical decision-making. Must be provided as string ('Male' or 'Female').
MODEL	Model for population of interest. Pharmacokinetic model to be used for specific patient type during simulations. Must be provided as string ('Pascual et al. (2012) - patients with invasive fungal infections').
RIFAMPICIN	Concurrent rifampicin. Presence of rifampicin coadministration. Must be provided as string ('No' or 'Yes').
SEVEREHEPATICCHOLESTASIS	Severe hepatic cholestasis. Severe hepatic cholestasis is defined as any liver function tests > 20 times the upper limit of normal (e.g. alkaline phosphatase, AST, ALT or GGT). Must be provided as string ('No' or 'Yes').
AUCPERMIC	AUC to MIC ratio target. The PK/PD target can be provided as 24 hour area under the concentration-time curve to minimum inhibitory concentration ratio (AUC/MIC). Must be provided as numeric (min. 10, max. 2000 ).
ORALORIVBAREHISTORY	Historical Records. Must be provided as list of 2-48 'HISTDOSE', 'HISTORALDOSE' or 'HISTCONCENTRATION' values.
ORALORIVORKGREGIMENS	Dosing Regimens. List of dosing regimens to be used in simulating target attainment, from which the dosing regimen with the smallest absolute difference from the desired target will be automatically selected. Must be provided as list of 1-20 'KGREGIMEN', 'REGIMEN' or 'ORALREGIMEN' values. Use the regimen helper function to define the REGIMEN values.

Details

Drug: Voriconazole

Method: Estimate the pharmacokinetic parameters of the patient from past concentrations with Bayesian inverse modeling, then use that information to predict the steady state concentrations for multiple dosing regimens and select the optimal one, with regard to the target pharmacodynamic index.

PK/PD target: 24 hour area under the free concentration-time curve to minimum inhibitory concentration ratio.

References

• Pascual, Andres et al. (2012): Challenging recommended oral and intravenous voriconazole doses for improved efficacy and safety: population pharmacokinetics-based analysis of adult patients with invasive fungal infections. In. Clinical Infectious Diseases. https://pubmed.ncbi.nlm.nih.gov/22610925

Examples

if (FALSE) {
simulate_voriconazole_bayesian_fauc_mic_ratio(PATID = "Anonymous", 
    AGE = 35, HEIGHT = 155, 
    WEIGHT = 55, GENDER = "Female", 
    MODEL = "Pascual et al. (2012) - patients with invasive fungal infections", 
    RIFAMPICIN = "No", 
    SEVEREHEPATICCHOLESTASIS = "No", 
    AUCPERMIC = 25, ORALORIVBAREHISTORY = list(
        list(DATETIME = structure(1633579200, class = c("POSIXct", 
        "POSIXt"), tzone = ""), 
            DOSE = 800, 
            set = "HISTORALDOSE"), 
        list(DATETIME = structure(1633622400, class = c("POSIXct", 
        "POSIXt"), tzone = ""), 
            DOSE = 400, 
            TINF = 1.5, 
            set = "HISTDOSE"), 
        list(DATETIME = structure(1633593600, class = c("POSIXct", 
        "POSIXt"), tzone = ""), 
            CONCENTRATION = 2.3, 
            set = "HISTCONCENTRATION"), 
        list(DATETIME = structure(1633665600, class = c("POSIXct", 
        "POSIXt"), tzone = ""), 
            CONCENTRATION = 2, 
            set = "HISTCONCENTRATION")), 
    ORALORIVORKGREGIMENS = list(
        list(set = "REGIMEN", 
            DOSE = 100, 
            INTERVAL = 12, 
            TINF = 1.5), 
        list(set = "ORALREGIMEN", 
            DOSE = 100, 
            INTERVAL = 12), 
        list(set = "REGIMEN", 
            DOSE = 200, 
            INTERVAL = 12, 
            TINF = 1.5), 
        list(set = "ORALREGIMEN", 
            DOSE = 200, 
            INTERVAL = 12), 
        list(set = "REGIMEN", 
            DOSE = 300, 
            INTERVAL = 12, 
            TINF = 1.5), 
        list(set = "ORALREGIMEN", 
            DOSE = 300, 
            INTERVAL = 12)))
}