Amikacin » Bayesian » AUC/MIC

Amikacin » Bayesian adaptive dosing » AUC to MIC ratio

simulate_amikacin_bayesian_auc_mic_ratio(
  PATID,
  AGE,
  HEIGHT,
  WEIGHT,
  GENDER,
  MODEL,
  MIC,
  AUCPERMIC,
  HISTORY,
  REGIMENS
)

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 ('Saez Fernandez et al. (2019) - General ward').
MIC	MIC. Minimum Inhibitory Concentration (MIC). Must be provided as numeric (min. 0.01, max. 1024 mg/L).
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 ).
HISTORY	Historical Records. Must be provided as list of 3-48 'HISTCREATININE', 'HISTDOSE' or 'HISTCONCENTRATION' values.
REGIMENS	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 'REGIMEN' values. Use the regimen helper function to define the REGIMEN values.

Details

Drug: Amikacin

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 concentration-time curve to minimum inhibitory concentration ratio.

References

• Saez Fernandez et al. (2019): Evaluation of renal function equations to predict amikacin clearance. In. Expert Review of Clinical Pharmacology. https://www.tandfonline.com/doi/full/10.1080/17512433.2019.1637253

• K. Soetaert, T. Petzoldt (2010): Inverse Modelling, Sensitivity and Monte Carlo Analysis in R Using Package FME. In. Journal of Statistical Software. https://www.jstatsoft.org/article/view/v033i03

Examples

if (FALSE) {
simulate_amikacin_bayesian_auc_mic_ratio(PATID = "Anonymous", 
    AGE = 65, HEIGHT = 175, 
    WEIGHT = 75, GENDER = "Male", 
    MODEL = "Saez Fernandez et al. (2019) - General ward", 
    MIC = 1, AUCPERMIC = 50, 
    HISTORY = list(list(
        DATETIME = structure(1601870400, class = c("POSIXct", 
        "POSIXt"), tzone = ""), 
        DOSE = 200, TINF = 0.5, 
        set = "HISTDOSE"), 
        list(DATETIME = structure(1601881200, class = c("POSIXct", 
        "POSIXt"), tzone = ""), 
            DOSE = 300, 
            TINF = 0.5, 
            set = "HISTDOSE"), 
        list(DATETIME = structure(1601899200, class = c("POSIXct", 
        "POSIXt"), tzone = ""), 
            DOSE = 400, 
            TINF = 0.5, 
            set = "HISTDOSE"), 
        list(DATETIME = structure(1601942400, class = c("POSIXct", 
        "POSIXt"), tzone = ""), 
            DOSE = 500, 
            TINF = 0.5, 
            set = "HISTDOSE"), 
        list(DATETIME = structure(1601866800, class = c("POSIXct", 
        "POSIXt"), tzone = ""), 
            CREATININE = 0.9, 
            set = "HISTCREATININE"), 
        list(DATETIME = structure(1601906400, class = c("POSIXct", 
        "POSIXt"), tzone = ""), 
            CREATININE = 0.7, 
            set = "HISTCREATININE"), 
        list(DATETIME = structure(1601888400, class = c("POSIXct", 
        "POSIXt"), tzone = ""), 
            CONCENTRATION = 8, 
            set = "HISTCONCENTRATION"), 
        list(DATETIME = structure(1601890200, class = c("POSIXct", 
        "POSIXt"), tzone = ""), 
            CONCENTRATION = 7, 
            set = "HISTCONCENTRATION"), 
        list(DATETIME = structure(1601906400, class = c("POSIXct", 
        "POSIXt"), tzone = ""), 
            CONCENTRATION = 10, 
            set = "HISTCONCENTRATION")), 
    REGIMENS = list(list(
        set = "REGIMEN", 
        DOSE = 100, INTERVAL = 8, 
        TINF = 0.5), 
        list(set = "REGIMEN", 
            DOSE = 100, 
            INTERVAL = 12, 
            TINF = 0.5), 
        list(set = "REGIMEN", 
            DOSE = 125, 
            INTERVAL = 8, 
            TINF = 0.5), 
        list(set = "REGIMEN", 
            DOSE = 125, 
            INTERVAL = 12, 
            TINF = 0.5), 
        list(set = "REGIMEN", 
            DOSE = 150, 
            INTERVAL = 8, 
            TINF = 0.5), 
        list(set = "REGIMEN", 
            DOSE = 150, 
            INTERVAL = 12, 
            TINF = 0.5), 
        list(set = "REGIMEN", 
            DOSE = 175, 
            INTERVAL = 8, 
            TINF = 0.5), 
        list(set = "REGIMEN", 
            DOSE = 175, 
            INTERVAL = 12, 
            TINF = 0.5), 
        list(set = "REGIMEN", 
            DOSE = 200, 
            INTERVAL = 8, 
            TINF = 0.5), 
        list(set = "REGIMEN", 
            DOSE = 200, 
            INTERVAL = 12, 
            TINF = 0.5), 
        list(set = "REGIMEN", 
            DOSE = 400, 
            INTERVAL = 24, 
            TINF = 0.5), 
        list(set = "REGIMEN", 
            DOSE = 400, 
            INTERVAL = 36, 
            TINF = 0.5), 
        list(set = "REGIMEN", 
            DOSE = 500, 
            INTERVAL = 24, 
            TINF = 0.5), 
        list(set = "REGIMEN", 
            DOSE = 500, 
            INTERVAL = 36, 
            TINF = 0.5), 
        list(set = "REGIMEN", 
            DOSE = 600, 
            INTERVAL = 24, 
            TINF = 0.5), 
        list(set = "REGIMEN", 
            DOSE = 600, 
            INTERVAL = 36, 
            TINF = 0.5), 
        list(set = "REGIMEN", 
            DOSE = 700, 
            INTERVAL = 24, 
            TINF = 0.5), 
        list(set = "REGIMEN", 
            DOSE = 700, 
            INTERVAL = 36, 
            TINF = 0.5), 
        list(set = "REGIMEN", 
            DOSE = 800, 
            INTERVAL = 24, 
            TINF = 0.5), 
        list(set = "REGIMEN", 
            DOSE = 800, 
            INTERVAL = 36, 
            TINF = 0.5)))
}