Amikacin » PTA » AUC/MIC

Source: R/simulate_amikacin_mc_pta_auc_mic_ratio.R

Amikacin » Probability of Target Attainment » AUC to MIC ratio

simulate_amikacin_mc_pta_auc_mic_ratio(
  PATID,
  AGE,
  HEIGHT,
  WEIGHT,
  GENDER,
  MODEL,
  CREATININE,
  AUCPERMIC,
  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').
CREATININE

Creatinine. Serum creatinine. Must be provided as numeric (min. 0.01, max. 15 mg/dL).
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 ).
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 1-8 'REGIMEN' values. Use the regimen helper function to define the REGIMEN values.

Details

Drug: Amikacin

Method: Monte Carlo simulation on the probabilities that a specific value of a pharmacodynamic index is achieved in case of different minimum inhibitory concentrations (MIC).

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

Examples

if (FALSE) {
simulate_amikacin_mc_pta_auc_mic_ratio(PATID = "Anonymous", 
    AGE = 35, HEIGHT = 155, 
    WEIGHT = 55, GENDER = "Female", 
    MODEL = "Saez Fernandez et al. (2019) - General ward", 
    CREATININE = 1.2, 
    AUCPERMIC = 100, 
    REGIMENS = list(list(
        DOSE = 200, INTERVAL = 16, 
        TINF = 0.5, set = "REGIMEN")))
}