R/simulate_amikacin_bayesian_cmin_mic_ratio.R
simulate_amikacin_bayesian_cmin_mic_ratio.Rd
Amikacin » Bayesian adaptive dosing » Total minimum concentration to MIC ratio
simulate_amikacin_bayesian_cmin_mic_ratio( PATID, AGE, HEIGHT, WEIGHT, GENDER, MODEL, MIC, CMINPERMIC, HISTORY, REGIMENS )
PATID | Patient Identifier. User-provided free text (such as patient id, name or alias) to identify related simulations. Must be provided as string. |
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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). |
CMINPERMIC | Minimum concentration to MIC ratio target. The PK/PD target can be provided as minimum concentration to minimum inhibitory concentration ratio (Cmin/MIC). Must be provided as numeric (min. 0.1, max. 50 ). |
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 |
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: Minimum concentration (mg/L) to minimum inhibitory concentration ratio (mg/L).
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
if (FALSE) { simulate_amikacin_bayesian_cmin_mic_ratio(PATID = "Anonymous", AGE = 65, HEIGHT = 175, WEIGHT = 75, GENDER = "Male", MODEL = "Saez Fernandez et al. (2019) - General ward", MIC = 1, CMINPERMIC = 5, 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 = 6, TINF = 0.5), list(set = "REGIMEN", DOSE = 100, INTERVAL = 8, TINF = 0.5), list(set = "REGIMEN", DOSE = 200, INTERVAL = 6, TINF = 0.5), list(set = "REGIMEN", DOSE = 200, INTERVAL = 8, TINF = 0.5), list(set = "REGIMEN", DOSE = 300, INTERVAL = 6, TINF = 0.5), list(set = "REGIMEN", DOSE = 300, INTERVAL = 8, TINF = 0.5), list(set = "REGIMEN", DOSE = 300, INTERVAL = 12, TINF = 0.5), list(set = "REGIMEN", DOSE = 400, INTERVAL = 6, TINF = 0.5), list(set = "REGIMEN", DOSE = 400, INTERVAL = 8, TINF = 0.5), list(set = "REGIMEN", DOSE = 400, 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))) }