scholarly journals High-performance, robustly verified Monte Carlo simulation with FullMonte

2018 ◽  
Vol 23 (08) ◽  
pp. 1 ◽  
Author(s):  
Jeffrey Cassidy ◽  
Ali Nouri ◽  
Vaughn Betz ◽  
Lothar Lilge
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
High Performance

scholarly journals PK/PD Analysis of Marbofloxacin by Monte Carlo Simulation against Mycoplasma agalactiae in Plasma and Milk of Lactating Goats after IV, SC and SC-Long Acting Formulations Administration

Animals ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 1104
Author(s):  
Emilio Fernández-Varón ◽  
Edgar García-Romero ◽  
Juan M. Serrano-Rodríguez ◽  
Carlos M. Cárceles ◽  
Ana García-Galán ◽  
...  
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
High Performance ◽  
Small Ruminants ◽  
Area Under The Curve ◽  
Hplc Method ◽  
Surrogate Markers ◽  
Contagious Agalactia ◽  
Lactating Goats ◽  
Long Acting

Contagious agalactia is a mycoplasmosis affecting small ruminants that have become an important issue in many countries. However, PK/PD studies of antibiotics to treat this problem in lactating goats affected by Mycoplasma (M.) agalactiae, the main CA-causing mycoplasma are almost non-existent. The aims of this study were to evaluate the plasma and milk disposition of marbofloxacin in lactating goats after intravenous (IV), subcutaneous (SC) and subcutaneous poloxamer P407 formulations with and without carboxy-methylcellulose (SC-P407-CMC and SC-P407) administration. Marbofloxacin concentrations were analysed by the High Performance Liquid Chromatography (HPLC) method. Minimum inhibitory concentrations (MIC) of M. agalactiae field isolates from mastitic goat’s milk were used to calculate surrogate markers of efficacy. Terminal half-lives of marbofloxacin after IV, SC, SC-P407 and SC-P407-CMC administration were 7.12, 6.57, 13.92 and 12.19 h in plasma, and the half-lives of elimination of marbofloxacin in milk were 7.22, 7.16, 9.30 and 7.74 h after IV, SC, SC-P407 and SC-P407-CMC administration, respectively. Marbofloxacin penetration from the blood into the milk was extensive, with Area Under the Curve (AUCmilk/AUCplasma) ratios ranged 1.04–1.23, and maximum concentrations (Cmax-milk/Cmax-plasma) ratios ranged 0.72–1.20. The PK/PD surrogate markers of efficacy fAUC24/MIC and the Monte Carlo simulation show that marbofloxacin ratio (fAUC24/MIC > 125) using a 90% of target attainment rate (TAR) need a dose regimen between 8.4 mg/kg (SC) and 11.57 mg/kg (P407CMC) and should be adequate to treat contagious agalactia in lactating goats.

Pharmacokinetic/Pharmacodynamic Analysis of Meropenem for the Treatment of Nosocomial Pneumonia in Intracerebral Hemorrhage Patients by Monte Carlo Simulation

2017 ◽  
Vol 51 (11) ◽  
pp. 970-975 ◽  
Author(s):  
Lingti Kong ◽  
Yan Tang ◽  
Xiaohua Zhang ◽  
Guoyu Lu ◽  
Meiling Yu ◽  
...  
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Intracerebral Hemorrhage ◽  
Nosocomial Pneumonia ◽  
High Performance ◽  
Plasma Concentrations ◽  
Volume Of Distribution ◽  
Time Profile ◽  
Dosing Regimens ◽  
Total Body

Background: Nosocomial pneumonia (NP) is a frequent complication among patients with intracerebral hemorrhage (ICH). However, there are currently no pharmacokinetic (PK) and pharmacodynamic (PD) data to guide meropenem dosing in these patients. Objective: To investigate the PK/PD properties of meropenem in these patients and whether the usual dosing regimens of meropenem (2-hour infusion, 1 g, every 8 hours) was suitable. Methods: A total of 11 patients with a diagnosis of ICH complicated with NP were selected in the emergency internal medicine and treated with a 1-g/2-hours extended infusion model. The plasma concentrations of meropenem were determined by high-performance liquid chromatography. PK parameters were estimated by plasma concentration versus time profile using WinNonlin software. The probability of target attainments (PTAs) of meropenem at different minimum inhibitory concentrations (MICs) based on percentage time that concentrations were above the minimum inhibitory concentration (%T>MIC) value were performed by Monte Carlo simulation. Results: The volume of distribution and total body clearance of meropenem were 55.55 L/kg and 22.89 L/h, respectively. Using 40%T>MIC, PTA was >90% at MICs ≤4 µg/mL. Using 80% or 100%T>MIC, PTA was >90% only at MICs ≤1 µg/mL. Conclusions: The PK/PD profile of dosing regimens tested will assist in selecting the appropriate meropenem regimens for these patients. At a target of 40%T>MIC, the usual dosing regimens can provide good coverage for pathogens with MICs of ≤4 µg/mL. However, when a higher target (80% or 100%) is desired for difficult-to-treat infections, larger doses, prolonged infusions, shorter intervals, and/or combination therapy may be required.

scholarly journals A Sensitivity and Robustness Analysis of GPR and ANN for High-Performance Concrete Compressive Strength Prediction Using a Monte Carlo Simulation

2020 ◽  
Vol 12 (3) ◽  
pp. 830 ◽  
Author(s):  
Dong Van Dao ◽  
Hojjat Adeli ◽  
Hai-Bang Ly ◽  
Lu Minh Le ◽  
Vuong Minh Le ◽  
...  
Keyword(s):  
Monte Carlo Simulation ◽  
Compressive Strength ◽  
Monte Carlo ◽  
High Performance ◽  
Mean Squared Error ◽  
High Performance Concrete ◽  
Robustness Analysis ◽  
Gaussian Process Regression ◽  
Coefficient Of Determination ◽  
Input Parameters

This study aims to analyze the sensitivity and robustness of two Artificial Intelligence (AI) techniques, namely Gaussian Process Regression (GPR) with five different kernels (Matern32, Matern52, Exponential, Squared Exponential, and Rational Quadratic) and an Artificial Neural Network (ANN) using a Monte Carlo simulation for prediction of High-Performance Concrete (HPC) compressive strength. To this purpose, 1030 samples were collected, including eight input parameters (contents of cement, blast furnace slag, fly ash, water, superplasticizer, coarse aggregates, fine aggregates, and concrete age) and an output parameter (the compressive strength) to generate the training and testing datasets. The proposed AI models were validated using several standard criteria, namely coefficient of determination (R2), Root Mean Squared Error (RMSE), and Mean Absolute Error (MAE). To analyze the sensitivity and robustness of the models, Monte Carlo simulations were performed with 500 runs. The results showed that the GPR using the Matern32 kernel function outperforms others. In addition, the sensitivity analysis showed that the content of cement and the testing age of the HPC were the most sensitive and important factors for the prediction of HPC compressive strength. In short, this study might help in selecting suitable AI models and appropriate input parameters for accurate and quick estimation of the HPC compressive strength.

High-performance Monte Carlo Simulation of Multilayer Magnetic Films

2017 ◽  
Vol 9 (5) ◽  
pp. 05015-1-05015-4
Author(s):  
V. Yu. Kapitan ◽  
◽  
A. V. Perzhu ◽  
K. V. Nefedev ◽  
◽  
...  
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
High Performance ◽  
Magnetic Films
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