PII-71The use of Beowulf cluster to accelerate the performance of Monte-Carlo parametric expectation maximization (MCPEM) algorithm in analyzing complex population pharmacokinetic/pharmacodynamic/efficacy data

2006 ◽  
Vol 79 (2) ◽  
pp. P54-P54 ◽  
Author(s):  
C NG ◽  
R BAUER
Keyword(s):  
Monte Carlo ◽  
Expectation Maximization ◽  
Population Pharmacokinetic ◽  
Efficacy Data ◽  
Beowulf Cluster ◽  
Complex Population

scholarly journals Population Pharmacokinetics of Continuous-Infusion Meropenem in Febrile Neutropenic Patients with Hematologic Malignancies: Dosing Strategies for Optimizing Empirical Treatment against Enterobacterales and P. aeruginosa

Pharmaceutics ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 785
Author(s):  
Pier Giorgio Cojutti ◽  
Anna Candoni ◽  
Davide Lazzarotto ◽  
Carla Filì ◽  
Maria Zannier ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Continuous Infusion ◽  
Hematologic Malignancies ◽  
Population Pharmacokinetic Analysis ◽  
Empirical Treatment ◽  
Pharmacokinetic Analysis ◽  
Population Pharmacokinetic ◽  
Dosing Strategies ◽  
Neutropenic Patients

A population pharmacokinetic analysis of continuous infusion (CI) meropenem was conducted in a prospective cohort of febrile neutropenic (FN) patients with hematologic malignancies. A non-parametric approach with Pmetrics was used for pharmacokinetic analysis and covariate evaluation. Monte Carlo simulations were performed for identifying the most appropriate dosages for empirical treatment against common Enterobacterales and P. aeruginosa. The probability of target attainment (PTA) of steady-state meropenem concentration (Css)-to-minimum inhibitory concentration (MIC) ratio (Css/MIC) ≥1 and ≥4 at the European Committee on Antimicrobial Susceptibility Testing (EUCAST) clinical breakpoint of 2 mg/L were calculated. Cumulative fraction of response (CFR) against Enterobacterales and P. aeruginosa were assessed as well. PTAs and CFRs ≥ 90% were considered optimal. A total of 61 patients with 178 meropenem Css were included. Creatinine clearance (CLCR) was the only covariate associated with meropenem clearance. Monte Carlo simulations showed that dosages of meropenem ranging between 1 g q8h and 1.25 g q6h by CI may grant optimal PTAs of Css/MIC ≥4 at the EUCAST clinical breakpoint. Optimal CFRs may be granted with these dosages against the Enterobacterales at Css/MIC ≥ 4 and against P. aeruginosa at Css/MIC ≥ 1. When dealing against P. aeruginosa at Css/MIC ≥ 4, only a dosage of 1.5 g q6h by CI may grant quasi-optimal CFR (around 80–87%). In conclusion, our findings suggest that dosages of meropenem ranging between 1 g q8h and 1.25 g q6h by CI may maximize empirical treatment against Enterobacterales and P. aeruginosa among FN patients with hematologic malignancies having different degree of renal function.

scholarly journals Population Pharmacokinetic Study of the Suitability of Standard Dosing Regimens of Amikacin in Critically Ill Patients with Open-Abdomen and Negative-Pressure Wound Therapy

2020 ◽  
Vol 64 (4) ◽  
Author(s):  
Cédric Carrié ◽  
Faustine Delzor ◽  
Stéphanie Roure ◽  
Vincent Dubuisson ◽  
Laurent Petit ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Body Weight ◽  
Monte Carlo Simulations ◽  
Critically Ill ◽  
Negative Pressure ◽  
Critically Ill Patients ◽  
Open Abdomen ◽  
Population Pharmacokinetic ◽  
Pressure Therapy ◽  
Dosing Regimens

ABSTRACT The aim was to assess the appropriateness of recommended regimens for empirical MIC coverage in critically ill patients with open-abdomen and negative-pressure therapy (OA/NPT). Over a 5-year period, every critically ill patient who received amikacin and who underwent therapeutic drug monitoring (TDM) while being treated by OA/NPT was retrospectively included. A population pharmacokinetic (PK) modeling was performed considering the effect of 10 covariates (age, sex, total body weight [TBW], adapted body weight [ABW], body surface area [BSA], modified sepsis-related organ failure assessment [SOFA] score, vasopressor use, creatinine clearance [CLCR], fluid balance, and amount of fluids collected by the NPT over the sampling day) in patients who underwent continuous renal replacement therapy (CRRT) or did not receive CRRT. Monte Carlo simulations were employed to determine the fractional target attainment (FTA) for the PK/pharmacodynamic [PD] targets (maximum concentration of drug [Cmax]/MIC ratio of ≥8 and a ratio of the area under the concentration-time curve from 0 to 24 h [AUC0–24]/MIC of ≥75). Seventy critically ill patients treated by OA/NPT (contributing 179 concentration values) were included. Amikacin PK concentrations were best described by a two-compartment model with linear elimination and proportional residual error, with CLCR and ABW as significant covariates for volume of distribution (V) and CLCR for CL. The reported V) in non-CRRT and CRRT patients was 35.8 and 40.2 liters, respectively. In Monte Carlo simulations, ABW-adjusted doses between 25 and 35 mg/kg were needed to reach an FTA of >85% for various renal functions. Despite an increased V and a wide interindividual variability, desirable PK/PD targets may be achieved using an ABW-based loading dose of 25 to 30 mg/kg. When less susceptible pathogens are targeted, higher dosing regimens are probably needed in patients with augmented renal clearance (ARC). Further studies are needed to assess the effect of OA/NPT on the PK parameters of antimicrobial agents.

scholarly journals Monte Carlo Simulation for Polychromatic X-Ray Fluorescence Computed Tomography with Sheet-Beam Geometry

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Shanghai Jiang ◽  
Peng He ◽  
Luzhen Deng ◽  
Mianyi Chen ◽  
Biao Wei
Keyword(s):  
Computed Tomography ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Expectation Maximization ◽  
Huge Amount ◽  
X Ray ◽  
Beam Geometry ◽  
Weight Concentration ◽  
Imaging Model ◽  
Maximum Likelihood Expectation Maximization

X-ray fluorescence computed tomography (XFCT) based on sheet beam can save a huge amount of time to obtain a whole set of projections using synchrotron. However, it is clearly unpractical for most biomedical research laboratories. In this paper, polychromatic X-ray fluorescence computed tomography with sheet-beam geometry is tested by Monte Carlo simulation. First, two phantoms (A and B) filled with PMMA are used to simulate imaging process through GEANT 4. Phantom A contains several GNP-loaded regions with the same size (10 mm) in height and diameter but different Au weight concentration ranging from 0.3% to 1.8%. Phantom B contains twelve GNP-loaded regions with the same Au weight concentration (1.6%) but different diameter ranging from 1 mm to 9 mm. Second, discretized presentation of imaging model is established to reconstruct more accurate XFCT images. Third, XFCT images of phantoms A and B are reconstructed by filter back-projection (FBP) and maximum likelihood expectation maximization (MLEM) with and without correction, respectively. Contrast-to-noise ratio (CNR) is calculated to evaluate all the reconstructed images. Our results show that it is feasible for sheet-beam XFCT system based on polychromatic X-ray source and the discretized imaging model can be used to reconstruct more accurate images.

scholarly journals A quantile variant of the expectation–maximization algorithm and its application to parameter estimation with interval data

2018 ◽  
Vol 12 (3) ◽  
pp. 253-272 ◽  
Author(s):  
Chanseok Park
Keyword(s):  
Monte Carlo ◽  
Expectation Maximization ◽  
Likelihood Function ◽  
Expectation Maximization Algorithm ◽  
Parametric Models ◽  
Maximum Likelihood Estimates ◽  
Computational Technique ◽  
Stable Convergence ◽  
Explicit Integration ◽  
Monte Carlo Expectation Maximization

The expectation–maximization algorithm is a powerful computational technique for finding the maximum likelihood estimates for parametric models when the data are not fully observed. The expectation–maximization is best suited for situations where the expectation in each E-step and the maximization in each M-step are straightforward. A difficulty with the implementation of the expectation–maximization algorithm is that each E-step requires the integration of the log-likelihood function in closed form. The explicit integration can be avoided by using what is known as the Monte Carlo expectation–maximization algorithm. The Monte Carlo expectation–maximization uses a random sample to estimate the integral at each E-step. But the problem with the Monte Carlo expectation–maximization is that it often converges to the integral quite slowly and the convergence behavior can also be unstable, which causes computational burden. In this paper, we propose what we refer to as the quantile variant of the expectation–maximization algorithm. We prove that the proposed method has an accuracy of [Formula: see text], while the Monte Carlo expectation–maximization method has an accuracy of [Formula: see text]. Thus, the proposed method possesses faster and more stable convergence properties when compared with the Monte Carlo expectation–maximization algorithm. The improved performance is illustrated through the numerical studies. Several practical examples illustrating its use in interval-censored data problems are also provided.

scholarly journals Bone Penetration of Amoxicillin and Clavulanic Acid Evaluated by Population Pharmacokinetics and Monte Carlo Simulation

2009 ◽  
Vol 53 (6) ◽  
pp. 2569-2578 ◽  
Author(s):  
Cornelia B. Landersdorfer ◽  
Martina Kinzig ◽  
Jürgen B. Bulitta ◽  
Friedrich F. Hennig ◽  
Ulrike Holzgrabe ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Cortical Bone ◽  
Population Pharmacokinetics ◽  
Clavulanic Acid ◽  
Cancellous Bone ◽  
Pharmacokinetic Analysis ◽  
Population Pharmacokinetic ◽  
Bone Infections ◽  
Drug Concentrations ◽  
Amoxicillin Clavulanic Acid

ABSTRACT Amoxicillin (amoxicilline)-clavulanic acid has promising activity against pathogens that cause bone infections. We present the first evaluation of the bone penetration of a beta-lactam by population pharmacokinetics and pharmacodynamic profiling via Monte Carlo simulations. Twenty uninfected patients undergoing total hip replacement received a single intravenous infusion of 2,000 mg/200 mg amoxicillin-clavulanic acid before surgery. Blood and bone specimens were collected. Bone samples were pulverized under liquid nitrogen with a cryogenic mill, including an internal standard. The drug concentrations in serum and total bone were analyzed by liquid chromatography-tandem mass spectrometry. We used NONMEM and S-ADAPT for population pharmacokinetic analysis and a target time of the non-protein-bound drug concentration above the MIC for ≥50% of the dosing interval for near-maximal bactericidal activity in serum. The median of the ratio of the area under the curve (AUC) for bone/AUC for serum was 20% (10th to 90th percentile for between-subject variability [variability], 16 to 25%) in cortical bone and 18% (variability, 11 to 29%) in cancellous bone for amoxicillin and 15% (variability, 11 to 21%) in cortical bone and 10% (variability, 5.1 to 21%) in cancellous bone for clavulanic acid. Analysis in S-ADAPT yielded similar results. The equilibration half-lives between serum and bone were 12 min for amoxicillin and 14 min for clavulanic acid. For a 30-min infusion of 2,000 mg/200 mg amoxicillin-clavulanic acid every 4 h, amoxicillin achieved robust (≥90%) probabilities of target attainment (PTAs) for MICs of ≤12 mg/liter in serum and 2 to 3 mg/liter in bone and population PTAs above 95% against methicillin-susceptible Staphylococcus aureus in bone and serum. The AUC of amoxicillin-clavulanic acid was 5 to 10 times lower in bone than in serum, and amoxicillin-clavulanic acid achieved a rapid equilibrium and favorable population PTAs against pathogens commonly encountered in bone infections.

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