Statistical analysis of bioavailability studies: Parametric and nonparametric confidence intervals

For a two-way cross-over design, which appears to be the most common experimental design in bioavailability studies, 95%-confidence limits for expected bioavailability can be obtained by classical analysis of variance (ANOVA). If symmetry of the confidence interval is desired about zero (differences) or unity (ratios) rather than about the corresponding point estimator, Westlake's modification can be used. Two nonparametric methods and their adaptations to bioavailability ratios are reviewed, one based on Wilcoxon's signed rank test (Tukey), and the other on Pitman's permutation test. The necessary assumptions and the merits of these procedures are discussed. The methods are illustrated by an example of a comparative bioavailability study. A FORTRAN program facilitating the procedures is available from the authors upon request.     

Propagation of uncertainty in nasal spray in vitro performance models using Monte Carlo simulation: Part I. model prediction using Monte Carlo Simulation

Design of experiment (DOE) methodology can provide a complete evaluation of the influences of nasal spray activation and formulation properties on delivery performance which makes it a powerful tool for product design purposes. Product performance models are computed from complex expressions containing multiple factor terms and response terms. Uncertainty in the regression model can be propagated using Monte Carlo simulation. In this study, four input factors, actuation stroke length, actuation velocity, concentration of gelling agent, and concentration of surfactant were investigated for their influences on measured responses of spray pattern, plume width, droplet size distribution (DSD), and impaction force. Quadratic models were calculated and optimized using a Box–Behnken experimental design to describe the relationship between factors and responses. Assuming that the models perfectly represent the relationship between input variables and the measured responses, the propagation of uncertainty in both input variables and response measurements on model prediction was performed using Monte Carlo simulations. The Monte Carlo simulations presented in this article illustrate the propagation of uncertainty in model predictions. The most influential input variable variances on the product performance variance were identified, which could help prioritize input variables in terms of importance during continuous improvement of nasal spray product design. This work extends recent Monte Carlo simulations of process models to the realm of product development models. © 2009 Wiley-Liss, Inc. and the American Pharmacists Association J Pharm Sci 99: 2114–2122, 2010     

Pharmacodynamic evaluation of biapenem in peritoneal fluid using population pharmacokinetic modelling and Monte Carlo simulation

This study evaluated the pharmacodynamics of biapenem in peritoneal fluid (PF). Biapenem (300 or 600mg) was administered via a 0.5-h infusion to 19 patients before abdominal surgery. Venous blood and PF samples were obtained after 0.5, 1, 2, 3, 4, 5 and 6h. Drug concentration data (108 plasma samples and 105 PF samples) were analysed using population pharmacokinetic modelling. A three-compartment model fits the data, with creatinine clearance (CL(Cr)) as the most significant covariate: CL (L/h)=0.036xCL(Cr)+4.88, V1 (L)=6.95, Q2 (L/h)=2.05, V2 (L)=3.47, Q3 (L/h)=13.7 and V3 (L)=5.91, where CL is the clearance, Q2 and Q3 are the intercompartmental clearances, and V1, V2 and V3 are the volumes of distribution of the central, peripheral and peritoneal compartments, respectively. A Monte Carlo simulation using the pharmacokinetic model showed the probabilities of attaining the bactericidal exposure target (30% of the time above the minimum inhibitory concentration (T>MIC)) in PF were greater than or equal to those in plasma. In the cases of CL(Cr)=90 and 60mL/min, the site-specific pharmacodynamic-derived breakpoints (the highest MIC values at which the probabilities of target attainment in PF were >/=90%) were 2mug/mL for 300mg every 12h, 4mug/mL for biapenem 300mg every 8h (q8h) and 8mug/mL for 600mg q8h. Thus, these results should support the clinical use of biapenem as a treatment for intra-abdominal infections and facilitate the design of the dosing regimen.     

Bioavailability estimation by semisimultaneous drug administration: a Monte Carlo simulation study

The performance of a novel method for determination of drug absorption characteristics was evaluated by Monte Carlo simulations. In bioavailability studies with use of this method, the test and the reference doses are administered within a time interval of hours. Estimates of bioavailability are obtained by fitting an appropriate model to the concentration-time profile, which in its terminal portion is thus the summed concentration of the two doses. Drugs with different properties, mimicked by varying the kinetic rate constants (ka, lambda 1 and lambda 2), and experimental designs with different sets of conditions regarding the interval between doses, dose ratio, dose order, and duration of sampling, were simulated to determine what factors govern parameter estimation. The absorption characteristics of the simulated drugs could be adequately determined in experiments lasting for 12 hr or less, provided that a proper design was used. Fitting of a simpler or a more complex disposition model produced estimates with similar accuracy and precision to those noted with the true model. For some conditions the use of an improper absorption model resulted in slightly reduced accuracy, but as these fits were poor there was a clear need to try other models. In another set of simulations the use of the proposed method to assess the relative availability of two extravascular doses was evaluated. The relative rate and extent of absorption could be estimated with good precision for two formulations exhibiting a rapid to moderate rate of absorption.     

Optimal dose finding of garenoxacin based on population pharmacokinetics/pharmacodynamics and Monte Carlo simulation

Purpose  

Garenoxacin, a novel des-F(6)-quinolone, possesses potent antibacterial activity against infectious pathogens in the respiratory tract. Population pharmacokinetic/pharmacodynamic (PK/PD) modeling and Monte Carlo simulations were used to optimize garenoxacin dosage regimens.     

A sequential Monte Carlo approach to derive sampling times and windows for population pharmacokinetic studies

Here we present a sequential Monte Carlo approach that can be used to find optimal designs. Our focus is on the design of population pharmacokinetic studies where the derivation of sampling windows is required, along with the optimal sampling schedule. The search is conducted via a particle filter which traverses a sequence of target distributions artificially constructed via an annealed utility. The algorithm derives a catalog of highly efficient designs which, not only contain the optimal, but can also be used to derive sampling windows. We demonstrate our approach by designing a hypothetical population pharmacokinetic study, and compare our results with those obtained via a simulation method from the literature.     

Ceftazidime dosage regimen in intensive care unit patients: from a population pharmacokinetic approach to clinical practice via Monte Carlo simulations

AIM

To predict the ceftazidime dosage regimen as a function of the glomerular filtration rate expressed by the modification of the diet in renal disease (MDRD), reason for admission and mechanical ventilation in intensive care unit (ICU) patients to treat Pseudomonas aeruginosa pneumonia.

METHOD

A published and qualified population pharmacokinetic model was used to perform Monte Carlo simulations of ceftazidime concentrations. The serum target of 40–100 mg l⁻¹ was defined based on the minimal inhibitory concentration (MIC), the European break point (EBP), the pulmonary drug diffusion and toxicity. The recommended dosage regimens were based on the maximum percentile of the patients with simulated steady state concentrations reaching the target.

RESULTS

Steady-state was reached at 72 h whatever the MDRD. The simulations of serum concentrations generated higher percentiles of the population reaching the target after continuous administration. We recommend a 4 g continuous dose after the usual 2 g loading dose for patients with MDRD from 10 to 30 ml min⁻¹, 6 g for MDRD between 40 and 80 ml min⁻¹, 8 g for MDRD from 90 to 110 ml min⁻¹, 10 g for MDRD from 120 to 190 ml min⁻¹ and 12 g day⁻¹ for patients with MDRD higher than 200 ml min⁻¹.

CONCLUSION

Our study demonstrated that in ICU patients for a given MDRD, steady-state takes longer to reach in polytrauma patients than in patients with medical or post surgery reasons for admission. Continuous infusion ensures that a higher percentage of patients reaches the target than the same dose given by discontinuous administration and this only depends on MDRD.     

Estimation of ligand binding parameters by simultaneous fitting of association and dissociation data: a Monte Carlo simulation study

A new procedure for analysis of ligand binding kinetics was evaluated by Monte Carlo simulations. In this, all association and dissociation data were fitted simultaneously to a set of nonlinear equations. This should have several advantages over more conventional methods; data are better used in a single fitting procedure in which the degrees of freedom are maximized and the error term is spread over more observations; all relevant parameters (Bmax, k1, and k-1) are obtained directly; values obtained from measurements are not treated as errorless; and it yields a single residual term that can be used for statistical comparison among binding models and/or experiments. We have compared this approach with the common practice of analyzing the association and dissociation phases separately, either by nonlinear regression or by linear regression after suitable transformations. With respect to both the precision and accuracy of parameter estimates, the simultaneous procedure was superior to the other two methods. The properties of the simultaneous procedure were further investigated, concerning both parameter estimation and the probability of reliably detecting a second binding site. For the latter, the relative density of receptor subtypes and the dissociation rate constants were found to be of major importance, whereas association rate constants and ligand concentration were of minor importance in this respect. The probability of resolving two sites by kinetic or equilibrium data under similar conditions with the aid of a single labeled ligand was examined. When the selectivity of the ligand was low, the resolution was found to be more probable when based on kinetic, rather than equilibrium, data. This was true at higher selectivities as well, provided kinetic data were obtained at two different ligand concentrations.     

哌拉西林他唑巴坦在肾内科患者中的群体药动学和蒙特卡罗模拟

目的:建立哌拉西林他唑巴坦在肾内科患者中的群体药动学模型,应用蒙特卡罗模拟优化其给药方案,以促进个体化给药.方法:采用高效液相色谱法测定50名肾内科患者静脉滴注哌拉西林-他唑巴坦的血清浓度310例次并收集相关临床指标,运用非线性混合效应模型(NONMEM)程序建立群体药动学模型.采用蒙特卡罗模拟(Monte Carlo simulation, MCS)比较哌拉西林他唑巴坦的不同给药方案对不同MIC群体的药效学目标到达.结果:哌拉西林、他唑巴坦的药动学符合一室模型,群体典型值及个体间差异(Between Subject Variability,BSV)分别为:哌拉西林CL/F=13.74 L·h^-1,BSV=11.1%;V/F=21.69 L,BSV=8.0%,他唑巴坦CL/F=9.32 L·h^-1, BSV=9.11%;V/F=16.0 L, BSV=5.28%;固定效应参数中,肌酐清除率对参数有影响.对于MIC值较大的细菌,延长输注的给药方案获得了更高的目标的累积反应分数(CFR).结论:群体药动学模型和蒙特卡罗模拟,可为调整哌拉西林他唑巴坦的治疗方案提供有效的分析手段.     

Glycopeptides and glycodepsipeptides in clinical development: a comparative review of their antibacterial spectrum, pharmacokinetics and clinical efficacy

Hemi-synthetic derivatives of glycopeptides have demonstrated bactericidal activity towards Gram-positive bacteria, including vancomycin-resistant strains (oritavancin and telavancin), and a prolonged half-life, allowing for once-daily (oritavancin and telavancin) or once-weekly (dalbavancin) administration. These compounds have proved effective for the treatment of infections caused by multidrug-resistant Gram-positive bacteria, including complicated skin and skin structure infections (oritavancin, telavancin and dalbavancin), bacteremia (oritavancin and dalbavancin) and nosocomial pneumonia. This review compares the antibacterial activity and clinical activity of three glycopeptides, oritavancin, telavancin and dalbavancin, and the natural lipoglycopeptide, ramoplanin, which, being unstable in the bloodstream, is administered orally to treat Clostridium difficile colitis and for digestive tract decontamination. All of these compounds, with the exception of oritavancin, have received Fast Track designation from the FDA because of their clinical efficacy.     

Evaluating biapenem dosage regimens in intensive care unit patients with Pseudomonas aeruginosa infections: a pharmacokinetic/pharmacodynamic analysis using Monte Carlo simulation

This study was conducted to identify optimal dosage regimens and estimate pharmacokinetic/pharmacodynamic (PK/PD) characteristics of short-infusion (SI) versus extended-infusion (EI) biapenem against Pseudomonas aeruginosa infections in Chinese intensive care unit (ICU) patients. A total of 85 strains of P. aeruginosa were collected, and the minimum inhibitory concentration (MIC) of biapenem was measured by the serial two-fold agar dilution method. We designed four frequently used clinical regimens: biapenem 300?mg I.V. q12h, q8h, and q6h, and 600?mg q12h. The Monte Carlo Simulation (MCS) was performed using previously published pharmacokinetic data to calculate the probability of target attainment (PTA) and the cumulative fraction of response (CFR) of these regimens as an SI (0.5?h) and an EI (1?h, 2?h, 3?h, and 4?h).For a target of 40%fT_>MIC (serum drug concentration remains above the MIC for a dosing period), none of the regimens achieved any CFRs>90% for P. aeruginosa, multidrug–resistant P. aeruginosa (MDR-PA) and even non–MDR-PA. The traditional biapenem SI regimens most commonly seen in clinical practice were insufficient in treating both MDR and non-MDR P. aeruginosa in ICU patients. However, biapenem 600?mg q12h over 2–4?h EI regimens could achieve CFR>90% with 20%fT_>MIC. Clinical trials should aim to validate the potentially greater PK/PD index with higher, more frequent doses and longer extended infusions.     

Monte Carlo simulation in the evaluation of susceptibility breakpoints: predicting the future: insights from the society of infectious diseases pharmacists

Appropriate treatment with antimicrobials involves factors we cannot control. Factors such as interpatient variability in drug exposure, the minimum inhibitory concentration (MIC) of the infecting pathogen, and the patient's clinical status clearly affect the therapeutic response. Despite these uncertainties, we can estimate the probability of attaining a successful therapeutic outcome in the context of factors that are within our control. Chief among these are drug, dose, and the dosing interval. One way to predict the probability of a positive therapeutic outcome is through the use of an integrated pharmacokinetic-pharmacodynamic stochastic model. Pharmacokinetic-pharmacodynamic target attainment analyses using Monte Carlo simulation to integrate interpatient variability in drug exposure, drug potency, and in vivo exposure targets predictive of positive therapeutic outcomes are influencing antibacterial susceptibility breakpoints at home and abroad. The consequences of this paradigm shift are far reaching, affecting the commercial concerns of drug and susceptibility testing device manufacturers, perceptions about antimicrobial resistance, and ultimately patient care decisions.     

Comparative performance of two quantitative safety signalling methods: implications for use in a pharmacovigilance department.

BACKGROUND AND OBJECTIVES: There is increasing interest in using disproportionality-based signal detection methods to support postmarketing safety surveillance activities. Two commonly used methods, empirical Bayes multi-item gamma Poisson shrinker (MGPS) and proportional reporting ratio (PRR), perform differently with respect to the number and types of signals detected. The goal of this study was to compare and analyse the performance characteristics of these two methods, to understand why they differ and to consider the practical implications of these differences for a large, industry-based pharmacovigilance department. METHODS: We compared the numbers and types of signals of disproportionate reporting (SDRs) obtained with MGPS and PRR using two postmarketing safety databases and a simulated database. We recorded signal counts and performed a qualitative comparison of the drug-event combinations signalled by the two methods as well as a sensitivity analysis to better understand how the thresholds commonly used for these methods impact their performance. RESULTS: PRR detected more SDRs than MGPS. We observed that MGPS is less subject to confounding by demographic factors because it employs stratification and is more stable than PRR when report counts are low. Simulation experiments performed using published empirical thresholds demonstrated that PRR detected false-positive signals at a rate of 1.1%, while MGPS did not detect any statistical false positives. In an attempt to separate the effect of choice of signal threshold from more fundamental methodological differences, we performed a series of experiments in which we modified the conventional threshold values for each method so that each method detected the same number of SDRs for the example drugs studied. This analysis, which provided quantitative examples of the relationship between the published thresholds for the two methods, demonstrates that the signalling criterion published for PRR has a higher signalling frequency than that published for MGPS. DISCUSSION AND CONCLUSION: The performance differences between the PRR and MGPS methods are related to (i) greater confounding by demographic factors with PRR; (ii) a higher tendency of PRR to detect false-positive signals when the number of reports is small; and (iii) the conventional thresholds that have been adapted for each method. PRR tends to be more 'sensitive' and less 'specific' than MGPS. A high-specificity disproportionality method, when used in conjunction with medical triage and investigation of critical medical events, may provide an efficient and robust approach to applying quantitative methods in routine postmarketing pharmacovigilance.     

Comparison of probability of target attainment calculated by Monte Carlo simulation with meropenem clinical and microbiological response for the treatment of complicated skin and skin structure infections

Monte Carlo simulation is often used to predict the cumulative fraction of response (CFR) for antibiotics, but the relevance of these predictions to outcomes in humans has not been well studied. We compared the CFR for meropenem 500 mg every 8h against pathogens causing complicated skin and skin structure infections from a randomised, multicentre clinical trial with clinical response (CR) and microbiological response (MR). A population pharmacokinetic model was utilised to estimate pharmacokinetic parameters for 96 clinically evaluable patients with pathogen and minimum inhibitory concentration (MIC) data available. A 1000-subject Monte Carlo simulation was performed to estimate bacteriostatic (20% of time serum concentration above the MIC (T>MIC)) and bactericidal (40% T>MIC) exposures for comparison. Only the bactericidal CFR versus the CR was not statistically different (92% CR versus 91.9% CFR; 95% confidence interval of the difference, -7.7% to 4.2%), whilst bacteriostatic CFRs overestimated actual CR and MR. This study demonstrates that the use of Monte Carlo simulation to predict the CR of meropenem in complicated skin and skin structures is accurate.     

Evaluation of bootstrap methods for estimating uncertainty of parameters in nonlinear mixed-effects models: a simulation study in population pharmacokinetics

Bootstrap methods are used in many disciplines to estimate the uncertainty of parameters, including multi-level or linear mixed-effects models. Residual-based bootstrap methods which resample both random effects and residuals are an alternative approach to case bootstrap, which resamples the individuals. Most PKPD applications use the case bootstrap, for which software is available. In this study, we evaluated the performance of three bootstrap methods (case bootstrap, nonparametric residual bootstrap and parametric bootstrap) by a simulation study and compared them to that of an asymptotic method (Asym) in estimating uncertainty of parameters in nonlinear mixed-effects models (NLMEM) with heteroscedastic error. This simulation was conducted using as an example of the PK model for aflibercept, an anti-angiogenic drug. As expected, we found that the bootstrap methods provided better estimates of uncertainty for parameters in NLMEM with high nonlinearity and having balanced designs compared to the Asym, as implemented in MONOLIX. Overall, the parametric bootstrap performed better than the case bootstrap as the true model and variance distribution were used. However, the case bootstrap is faster and simpler as it makes no assumptions on the model and preserves both between subject and residual variability in one resampling step. The performance of the nonparametric residual bootstrap was found to be limited when applying to NLMEM due to its failure to reflate the variance before resampling in unbalanced designs where the Asym and the parametric bootstrap performed well and better than case bootstrap even with stratification.     

In vitro comparative studies of two marketed transdermal nicotine delivery systems: Nicopatch and Nicorette

The aim of this work was to compare in vitro the performances at delivering nicotine of two transdermal delivery system (TDS): Nicorette (8.3 mg/10 cm(2) nicotine content) and Nicopatch (17.5 mg/10 cm(2)). Release profiles were obtained using the FDA paddle method, and skin permeation profiles using Franz-type diffusion cells. Using the first method, nicotine release followed the polymer matrix diffusion-controlled process, as suggested by the linear Q versus t(1/2) relationship. Cumulative amounts released from Nicopatch were twice the amounts released from Nicorette, but the released fractions were almost equal for both TDS ( approximately 50%). Using diffusion cells, skin permeation rates were constant over the time: they were not significantly different between both TDS and close to in vivo claimed releases: Nicorette should be considered as more efficient at delivering nicotine through skin than Nicopatch. However, cumulative permeated amounts were overestimated, indicating that the actual diffusion surface area exceeded the effective diffusion surface area of the cells. Reducing the trimmed TDS surface area led not only to a reduction of the cumulative permeated amounts, but also to a reduction of the permeation rates. Therefore, the usefulness of the method to evaluate skin permeation parameters of TDS is questioned.     

The clinical impact of pitavastatin: comparative studies with other statins on LDL-C and HDL-C

INTRODUCTION: Statins are currently the most effective drugs for lowering low-density lipoprotein cholesterol (LDL-C) and represent the first choice for treating hypercholesterolemia. Pitavastatin was launched as a new statin on the Japanese market in 2003, followed by Korea, Thailand, China, the United States and Europe. This review summarizes and evaluates new insights into pitavastatin, from clinical trials since 2010. AREAS COVERED: This article reviews studies that compare pitavastatin with various other statins: i) Randomized Head-to-Head Comparison of Pitavastatin, Atorvastatin, and Rosuvastatin for Safety and Efficacy (Quantity and Quality of LDL): the PATROL Trial; ii) various Phase III clinical trials in Western countries; iii) The Comparison of Preventive Effect on Cardiovascular Events With Different Statins (CIRCLE) study; and iv) The Livalo Effectiveness and Safety (LIVES) Study Extension. Pitavastatin was found to have a similar LDL-C-lowering effect to other strong statins but also had a strong HDL-C-elevating effect and did not worsen glucose metabolism. EXPERT OPINION: Pitavastatin has been launched in various countries around the world as a statin with potent LDL-C-lowering activity that is virtually unmetabolized by the cytochrome P450 family, with relatively few drug-drug interactions and no adverse effects on blood glucose. Pitavastatin thus appears well suited to long-term use.