544 resultados para Pharmacokinetic
Resumo:
Optimal sampling times are found for a study in which one of the primary purposes is to develop a model of the pharmacokinetics of itraconazole in patients with cystic fibrosis for both capsule and solution doses. The optimal design is expected to produce reliable estimates of population parameters for two different structural PK models. Data collected at these sampling times are also expected to provide the researchers with sufficient information to reasonably discriminate between the two competing structural models.
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Defining the pharmacokinetics of drugs in overdose is complicated. Deliberate self-poisoning is generally impulsive and associated with poor accuracy in dose history. In addition, early blood samples are rarely collected to characterize the whole plasma-concentration time profile and the effect of decontamination on the pharmacokinetics is uncertain. The aim of this study was to explore a fully Bayesian methodology for population pharmacokinetic analysis of data that arose from deliberate self-poisoning with citalopram. Prior information on the pharmacokinetic parameters was elicited from 14 published studies on citalopram when taken in therapeutic doses. The data set included concentration-time data from 53 patients studied after 63 citalopram overdose events (dose range: 20-1700 mg). Activated charcoal was administered between 0.5 and 4 h after 17 overdose events. The clinical investigator graded the veracity of the patients' dosing history on a 5-point ordinal scale. Inclusion of informative priors stabilised the pharmacokinetic model and the population mean values could be estimated well. There were no indications of non-linear clearance after excessive doses. The final model included an estimated uncertainty of the dose amount which in a simulation study was shown to not affect the model's ability to characterise the effects of activated charcoal. The effect of activated charcoal on clearance and bioavailability was pronounced and resulted in a 72% increase and 22% decrease, respectively. These findings suggest charcoal administration is potentially beneficial after citalopram overdose. The methodology explored seems promising for exploring the dose-exposure relationship in the toxicological settings.
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The pharmacokinetic disposition of metformin in late pregnancy was studied together with the level of fetal exposure at birth. Blood samples were obtained in the third trimester of pregnancy from women with gestational diabetes or type 2 diabetes, 5 had a previous diagnosis of polycystic ovary syndrome. A cord blood sample also was obtained at the delivery of some of these women, and also at delivery of others who had been taking metformin during pregnancy but from whom no blood had been taken. Plasma metformin concentrations were assayed by a new, validated, reverse-phase HPLC method, A 2-compartment, extravascular maternal model with transplacental partitioning of drug to a fetal compartment was fitted to the data. Nonlinear mixed-effects modeling was performed in'NONMEM using FOCE with INTERACTION. Variability was estimated using logarithmic interindividual and additive residual variance models; the covariance between clearance and volume was modeled simultaneously. Mean (range) metformin concentrations in cord plasma and in maternal plasma were 0.81 (range, 0.1-2.6) mg/L and 1.2 (range, 0. 1-2.9) mg/L, respectively. Typical population values (interindividual variability, CV%) for allometrically scaled maternal clearance and volume of distribution were 28 L/h/70 kg (17.1%) and 190 L/70 ka (46.3%), giving a derived population-wide half-life of 5.1 hours. The placental partition coefficient for metformin was 1.07 (36.3%). Neither maternal age nor weight significantly influenced the pharmacokinetics. The variability (SD) of observed concentrations about model-predicted concentrations was 0.32 mg/L. The pharmacokinetics were similar to those in nonpregnant patients and, therefore, no dosage adjustment is warranted. Metformin readily crosses the placenta, exposing the fetus to concentrations approaching those in the maternal circulation. The sequelae to such exposure, ea, effects on neonatal obesity and insulin resistance, remain unknown.
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Indomethacin (IND) is the drug of choice for the closure of a patent ductus arteriosus (PDA) in neonates. This paper describes a simple, sensitive, accurate and precise microscale HPLC method suitable for the analysis of IND in plasma of premature neonates. Samples were prepared by plasma protein precipitation with acetonitrile containing the methyl ester of IND as the internal standard (IS). Chromatography was performed on a Hypersil C-18 column. The mobile phase of methanol, water and orthophosphoric acid (70:29.5:0.5, v/v, respectively), was delivered at 1.5 mL/min and monitored at 270 nm. IND and the IS were eluted at 2.9 and 4.3 min, respectively. Calibrations were linear (r > 0.999) from 25 to 2500 mu g/L. The inter- and intra-day assay imprecision was less than 4.3% at 400-2000 mu g/L, and less than 22.1% at 35 mu g/L. Inaccuracy ranged from -6.0% to +1.0% from 35 to 2000 mu g/L. The absolute recovery of IND over this range was 93.0-113.3%. The IS was stable for at least 36 h when added to plasma at ambient temperature. This method is suitable for pharmacokinetic studies of IND and has potential for monitoring therapy in infants with PDA when a target therapeutic range for IND has been validated. (c) 2005 Elsevier B.V. All rights reserved.
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Aim To develop an appropriate dosing strategy for continuous intravenous infusions (CII) of enoxaparin by minimizing the percentage of steady-state anti-Xa concentration (C-ss) outside the therapeutic range of 0.5-1.2 IU ml(-1). Methods A nonlinear mixed effects model was developed with NONMEM (R) for 48 adult patients who received CII of enoxaparin with infusion durations that ranged from 8 to 894 h at rates between 100 and 1600 IU h(-1). Three hundred and sixty-three anti-Xa concentration measurements were available from patients who received CII. These were combined with 309 anti-Xa concentrations from 35 patients who received subcutaneous enoxaparin. The effects of age, body size, height, sex, creatinine clearance (CrCL) and patient location [intensive care unit (ICU) or general medical unit] on pharmacokinetic (PK) parameters were evaluated. Monte Carlo simulations were used to (i) evaluate covariate effects on C-ss and (ii) compare the impact of different infusion rates on predicted C-ss. The best dose was selected based on the highest probability that the C-ss achieved would lie within the therapeutic range. Results A two-compartment linear model with additive and proportional residual error for general medical unit patients and only a proportional error for patients in ICU provided the best description of the data. Both CrCL and weight were found to affect significantly clearance and volume of distribution of the central compartment, respectively. Simulations suggested that the best doses for patients in the ICU setting were 50 IU kg(-1) per 12 h (4.2 IU kg(-1) h(-1)) if CrCL < 30 ml min(-1); 60 IU kg(-1) per 12 h (5.0 IU kg(-1) h(-1)) if CrCL was 30-50 ml min(-1); and 70 IU kg(-1) per 12 h (5.8 IU kg(-1) h(-1)) if CrCL > 50 ml min(-1). The best doses for patients in the general medical unit were 60 IU kg(-1) per 12 h (5.0 IU kg(-1) h(-1)) if CrCL < 30 ml min(-1); 70 IU kg(-1) per 12 h (5.8 IU kg(-1) h(-1)) if CrCL was 30-50 ml min(-1); and 100 IU kg(-1) per 12 h (8.3 IU kg(-1) h(-1)) if CrCL > 50 ml min(-1). These best doses were selected based on providing the lowest equal probability of either being above or below the therapeutic range and the highest probability that the C-ss achieved would lie within the therapeutic range. Conclusion The dose of enoxaparin should be individualized to the patients' renal function and weight. There is some evidence to support slightly lower doses of CII enoxaparin in patients in the ICU setting.
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The aim of this study was to ascertain the most suitable dosing schedule for gentamicin in patients receiving hemodialysis. We developed a model to describe the concentrationtime course of gentamicin in patients receiving hemodialysis. Using the model, an optimal dosing schedule was evaluated. Various dosing regimens were compared in their ability to achieve maximum concentration (C-max, >= 8 mg/L) and area under the concentration time-curve (AUC >= 70 mg(.)h/L and <= 120 mg(.)h/L per 24 hours). The model was evaluated by comparing model predictions against real data collected retrospectively. Simulations from the model confirmed the benefits of predialysis dosing. The mean optimal dose was 230 mg administered immediately before dialysis. The model was found to have good predictive performance when simulated data were compared to data observed in real patients. In summary, a model was developed that describes gentamicin pharmacokinetics in patients receiving hemodialysis. Predialysis dosing provided a superior pharmacokinetic profile than did postdialysis dosing.
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We report here a validated method for the quantification of a new immunosuppressant drug FTY720, using HPLC-tandem mass spectrometry. Whole blood samples (500 mu l) were subjected to liquid-liquid extraction, in the presence of an internal standard (Y-32919). Mass spectrometric detection was by selected reaction monitoring with an atmospheric pressure chemical ionization source in positive ionization mode (FTY720: m/z 308.3 -> 255.3). The assay was linear from 0.2 to 25 mu g/l (r(2) > 0.997, n = 5). The inter- and intra-day analytical recovery and imprecision for quality control samples (0.5, 7 and 15 mu g/l) were 95.8-103.2 and < 5.5%, respectively. At the lower limit of quantification (0.2 mu g/l) the interand intra-day analytical recovery was 99.0-102.8% with imprecision of < 7.6% (n = 5). The assay had a mean relative recovery of 100.5 +/- 5.8% (n = 15). Extracted samples were stable for 16 h. IFTY720 quality control samples were stable at room temperature for 16 h at 4 degrees C for at least 8 days and when taken through at least three freeze-thaw cycles. In conclusion, the method described displays analytical performance characteristics that are suitable for pharmacokinetic studies in humans. (c) 2006 Elsevier B.V. All rights reserved.
Resumo:
Objective: The objective of the study was to characterise the population pharmacokinetic properties of itraconazole and its active metabolite hydroxyitraconazole in a representative paediatric population of cystic fibrosis and bone marrow transplant (BMT) patients and to identify patient characteristics influencing the pharmacokinetics of itraconazole. The ultimate goals were to determine the relative bioavailability between the two oral formulations (capsules vs oral solution) and to optimise dosing regimens in these patients. Methods: All paediatric patients with cystic fibrosis or patients undergoing BMT at The Royal Children's Hospital, Brisbane, QLD, Australia, who were prescribed oral itraconazole for the treatment of allergic bronchopulmonary aspergillosis (cystic fibrosis patients) or for prophylaxis of any fungal infection (BMT patients) were eligible for the study. Blood samples were taken from the recruited patients as per an empirical sampling design either during hospitalisation or during outpatient clinic visits. ltraconazole and hydroxy-itraconazole plasma concentrations were determined by a validated high-performance liquid chromatography assay with fluorometric detection. A nonlinear mixed-effect modelling approach using the NONMEM software to simultaneously describe the pharmacokinetics of itraconazole and its metabolite. Results: A one-compartment model with first-order absorption described the itraconazole data, and the metabolism of the parent drug to hydroxy-itraconazole was described by a first-order rate constant. The metabolite data also showed one-compartment characteristics with linear elimination. For itraconazole the apparent clearance (CLitraconazole) was 35.5 L/hour, the apparent volume of distribution (V-d(itraconazole)) was 672L, the absorption rate constant for the capsule formulation was 0.0901 h(-1) and for the oral solution formulation was 0.96 h-1. The lag time was estimated to be 19.1 minutes and the relative bioavailability between capsules and oral solution (F-rel) was 0.55. For the metabolite, volume of distribution, V-m/(F (.) f(m)), and clearance, CL/(F (.) fm), were 10.6L and 5.28 L/h, respectively. The influence of total bodyweight was significant, added as a covariate on CLitraconazoie/F and V-d(itraconazole)/F (standardised to a 70kg person) using allometric three-quarter power scaling on CLitraconazole/F, which therefore reflected adult values. The unexplained between-subject variability (coefficient of variation %) was 68.7%, 75.8%, 73.4% and 61.1% for CLitraconazoie/F, Vd(itraconazole)/F, CLm/(F (.) fm) and F-rel, respectively. The correlation between random effects of CLitraconazole and Vd((itraconazole)) was 0.69. Conclusion: The developed population pharmacokinetic model adequately described the pharmacokinetics of itraconazole and its active metabolite, hydroxy-itraconazole, in paediatric patients with either cystic fibrosis or undergoing BMT. More appropriate dosing schedules have been developed for the oral solution and the capsules to secure a minimum therapeutic trough plasma concentration of 0.5 mg/L for these patients.
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Treatment of sepsis remains a significant challenge with persisting high mortality and morbidity. Early and appropriate antibacterial therapy remains an important intervention for such patients. To optimise antibacterial therapy, the clinician must possess knowledge of the pharmacokinetic and pharmacodynamic properties of commonly used antibacterials and how these parameters may be affected by the constellation of pathophysiological changes occurring during sepsis. Sepsis, and the treatment thereof, increases renal preload and, via capillary permeability, leads to 'third-spacing', both resulting in higher antibacterial clearances. Alternatively, sepsis can induce multiple organ dysfunction, including renal and/or hepatic dysfunction, causing a decrease in antibacterial clearance. Aminoglycosides are concentration-dependent antibacterials and they display an increased volume of distribution (V-d) in sepsis, resulting in decreased peak serum concentrations. Reduced clearance from renal dysfunction would increase the likelihood of toxicity. Individualised dosing using extended interval dosing, which maximises the peak serum drug concentration (C-max)/minimum inhibitory concentration ratio is recommended. beta-Lactams and carbapenems are time-dependent antibacterials. An increase in Vd and renal clearance will require increased dosing or administration by continuous infusion. If renal impairment occurs a corresponding dose reduction may be required. Vancomycin displays predominantly time-dependent pharmacodynamic properties and probably requires higher than conventionally recommended doses because of an increased V-d and clearance during sepsis without organ dysfunction. However, optimal dosing regimens remain unresolved. The poor penetration of vancomycin into solid organs may require alternative therapies when sepsis involves solid organs (e.g. lung). Ciprofloxacin displays largely concentration-dependent kill characteristics, but also exerts some time-dependent effects. The V-d of ciprofloxacin is not altered with fluid shifts or over time, and thus no alterations of standard doses are required unless renal dysfunction occurs. In order to optimise antibacterial regimens in patients with sepsis, the pathophysiological effects of systemic inflammatory response syndrome need consideration, in conjunction with knowledge of the different kill characteristics of the various antibacterial classes. In conclusion, certain antibacterials can have a very high V-d, therefore leading to a low C-max and if a high peak is needed, then this would lead to underdosing. The Vd of certain antibacterials, namely aminoglycosides and vancomycin, changes over time, which means dosing may need to be altered over time. Some patients with serum creatinine values within the normal range can have very high drug clearances, thereby producing low serum drug levels and again leading to underdosing. Copyright © 2010 Elsevier Inc. All rights reserved.
Resumo:
Current Physiologically based pharmacokinetic (PBPK) models are inductive. We present an additional, different approach that is based on the synthetic rather than the inductive approach to modeling and simulation. It relies on object-oriented programming A model of the referent system in its experimental context is synthesized by assembling objects that represent components such as molecules, cells, aspects of tissue architecture, catheters, etc. The single pass perfused rat liver has been well described in evaluating hepatic drug pharmacokinetics (PK) and is the system on which we focus. In silico experiments begin with administration of objects representing actual compounds. Data are collected in a manner analogous to that in the referent PK experiments. The synthetic modeling method allows for recognition and representation of discrete event and discrete time processes, as well as heterogeneity in organization, function, and spatial effects. An application is developed for sucrose and antipyrine, administered separately and together PBPK modeling has made extensive progress in characterizing abstracted PK properties but this has also been its limitation. Now, other important questions and possible extensions emerge. How are these PK properties and the observed behaviors generated? The inherent heuristic limitations of traditional models have hindered getting meaningful, detailed answers to such questions. Synthetic models of the type described here are specifically intended to help answer such questions. Analogous to wet-lab experimental models, they retain their applicability even when broken apart into sub-components. Having and applying this new class of models along with traditional PK modeling methods is expected to increase the productivity of pharmaceutical research at all levels that make use of modeling and simulation.
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Systemic inflammation is known to affect drug disposition in the liver. This study sought to relate and quantitate changes in hepatic pharmacokinetics of propranolol with changes in hepatic architecture and physiology in adjuvant-treated rats. Transmission electron microscopy was used to assess morphological changes in mitochondria and lysosomes of adjuvant-treated rat livers. The disposition of propranolol was assessed in the perfused rat liver using the multiple indicator dilution technique. Hepatic extraction and mean transit time were determined from outflow-concentration profiles using a nonparametric method. Kinetic parameters were derived from a two-phase physiologically based organ pharmacokinetic model. Possible relationships were then explored between the changes in hepatic drug disposition and cytochrome P-450 activity and iron concentration. Adjuvant treatment induced the appearance of mitochondrial inclusions/tubularization and irregularly shaped lysosomes in rat livers. Livers from adjuvant-treated rats had (relative to normal) significantly higher alpha(1)-acid glycoprotein (orosomucoid) and iron tissue concentrations but lower cytochrome P-450 content. The hepatic extraction, metabolism, and ion trapping of propranolol were significantly impaired in adjuvant-treated rats and could be correlated with altered iron store and cytochrome P-450 activity. It is concluded that adjuvant-induced systemic inflammation alters hepatocellular morphology and biochemistry and consequently influences hepatic disposition of propranolol.
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The aim of this study was to evaluate dosing schedules of gentamicin in patients with end-stage renal disease and receiving hemodialysis. Forty-six patients were recruited who received gentamicin while on hemodialysis. Each patient provided approximately 4 blood samples at various times before and after dialysis for analysis of plasma gentamicin concentrations. A population pharmacokinetic model was constructed using NONMEM (version 5). The clearance of gentamicin during dialysis was 4.69 L/h and between dialysis was 0.453 L/h. The clearance between dialysis was best described by residual creatinine clearance (as calculated using the Cockcroft and Gault equation), which probably reflects both lean mass and residual clearance mechanisms. Simulation from the final population model showed that predialysis dosing has a higher probability of achieving target maximum concentration (C-max) concentrations (> 8 mg/L) within acceptable exposure limits (area under the concentration-time curve [AUC] values > 70 and < 120 mg.h/L per 24 hours) than postdialysis dosing.
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Aim: To identify an appropriate dosage strategy for patients receiving enoxaparin by continuous intravenous infusion (CII). Methods: Monte Carlo simulations were performed in NONMEM, (200 replicates of 1000 patients) to predict steady state anti-Xa concentrations (Css) for patients receiving a CII of enoxaparin. The covariate distribution model was simulated based on covariate demographics in the CII study population. The impact of patient weight, renal function (creatinine clearance (CrCL)) and patient location (intensive care unit (ICU)) were evaluated. A population pharmacokinetic model was used as the input-output model (1-compartment first order output model with mixed residual error structure). Success of a dosing regimen was based on the percent of Css that is between the therapeutic range of 0.5 IU/ml to 1.2 IU/ml. Results: The best dose for patients in the ICU was 4.2IU/kg/h (success mean 64.8% and 90% prediction interval (PI): 60.1–69.8%) if CrCL60ml/min, the best dose was 8.3IU/kg/h (success mean 65.4%, 90% PI: 58.5–73.2%). Simulations suggest that there was a 50% improvement in the success of the CII if the dose rate for ICU patients with CrCL
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Objective: To investigate the population pharmacokinetics and the enteral bioavailability of phenytoin in neonates and infants with seizures. Methods: Data (5 mg kg-1 day-1) from 83 patients were obtained retrospectively from the medical records following written ethical approval. A one-compartment model was fitted to the data using NONMEM with FOCE-interaction. Between-subject variability (BSV) and interoccasion variability (IOV) were modelled exponentially together with a log transform-both-sides exponential residual unexplained variance (RUV) model. Covariates in nested models were screened for significance (X2, 1, 0.01). Model validity was determined by bootstrapping with replacement (N=500 samples) from the dataset. Results: The parameters of final pharmacokinetic were: Clearance (L h-1) = 0.826.(current Weight [kg]/70)0.75.(1+0.0692.(Postnatal age [days]-11)); Volume of distribution (L) = 74.2.(current Weight [kg]/70); Enteral bioavailability = 0.76; Absorption rate constant (h-1) = 0.167. BSV for clearance and volume of distribution were 74.2% and 65.6%, respectively. The IOV in clearance was 54.4%. The RUV was 51.1%. Final model parameters deviated from mean bootstrap estimates by
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We have carried out a discovery proteomics investigation aimed at identifying disease biomarkers present in saliva, and, more specifically, early biomarkers of inflammation. The proteomic characterization of saliva is possible due to the straightforward and non-invasive sample collection that allows repetitive analyses for pharmacokinetic studies. These advantages are particularly relevant in the case of newborn patients. The study was carried out with samples collected during the first 48 hours of life of the newborns according to an approved Ethic Committee procedure. In particular, the salivary samples were collected from healthy and infected (n=1) newborns. Proteins were extracted through cycles of sonication, precipitated in ice cold acetone, resuspended and resolved by 2D-electrophoresis. MALDI TOF/TOF mass spectrometry analysis was performed for each spot obtaining the proteins’ identifications. Then we compared healthy newborn salivary proteome and an infected newborn salivary proteome in order to investigate proteins differently expressed in inflammatory condition. In particular the protein alpha-1-antitrypsin (A1AT), correlated with inflammation, was detected differently expressed in the infected newborn saliva. Therefore, in the second part of the project we aimed to develop a robust LC-MS based method that identifies and quantifies this inflammatory protein within saliva that might represent the first relevant step to diagnose a condition of inflammation with a no-invasive assay. The same LC-MS method is also useful to investigate the presence of the F allelic variant of the A1AT in biological samples, which is correlated with the onset of pulmonary diseases. In the last part of the work we analysed newborn saliva samples in order to investigate how phospholipids and mediators of inflammation (eicosanoids) are subject to variations under inflammatory conditions and a trend was observed in lysophosphatidylcholines composition according to the inflammatory conditions.