Biomedical subjects

Paolo Vicini

Publications and source records attributed to Paolo Vicini.

At least 19 recordsLinked to original sources

PubMed2006

Real-time dose adjustment of cyclophosphamide in a preparative regimen for hematopoietic cell transplant: a Bayesian pharmacokinetic approach.

PURPOSE: Dose-related toxicity of cyclophosphamide may be reduced and therapeutic efficacy may be improved by pharmacokinetic sampling and dose adjustment to achieve a target area under the curve (AUC) for two of its metabolites, hydroxycyclophosphamide (HCY) and carboxyethylphosphoramide mustard (CEPM). To facilitate real-time dose adjustment, we developed open-source code within the statistical software R that incorporates individual data into a population pharmacokinetic model. EXPERIMENTAL DESIGN: Dosage prediction performance was compared to that obtained with nonlinear mixed-effects modeling using NONMEM in 20 cancer patients receiving cyclophosphamide. Bayesian estimation of individual pharmacokinetic parameters was accomplished from limited (i.e., five samples over 0-16 hours) sampling of plasma HCY and CEPM after the initial cyclophosphamide dose. Conditional on individual pharmacokinetics, simulations of the AUC of both HCY and CEPM were provided for a range of second doses (i.e., 0-100 mg/kg cyclophosphamide). RESULTS: The results compared favorably with NONMEM and returned accurate predictions for AUCs of HCY and CEPM with comparable mean absolute prediction error and root mean square prediction error. With our method, the mean absolute prediction error and root mean square prediction error of AUC CEPM were 11.0% and 12.8% and AUC HCY were 31.7% and 44.8%, respectively. CONCLUSIONS: We developed dose adjustment software that potentially can be used to adjust cyclophosphamide dosing in a clinical setting, thus expanding the opportunity for pharmacokinetic individualization of cyclophosphamide. The software is simple to use (requiring no programming experience), reads individual patient data directly from an Excel spreadsheet, and runs in less than 5 minutes on a desktop PC.

Bayes Theorem↗

PubMed2006

Population approaches to estimate minimal model indexes of insulin sensitivity and glucose effectiveness using full and reduced sampling schedules.

The intravenous glucose tolerance test (IVGTT) interpreted with the minimal model provides individual indexes of insulin sensitivity (S(I)) and glucose effectiveness (S(G)). In population studies, the traditional approach, the standard two-stage (STS) method, fails to account for uncertainty in individual estimates, resulting in an overestimation of between-subject variability. Furthermore, in the presence of reduced sampling and/or insulin resistance, individual estimates may be unobtainable, biasing population information. Therefore, we investigated the use of two population approaches, the iterative two-stage (ITS) method and nonlinear mixed-effects modeling (NM), in a population (n = 235) of insulin-sensitive and insulin-resistant subjects under full (FSS, 33 samples) and reduced [RSS(240-min), 13 samples and RSS(180-min), 12 samples] IVGTT sampling schedules. All three population methods gave similar results with the FSS. Using RSS(240), the three methods gave similar results for S(I), but S(G) population means were overestimated. With RSS(180), S(I) and S(G) population means were higher for all three methods compared with their FSS counterparts. NM estimated similar between-subject variability (19% S(G), 53% S(I)) with RSS(180), whereas ITS showed regression to the mean for S(G) (0.01% S(G), 56% S(I)) and STS provided larger population variability in S(I) (29% S(G), 91% S(I)). NM provided individual estimates for all subjects, whereas the two-stage methods failed in 16-18% of the subjects using RSS(180) and 6-14% using RSS(240). We conclude that population approaches, specifically NM, are useful in studies with a sparsely sampled IVGTT ( approximately 12 samples) of short duration ( approximately 3 h) and when individual parameter estimates in all subjects are desired.

Blood Glucose↗

PubMed2005

Catch-bond model derived from allostery explains force-activated bacterial adhesion.

High shear enhances the adhesion of Escherichia coli bacteria binding to mannose coated surfaces via the adhesin FimH, raising the question as to whether FimH forms catch bonds that are stronger under tensile mechanical force. Here, we study the length of time that E. coli pause on mannosylated surfaces and report a double exponential decay in the duration of the pauses. This double exponential decay is unlike previous single molecule or whole cell data for other catch bonds, and indicates the existence of two distinct conformational states. We present a mathematical model, derived from the common notion of chemical allostery, which describes the lifetime of a catch bond in which mechanical force regulates the transitions between two conformational states that have different unbinding rates. The model explains these characteristics of the data: a double exponential decay, an increase in both the likelihood and lifetime of the high-binding state with shear stress, and a biphasic effect of force on detachment rates. The model parameters estimated from the data are consistent with the force-induced structural changes shown earlier in FimH. This strongly suggests that FimH forms allosteric catch bonds. The model advances our understanding of both catch bonds and the role of allostery in regulating protein activity.

Adhesins, Escherichia coli↗

PubMed2005

Simultaneous population optimal design for pharmacokinetic-pharmacodynamic experiments.

Multiple outputs or measurement types are commonly gathered in biological experiments. Often, these experiments are expensive (such as clinical drug trials) or require careful design to achieve the desired information content. Optimal experimental design protocols could help alleviate the cost and increase the accuracy of these experiments. In general, optimal design techniques ignore between-individual variability, but even work that incorporates it (population optimal design) has treated simultaneous multiple output experiments separately by computing the optimal design sequentially, first finding the optimal design for one output (eg, a pharmacokinetic [PK] measurement) and then determining the design for the second output (eg, a pharmacodynamic [PD] measurement). Theoretically, this procedure can lead to biased and imprecise results when the second model parameters are also included in the first model (as in PK-PD models). We present methods and tools for simultaneous population D-optimal experimental designs, which simultaneously compute the design of multiple output experiments, allowing for correlation between model parameters. We then apply these methods to simulated PK-PD experiments. We compare the new simultaneous designs to sequential designs that first compute the PK design, fix the PK parameters, and then compute the PD design in an experiment. We find that both population designs yield similar results in designs for low sample number experiments, with simultaneous designs being possibly superior in situations in which the number of samples is unevenly distributed between outputs. Simultaneous population D-optimality is a potentially useful tool in the emerging field of experimental design.

Computer Simulation↗

PubMed2005

Population pharmacokinetics of recombinant factor XIII in cynomolgus monkeys.

Hemostasis in humans and other animals is a complex process that controls blood loss after a vascular injury. Factor XIII (FXIII) stabilizes clots primarily by cross-linking fibrin, thus protecting a newly formed clot from fibrinolysis by plasmin. Congenital deficiencies in humans involving FXIII are associated with delayed bleeding and wound healing and severe spontaneous hemorrhaging. These symptoms can be alleviated by intravenous administration of enriched FXIII plasma fractions. Circulating plasma FXIII is found as a heterotetramer that dissociates in the presence of calcium and thrombin into an active dimer and 2 inactive monomers. The recombinant FXIII under investigation is the active dimer alone. A 3-compartment, nonlinear population pharmacokinetic model was implemented in NONMEM V and then used to analyze data from preclinical studies in cynomolgus monkeys. The model simultaneously describes endogenous production of dimer (0.622 microg kg(-1) hr(-1)) and monomer (12.1 microg kg(-1) hr(-1)), and the administration of recombinant dimer. The model incorporates the rate and extent of complexation of recombinant dimer with available endogenous monomer (6.59 mg(-1) kg hr(-1)) to form the heterotetramer. Half-lives for dimer, heterotetramer, and monomer (3.33 hours, 2.83 days, and 3.94 hours for A(2), A(2)B(2), and B, respectively) were estimated, along with their variability in the population studied.

Animals↗

PubMed2005

Automated identification of axonal growth cones in time-lapse image sequences.

The isolation and purification of axon guidance molecules has enabled in vitro studies of the effects of axon guidance molecule gradients on numerous neuronal cell types. In a typical experiment, cultured neurons are exposed to a chemotactic gradient and their growth is recorded by manual identification of the axon tip position from two or more micrographs. Detailed and statistically valid quantification of axon growth requires evaluation of a large number of neurons at closely spaced time points (e.g. using a time-lapse microscopy setup). However, manual tracing becomes increasingly impractical for recording axon growth as the number of time points and/or neurons increases. We present a software tool that automatically identifies and records the axon tip position in each phase-contrast image of a time-lapse series with minimal user involvement. The software outputs several quantitative measures of axon growth, and allows users to develop custom measurements. For, example analysis of growth velocity for a dissociated E13 mouse cortical neuron revealed frequent extension and retraction events with an average growth velocity of 0.05 +/- 0.14 microm/min. Comparison of software-identified axon tip positions with manually identified axon tip positions shows that the software's performance is indistinguishable from that of skilled human users.

Animals↗

PubMed2005

Integrated model of hepatic and peripheral glucose regulation for estimation of endogenous glucose production during the hot IVGTT.

We have developed a new model to describe endogenous glucose kinetics during a labeled (hot) intravenous glucose tolerance test (IVGTT) to derive a time profile of endogenous glucose production (EGP). We reanalyzed data from a previously published study (P. Vicini, J. J. Zachwieja, K. E. Yarasheski, D. M. Bier, A. Caumo, and C. Cobelli. Am J Physiol Endocrinol Metab 276: E285-E294, 1999), in which insulin-modified [6,6-2H2]glucose-labeled IVGTTs (0.33 g/kg glucose) were performed in 10 normal subjects. In addition, a second tracer ([U-13C]glucose) was infused in a variable rate to clamp the endogenous glucose tracer-to-tracee ratio (TTR). Our new model describing endogenous glucose kinetics was incorporated into the two-compartment hot minimal-model structure. The model gave estimates of glucose effectiveness [1.54 +/- 0.31 (SE) ml x kg(-1) x min(-1)], insulin sensitivity (37.74 +/- 5.23 10(4) dl x kg(-1) x min(-1) x microU(-1) x ml), and a new parameter describing the sensitivity of EGP to the inhibitory effect of insulin (IC50 = 0.0195 +/- 0.0046 min(-1)). The model additionally provided an estimate of the time course of EGP showing almost immediate inhibition, followed by a secondary inhibitory effect caused by infusion of insulin, and a large overshoot as EGP returns to its basal value. Our estimates show very good agreement with those obtained via deconvolution and the model-independent TTR clamp technique. These results suggest that the new integrated model can serve as a simple one-step approach to obtain metabolic indexes while also providing a parametric description of EGP.

Blood Glucose↗

PubMed2005

Mixture model approach to tumor classification based on pharmacokinetic measures of tumor permeability.

PURPOSE: To categorize the disease severity of mammary tumors in an animal model through the application of a novel tumor permeability mixture model within a hierarchical modeling framework. MATERIALS AND METHODS: Thirty-six rats with mammary tumors of varying grade were imaged via dynamic contrast-enhanced (CE) MRI using albumin-(Gd-DTPA)30. Time-dependent contrast agent concentration curves for blood and tumor tissue were obtained and a mathematical model of microvascular blood-tissue exchange was developed under the hypothesis that endothelial integrity is disrupted in a manner proportional to the degree of malignancy, with benign tumors showing no disruption of the vasculature endothelium. This permeability model was incorporated into a statistical model for the benign and malignant tumor subgroups that enabled automatic subject classification. The structural and statistical models were implemented using the software Nonlinear Mixed Effects Modeling (NONMEM) to statistically separate subjects into the two subgroups. RESULTS: Individual tumor classifications (as benign or malignant) were evaluated against the Scarff-Bloom-Richardson microscopic scoring method as applied to the tumor histology of each subject. The model-based classification resulted in 90.9% sensitivity, 92.9% specificity, and 91.7% accuracy. CONCLUSION: Mixture model analysis provides a robust method for subject classification without user intervention and bias. Although the present results are promising, additional research is needed to further evaluate this technique for diagnostic purposes.

Animals↗

PubMed2005

Estimating in vitro mitochondrial oxygen consumption during muscle contraction and recovery: a novel approach that accounts for diffusion.

A deconvolution algorithm, based on a Bayesian statistical framework and smoothing spline technique, is applied to reconstructing input functions from noisy measurements in biological systems. Deconvolution is usually ill-posed. However, placing a Bayesian prior distribution on the input function can make the problem well-posed. Using this algorithm and a computational model of diffusional oxygen transport in an approximately cylindrical muscle (about 0.5-mm diameter and 10-mm long mouse leg muscle), the time course of muscle oxygen uptake and mitochondrial oxygen consumption, both during isometric twitch contractions (at various frequencies) and the recovery period, is estimated from polarographic measurements of oxygen concentration on the muscle surface. An important feature of our experimental protocol is the availability of data for the apparatus characteristics. From these time courses, the actual mitochondrial consumption rates during resting and exercise states can be estimated. Mitochondrial oxygen consumption rate increased during stimulation to a maximum steady state value approximately five times of the resting value of 0.63 nmol/s/g wet weight for the stimulation conditions studied. Diffusion slowed the kinetic responses to the contraction but not the steady state fluxes during the stimulation interval.

Adaptation, Physiological↗

PubMed2005

Robust population pharmacokinetic experiment design.

The population approach to estimating mixed effects model parameters of interest in pharmacokinetic (PK) studies has been demonstrated to be an effective method in quantifying relevant population drug properties. The information available for each individual is usually sparse. As such, care should be taken to ensure that the information gained from each population experiment is as efficient as possible by designing the experiment optimally, according to some criterion. The classic approach to this problem is to design "good" sampling schedules, usually addressed by the D-optimality criterion. This method has the drawback of requiring exact advanced knowledge (expected values) of the parameters of interest. Often, this information is not available. Additionally, if such prior knowledge about the parameters is misspecified, this approach yields designs that may not be robust for parameter estimation. In order to incorporate uncertainty in the prior parameter specification, a number of criteria have been suggested. We focus on ED-optimality. This criterion leads to a difficult numerical problem, which is made tractable here by a novel approximation of the expectation integral usually solved by stochastic integration techniques. We present two case studies as evidence of the robustness of ED-optimal designs in the face of misspecified prior information. Estimates from replicate simulated population data show that such misspecified ED-optimal designs recover parameter estimates that are better than similarly misspecified D-optimal designs, and approach estimates gained from D-optimal designs where the parameters are correctly specified.

Algorithms↗

PubMed2005

Metabolism-based cyclophosphamide dosing for hematopoietic cell transplant.

When cyclophosphamide (120 mg/kg) is used for hematopoietic cell transplant, the increased area under the curve of carboxyethylphosphoramide mustard (AUC(CEPM)) is related to liver toxicity and death. We determined the feasibility of dose-adjusting cyclophosphamide to a preset metabolic endpoint (AUC(CEPM), 325 +/- 25 micromol/L.h). In 20 patients blood sampling was done over a 16-hour period after administration of 45 mg/kg cyclophosphamide; AUC(CEPM) from 0 to 16 hours was calculated by noncompartmental analysis. The expected AUC(CEPM) for 0 to 48 hours was estimated, and the second cyclophosphamide dose was determined. The mean second cyclophosphamide dose was 42 mg/kg, and the mean total cyclophosphamide dose was 86 mg/kg (range, 54-120 mg/kg). The mean AUC(CEPM) for the time from 0 to 48 hours was 296 micromol/L.h (95% confidence interval, 275-317 micromol/L.h). A retrospective analysis indicated that AUC(CEPM) could be more accurately predicted by use of a population pharmacokinetic model. We conclude that metabolism-based dosing of cyclophosphamide is feasible and that a lower cyclophosphamide dose does not affect engraftment.

Adolescent↗

PubMed2005

Paradoxical role of cytochrome P450 3A in the bioactivation and clinical effects of levo-alpha-acetylmethadol: importance of clinical investigations to validate in vitro drug metabolism studies.

OBJECTIVE: Levo-alpha-acetylmethadol (LAAM, levacetylmethadol) is a long-acting opioid agonist used for the prevention of opioid withdrawal. LAAM undergoes sequential N-demethylation to norLAAM and dinorLAAM, which are more potent and longer-acting than LAAM. Hepatic and intestinal microsomal N-demethylation in vitro is catalysed mainly by cytochrome P450 (CYP) 3A4; however, the role of CYP3A in LAAM disposition in humans in vivo is unknown. This investigation tested the hypothesis that CYP3A induction (or inhibition) would increase (or decrease) LAAM metabolism and bioactivation and, thus, clinical effects. It also related changes in LAAM disposition during enzyme inhibition or induction to any changes in pharmacological effect. METHODS: Healthy volunteers (n = 13) completed the three-way, randomised, balanced crossover study. Subjects received oral LAAM (0.25 mg/kg) after CYP3A induction (rifampicin [rifampin]), inhibition (troleandomycin) or nothing (controls). Plasma and urine LAAM, norLAAM and dinorLAAM were determined by electrospray high-performance liquid chromatography/mass spectrometry (HPLC/MS). Dark-adapted pupil diameter change from baseline (miosis) was the LAAM effect measure. Results were analysed by noncompartmental methods and by a combined pharmacokinetic/pharmacodynamic model. RESULTS: Compared with controls, CYP3A induction (or inhibition) decreased (or increased) plasma LAAM concentrations and mean area under the plasma concentration-time curve from time zero to infinity (AUC(infinity) 199 +/- 91 [control] versus 11.3 +/- 4.0 [rifampicin] and 731 +/- 229 ng . h/mL [troleandomycin]; p < 0.05), and increased (or decreased) median formation clearances of norLAAM (1740 versus 14 100 and 302 mL/h/kg; p < 0.05) and dinorLAAM (636 versus 7840 and 173 mL/h/kg; p < 0.05). Surprisingly, however, CYP3A induction (or inhibition) decreased (or increased) mean plasma metabolite AUC from 0 to 96 hours (AUC(96)) [norLAAM + dinorLAAM] (859 +/- 241 versus 107 +/- 48 and 1185 +/- 179 ng . h/mL; p < 0.05) and clinical effects (mean miosis AUC(96) 128 +/- 40 versus 22.5 +/- 14.9 and 178 +/- 81 mm . h; p < 0.05). Clinical effects were best correlated with plasma norLAAM concentrations. CONCLUSION: CYP3A mediates human LAAM N-demethylation and bioactivation to norLAAM and dinorLAAM in vivo. Paradoxically, however, CYP3A induction decreased and inhibition increased LAAM active metabolite concentrations and clinical effects. This suggests a CYP3A-mediated metabolic pathway leading to inactive metabolites, which predominates over CYP3A-dependent bioactivation. These results highlight the need for clinical investigations to validate in vitro drug metabolism studies.

Administration, Oral↗

PubMed2004

Pharmacokinetic model-predicted anticancer drug concentrations in human tumors.

In an era when molecular and targeted anticancer therapeutics is a major focus and when understanding drug dynamics in tumor is critical, it seems advantageous to be able to relate drug concentrations in tumors to corresponding biological end points. To that end, a novel method, based on physiologically based hybrid pharmacokinetic models, is presented to predict human tumor drug concentrations. Such models consist of a forcing function, describing the plasma drug concentration-time profile, which is linked to a model describing drug disposition in tumors. The hybrid models are originally derived from preclinical data and then scaled to humans. Integral to the scale-up procedure is the ability to derive human forcing functions directly from clinical pharmacokinetic data. Three examples of this approach are presented based on preclinical investigations with carboplatin, topotecan, and temozolomide. Translation of these preclinical hybrid models to humans used a Monte Carlo simulation technique that accounted for intrasubject and intersubject variability. Different pharmacokinetic end points, such as the AUC tumor, were extracted from the simulated human tumor drug concentrations to show how the predicted drug concentrations might be used to select drug-dosing regimens. It is believed that this modeling strategy can be used as an aid in the drug development process by providing key insights into drug disposition in tumors and by offering a foundation to optimize drug regimen design.

Animals↗

PubMed2004

Diminishing the risk of nonrelapse mortality in hematopoietic stem cell transplantation: Prediction of exposure to the cyclophosphamide metabolite carboxyethylphosphoramide mustard.

OBJECTIVES: Our objectives were (1) to develop a population pharmacokinetic model for cyclophosphamide, 4-hydroxycyclophosphamide, and carboxyethylphosphoramide mustard (a reporter for nonrelapse mortality) in hematopoietic stem cell transplantation patients and (2) to validate a Bayesian approach to dosing. METHODS: In this study 147 patients received intravenous infusions of 60 mg. kg -1. d -1 cyclophosphamide for 2 days, followed by 12 to 14.4 Gy total body irradiation. A population model was developed to fit concentration-time data of cyclophosphamide and metabolites. Bayesian prediction of the area under the curve (AUC) was validated by dividing the data set into an index set (98 patients) and validation set (49 patients). Parameters from the index data set were used as priors. RESULTS: Cyclophosphamide elimination was best described by noninducible and inducible routes producing 4-hydroxycyclophosphamide. Induction was described by a zero-order maximum fold of induction-type increase in enzyme level. The prediction of the AUC of carboxyethylphosphoramide mustard was clinically accurate and precise (mean prediction error = -3.5% and root mean squared prediction error = 12.2%) with data limited to 5 to 6 points obtained in the first 16 hours. However, the AUC of 4-hydroxycyclophosphamide was overestimated (mean prediction error = 16.9%-23.6%). Several alternative models did not improve the result. CONCLUSION: The integrated mechanism-based model describes the pharmacokinetics of cyclophosphamide and carboxyethylphosphoramide mustard. Accurate modeling of 4-hydroxycyclophosphamide is limited by its chemical instability. Exposure to carboxyethylphosphoramide mustard could be accurately and precisely predicted with minimal data obtained over a 16-hour period after the first dose, offering the potential of pharmacokinetically guided dosing to reduce the nonrelapse mortality rate.

Adolescent↗

PubMed2004

POPED, a software for optimal experiment design in population kinetics.

Population kinetic analysis is the methodology used to quantify inter-subject variability in kinetic studies. It entails the collection of (possibly sparse) data from dynamic experiments in a group of subjects and their quantitative interpretation by means of a mathematical model. This methodology is widely used in the pharmaceutical industry (where it is termed "pharmacokinetic population analysis") and recently it is becoming increasingly used in other areas of biomedical research. Unlike traditional kinetic studies, where the number of subjects can be quite small, population kinetic studies require large numbers of subjects. It is, therefore, of great interest to design these studies in the most efficient manner possible, to maximize the information content provided by the data. In this paper we propose an algorithm and a computer program, POPED, for the optimal design of a population kinetic experiment. In particular, the number of samples for each subject and the design of the individual sampling strategies, i.e. the number and location of the time points at which the output variable is sampled, will be considered. Among the various criteria proposed in the literature, D and ED optimality are the ones implemented in our software program, since they are the most widely used. A brief description of the techniques employed to perform design optimization is given, together with some details on their actual implementation. Some examples are then presented to show the program usage and the results provided.

Algorithms↗

PubMed2004

Pubertal changes in HOMA and QUICKI: relationship to hepatic and peripheral insulin sensitivity.

BACKGROUND: Homeostasis model assessment (HOMA) and quantitative insulin-sensitivity check index (QUICKI) are measures of insulin resistance and insulin sensitivity derived from fasting glucose (FG) and insulin levels. They thus should reflect, in principle, insulin action on both the liver and the periphery. METHODS: Twenty-three prepubertal and early pubertal adolescents were studied at baseline and after 6 months, using the frequently sampled intravenous glucose tolerance test (IVGTT) with labeled glucose. Total body insulin sensitivity (SI) was calculated using the minimal model and total glucose concentrations. Peripheral insulin sensitivity (SI*) was calculated from labeled glucose concentrations. Hepatic insulin resistance (HIR) was calculated by multiplying glucose production over the last hour by the average insulin level. HOMA and QUICKI were calculated from the fasting glucose and insulin values. RESULTS: HOMA, QUICKI fasting insulin, and glucose to insulin ratio were all significantly related to SI (p <0.05) but were not independently related to SI* or HIR. Multiple linear regression analysis revealed that both SI* and HIR independently predicted HOMA and fasting glucose (p <0.1). QUICKI, fasting insulin, and glucose to insulin ratio were not independently related to SI, SI*, or HIR. CONCLUSIONS: HOMA and fasting insulin reflect total body insulin sensitivity and HIR but not peripheral insulin sensitivity in prepubertal and early pubertal adolescents.

Blood Glucose↗

PubMed2004

Assessing convergence of Markov chain Monte Carlo simulations in hierarchical Bayesian models for population pharmacokinetics.

Advances in computer hardware and the associated computer-intensive algorithms made feasible by these advances [like Markov chain Monte Carlo (MCMC) data analysis techniques] have made possible the application of hierarchical full Bayesian methods in analyzing pharmacokinetic and pharmacodynamic (PK-PD) data sets that are multivariate in nature. Pharmacokinetic data analysis in particular has been one area that has seized upon this technology to refine estimates of drug parameters from sparse data gathered in a large, highly variable population of patients. A drawback in this type of analysis is that it is difficult to quantitatively assess convergence of the Markov chains to a target distribution, and thus, it is sometimes difficult to assess the reliability of estimates gained from this procedure. Another complicating factor is that, although the application of MCMC methods to population PK-PD problems has been facilitated by new software designed for the PK-PD domain (specifically PKBUGS), experts in PK-PD may not have the necessary experience with MCMC methods to detect and understand problems with model convergence. The objective of this work is to provide an example of a set of diagnostics useful to investigators, by analyzing in detail three convergence criteria (namely the Raftery and Lewis, Geweke, and Heidelberger and Welch methods) on a simulated problem and with a rule of thumb of 10,000 chain elements in the Markov chain. We used two publicly available software packages to assess convergence of MCMC parameter estimates; the first performs Bayesian parameter estimation (PKBUGS/WinBUGS), and the second is focused on posterior analysis of estimates (BOA). The main message that seems to emerge is that accurately estimating confidence regions for the parameters of interest is more demanding than estimating the parameter means. Together, these tools provide numerical means by which an investigator can establish confidence in convergence and thus in the estimated parameters derived from hierarchical full Bayesian pharmacokinetic data analysis.

Algorithms↗

PubMed2004

Disposition of artesunate and dihydroartemisinin after administration of artesunate suppositories in children from Papua New Guinea with uncomplicated malaria.

A detailed pharmacokinetic analysis was performed with 47 children from Papua New Guinea with uncomplicated falciparum or vivax malaria treated with artesunate (ARTS) suppositories (Rectocaps) given in two doses of approximately 13 mg/kg of body weight 12 h apart. Following an intensive sampling protocol, samples were assayed for ARTS and its primary active metabolite, dihydroartemisinin (DHA), by liquid chromatography-mass spectrometry. A population pharmacokinetic model was developed to describe the data. Following administration of the first dose, the mean maximal concentrations of ARTS and DHA were 1,085 nmol/liter at 0.9 h and 2,525 nmol/liter at 2.3 h, respectively. The absorption half-life for ARTS was 2.3 h, and the conversion half-life (ARTS to DHA) was 0.27 h, while the elimination half-life of DHA was 0.71 h. The mean common volumes of distribution for ARTS and DHA relative to bioavailability were 42.8 and 2.04 liters/kg, respectively, and the mean clearance values relative to bioavailability were 6 and 2.2 liters/h/kg for ARTS and DHA, respectively. Substantial interpatient variability was observed, and the bioavailability of the second dose relative to that of the first was estimated to be 0.72. The covariates age, sex, and alpha-thalassemia genotype were not influential in the pharmacokinetic model development; but the inclusion of weight as a covariate significantly improved the performance of the model. An ARTS suppositories dose of 10 of 20 mg/kg is appropriate for use in children with uncomplicated malaria.

Aging↗