Causality detection on US mutual fund movements using evolutionary subset time-series

In this paper we develop an evolutionary kernel-based time update algorithm to recursively estimate subset discrete lag models (including fullorder models) with a forgetting factor and a constant term, using the exactwindowed case. The algorithm applies to causality detection when the true relationship occurs with a continuous or a random delay. We then demonstrate the use of the proposed evolutionary algorithm to study the monthly mutual fund data, which come from the 'CRSP Survivor-bias free US Mutual Fund Database'. The results show that the NAV is an influential player on the international stage of global bond and stock markets.

Population pharmacokinetic analysis of mycophenolic acid in renal transplant recipients following oral administration of mycophenolate mofetil

Aim To develop a population pharmacokinetic model for mycophenolic acid in adult kidney transplant recipients, quantifying average population pharmacokinetic parameter values, and between- and within-subject variability and to evaluate the influence of covariates on the pharmacokinetic variability. Methods Pharmacokinetic data for mycophenolic acid and covariate information were previously available from 22 patients who underwent kidney transplantation at the Princess Alexandra Hospital. All patients received mycophenolate mofetil 1 g orally twice daily. A total of 557 concentration-time points were available. Data were analysed using the first-order method in NONMEM (version 5 level 1.1) using the G77 FORTRAN compiler. Results The best base model was a two-compartment model with a lag time (apparent oral clearance was 271 h(-1), and apparent volume of the central compartment 981). There was visual evidence of complex absorption and time-dependent clearance processes, but they could not be successfully modelled in this study. Weight was investigated as a covariate, but no significant relationship was determined. Conclusions The complexity in determining the pharmacokinetics of mycophenolic acid is currently underestimated. More complex pharmacokinetic models, though not supported by the limited data collected for this study, may prove useful in the future. The large between-subject and between-occasion variability and the possibility of nonlinear processes associated with the pharmacokinetics of mycophenolic acid raise questions about the value of the use of therapeutic monitoring and limited sampling strategies.

Sampling times for monitoring tacrolimus in stable adult liver transplant recipients

The aim of this study was to determine the most informative sampling time(s) providing a precise prediction of tacrolimus area under the concentration-time curve (AUC). Fifty-four concentration-time profiles of tacrolimus from 31 adult liver transplant recipients were analyzed. Each profile contained 5 tacrolimus whole-blood concentrations (predose and 1, 2, 4, and 6 or 8 hours postdose), measured using liquid chromatography-tandem mass spectrometry. The concentration at 6 hours was interpolated for each profile, and 54 values of AUC(0-6) were calculated using the trapezoidal rule. The best sampling times were then determined using limited sampling strategies and sensitivity analysis. Linear mixed-effects modeling was performed to estimate regression coefficients of equations incorporating each concentration-time point (C0, C1, C2, C4, interpolated C5, and interpolated C6) as a predictor of AUC(0-6). Predictive performance was evaluated by assessment of the mean error (ME) and root mean square error (RMSE). Limited sampling strategy (LSS) equations with C2, C4, and C5 provided similar results for prediction of AUC(0-6) (R-2 = 0.869, 0.844, and 0.832, respectively). These 3 time points were superior to C0 in the prediction of AUC. The ME was similar for all time points; the RMSE was smallest for C2, C4, and C5. The highest sensitivity index was determined to be 4.9 hours postdose at steady state, suggesting that this time point provides the most information about the AUC(0-12). The results from limited sampling strategies and sensitivity analysis supported the use of a single blood sample at 5 hours postdose as a predictor of both AUC(0-6) and AUC(0-12). A jackknife procedure was used to evaluate the predictive performance of the model, and this demonstrated that collecting a sample at 5 hours after dosing could be considered as the optimal sampling time for predicting AUC(0-6).

Free mycophenolic acid should be monitored in renal transplant recipients with hypoalbuminemia

The current approach for therapeutic drug monitoring in renal transplant recipients receiving mycophenolate mofetil (MMF) is measurement of total mycophenolic acid (MPA) concentration. Because MPA is highly bound, during hypoalbuminemia the total concentration no longer reflects the free (pharmacologically active) concentration. The authors investigated what degree of hypoalbuminemia causes a significant change in protein binding and thus percentage free MPA. Forty-two renal transplant recipients were recruited for the study. Free and total concentrations of MPA (predose, and 1, 3, and 6 hours post-MMF dose samples) and plasma albumin concentrations were determined on day 5 posttransplantation. Six-hour area under the concentration-time curve (AUC(0-6)) values were calculated for free and total MPA, and percentage free MPA was determined for each patient. The authors found a significant relationship between low albumin concentrations and increased percentage free MPA (Spearman correlation = -0.54, P < 0.0001). Receiver operating characteristic (ROC) curve analysis was performed on the albumin versus percentage free MPA data. The cutoff value of albumin determined from the ROC analysis that differentiated normal from elevated percentage free MPA (defined as greater than or equal to3%) in this patient population was 31 g/L. At this cutoff value albumin was found to be a good predictor of altered free MPA percentage, with a sensitivity and specificity of 0.75 and 0.80, respectively, and an area under the ROC curve of 0.79. To rationalize MMF dosing regimens in hypoalbuminemic patients (plasma albumin less than or equal to 31 g/L), clinicians should consider monitoring the free MPA concentration.

Frequency and temporal effects in linear optical quantum computing

Typically linear optical quantum computing (LOQC) models assume that all input photons are completely indistinguishable. In practice there will inevitably be nonidealities associated with the photons and the experimental setup which will introduce a degree of distinguishability between photons. We consider a nondeterministic optical controlled-NOT gate, a fundamental LOQC gate, and examine the effect of temporal and spectral distinguishability on its operation. We also consider the effect of utilizing nonideal photon counters, which have finite bandwidth and time response.

Echinacea alkamide disposition and pharmacokinetics in humans after tablet ingestion

Echinacea is a widely used herbal remedy for the treatment of colds and other infections. However, almost nothing is known about the disposition and pharmacokinetics of any of its components, particularly the alkamides and caffeic acid conjugates which are thought to be the active phytochemicals. In this investigation, we have examined serial plasma samples from 9 healthy volunteers who ingested echinacea tablets manufactured from ethanolic liquid extracts of Echinacea angustifolia and Echinacea purpurea immediately after a standard high fat breakfast. Caffeic acid conjugates could not be identified in any plasma sample at any time after tablet ingestion. Alkamides were rapidly absorbed and were measurable in plasma 20 min after tablet ingestion and remained detectable for up to 12 h. Concentration-time curves for 2,4-diene and 2-ene alkamides were determined. The maximal concentrations for the sum of alkamides in human plasma were reached within 2.3 h post ingestion and averaged 336 +/- 131 ng eq/mL plasma. No obvious differences were observed in the pharmacokinetics of individual or total alkamides in 2 additional fasted subjects who took the same dose of the echinacea preparation. This single dose study provides evidence that alkamides are orally available and that their pharmacokinetics are in agreement with the one dose three times daily regimen already recommended for echinacea.

The population pharmacokinetics of citalopram after deliberate self-poisoning: A Bayesian approach

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.

Analysis of population pharmacokinetic data using NONMEM and WinBUGS

The aim of this report is to describe the use of WinBUGS for two datasets that arise from typical population pharmacokinetic studies. The first dataset relates to gentamicin concentration-time data that arose as part of routine clinical care of 55 neonates. The second dataset incorporated data from 96 patients receiving enoxaparin. Both datasets were originally analyzed by using NONMEM. In the first instance, although NONMEM provided reasonable estimates of the fixed effects parameters it was unable to provide satisfactory estimates of the between-subject variance. In the second instance, the use of NONMEM resulted in the development of a successful model, albeit with limited available information on the between-subject variability of the pharmacokinetic parameters. WinBUGS was used to develop a model for both of these datasets. Model comparison for the enoxaparin dataset was performed by using the posterior distribution of the log-likelihood and a posterior predictive check. The use of WinBUGS supported the same structural models tried in NONMEM. For the gentamicin dataset a one-compartment model with intravenous infusion was developed, and the population parameters including the full between-subject variance-covariance matrix were available. Analysis of the enoxaparin dataset supported a two compartment model as superior to the one-compartment model, based on the posterior predictive check. Again, the full between-subject variance-covariance matrix parameters were available. Fully Bayesian approaches using MCMC methods, via WinBUGS, can offer added value for analysis of population pharmacokinetic data.

Relationships of tacrolimus pharmacokinetic measures and adverse outcomes in stable adult liver transplant recipients

Alternative measures to trough concentrations [non-trough concentrations and limited area under the concentration-time curve (AUC)] have been shown to better predict tacrolimus AUC. The aim of this study was to determine if these are also better predictors of adverse outcomes in long term liver transplant recipients. The associations between tacrolimus trough concentrations (C-0), non-trough concentrations (C-1, C-2, C-4, C-6/8), and AUC(0-12) and the occurrence of hypertension, hyperkalaemia, hyperglycaemia and nephrotoxicity were assessed in 34 clinically stable liver transplant patients. The most common adverse outcome was hypertension, prevalence of 36%. Hyperkalaemia and hyperglycaemia had a prevalence of 21% and 13%, respectively. A sequential population pharmacokinetic/pharmacodynamic approach was implemented. No significant association between predicted C-0, C-1, C-2, C-4, C-6/8 or AUC(0-12) and adverse effects could be found. Tacrolimus concentrations and AUC measures were in the same range in patients with and without adverse effects. Measures reported to provide benefit, preventing graft rejection and minimizing acute adverse effects in the early post-transplant period, were not able to predict adverse effects in stable adult liver recipients whose trough concentrations were maintained in the notional target range.

Recommendations and guidelines for the performance of accurate heat transfer measurements in rapid forming processes

The published requirements for accurate measurement of heat transfer at the interface between two bodies have been reviewed. A strategy for reliable measurement has been established, based on the depth of the temperature sensors in the medium, on the inverse method parameters and on the time response of the sensors. Sources of both deterministic and stochastic errors have been investigated and a method to evaluate them has been proposed, with the help of a normalisation technique. The key normalisation variables are the duration of the heat input and the maximum heat flux density. An example of application of this technique in the field of high pressure die casting is demonstrated. The normalisation study, coupled with previous determination of the heat input duration, makes it possible to determine the optimum location for the sensors, along with an acceptable sampling rate and the thermocouples critical response-time (as well as eventual filter characteristics). Results from the gauge are used to assess the suitability of the initial design choices. In particular the unavoidable response time of the thermocouples is estimated by comparison with the normalised simulation. (c) 2006 Elsevier Ltd. All rights reserved.

Development of a semimechanistic model to describe the pharmacokinetics of gentamicin in patients receiving Hemodialysis

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.

Dosing of gentamicin in patients with end-stage renal disease receiving hemodialysis

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.

Bayesian population pharmacokinetic analysis of sirolimus

Objective: It is usual that data collected from routine clinical care is sparse and unable to support the more complex pharmacokinetic (PK) models that may have been reported in previous rich data studies. Informative priors may be a pre-requisite for model development. The aim of this study was to estimate the population PK parameters of sirolimus using a fully Bayesian approach with informative priors. Methods: Informative priors including prior mean and precision of the prior mean were elicited from previous published studies using a meta-analytic technique. Precision of between-subject variability was determined by simulations from a Wishart distribution using MATLAB (version 6.5). Concentration-time data of sirolimus retrospectively collected from kidney transplant patients were analysed using WinBUGS (version 1.3). The candidate models were either one- or two-compartment with first order absorption and first order elimination. Model discrimination was based on computation of the posterior odds supporting the model. Results: A total of 315 concentration-time points were obtained from 25 patients. Most data were clustered at trough concentrations with range of 1.6 to 77 hours post-dose. Using informative priors, either a one- or two-compartment model could be used to describe the data. When a one-compartment model was applied, information was gained from the data for the value of apparent clearance (CL/F = 18.5 L/h), and apparent volume of distribution (V/F = 1406 L) but no information was gained about the absorption rate constant (ka). When a two-compartment model was fitted to the data, the data were informative about CL/F, apparent inter-compartmental clearance, and apparent volume of distribution of the peripheral compartment (13.2 L/h, 20.8 L/h, and 579 L, respectively). The posterior distribution of the volume distribution of central compartment and ka were the same as priors. The posterior odds for the two-compartment model was 8.1, indicating the data supported the two-compartment model. Conclusion: The use of informative priors supported the choice of a more complex and informative model that would otherwise have not been supported by the sparse data.