BUGS is a software package for Bayesian inference using Gibbs sampling. The software has been instrumental in raising awareness of Bayesian modelling among both academic and commercial communities internationally, and has enjoyed considerable success over its 20-year life span. Despite this, the software has a number of shortcomings and a principal aim of this paper is to provide a balanced critical appraisal, in particular highlighting how various ideas have led to unprecedented flexibility while at the same time producing negative side effects. We also present a historical overview of the BUGS project and some future perspectives. Copyright © 2009 John Wiley & Sons, Ltd.

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The BUGS project: Evolution, critique and future directions

Seventy-four acutely ill patients were treated with intravenous ciprofloxacin at dosages ranging between 200 mg every 12 h and 400 mg every 8 h. A population pharmacokinetic-pharmacodynamic analysis relating drug exposure (and other factors) to infectious outcome was performed. Plasma samples were obtained and assayed for ciprofloxacin by high-performance liquid chromatography. Samples from patients were frequently cultured so that the day of bacterial eradication could be determined. The pharmacokinetic data were fitted by iterative two-stage analysis, assuming a linear two-compartment model. Logistic regression was used to model ciprofloxacin exposure (and other potential covariates) versus the probabilities of achieving clinical and microbiologic cures. The same variables were also modelled versus the time to bacterial eradication by proportional hazards regression. The independent variables considered were dose, site of infection, infecting organism and the MIC for it, percent time above the MIC, peak, peak/MIC ratio, trough, trough/MIC ratio, 24-h area under the concentration-time curve (AUC), AUC/MIC ratio (AUIC), presence of other active antibacterial agents, and patient characteristics. The most important predictor for all three measures of ciprofloxacin pharmacodynamics was the AUIC. A 24-h AUIC of 125 SIT-1.h (inverse serum inhibitory titer integrated over time) was found to be a significant breakpoint for probabilities of both clinical and microbiologic cures. At an AUIC below 125 (19 patients), the percent probabilities of clinical and microbiologic cures were 42 and 26%, respectively. At an AUIC above 125 (45 patients), the probabilities were 80% (P < 0.005) and 82% (P < 0.001), respectively. There were two significant breakpoints in the time-to-bacterial-eradication data. At an AUIC below 125 (21 patients), the median time to eradication exceeded 32 days; at an AUIC of 125 to 250 (15 patients), time to eradication was 6.6 days: and at AUIC above 250 (28 patients), the median time to eradication was 1.9 days (groups differed; P < 0.005). These findings, when combined with pharmacokinetic data reported in the companion article, provide the rationale and tools needed for targeting the dosage of intravenous ciprofloxacin to individual patients' pharmacokinetics and their bacterial pathogens' susceptibilities. An a priori dosing algorithm (based on MIC, patient creatine clearance and weight, and the clinician-specified AUIC target) was developed. This approach was shown, retrospectively, to be more precise than current guidelines, and it can be used to achieve more rapid bacteriologic and clinical responses to ciprofloxacin, as a consequence of targeting the AUIC.

Pharmacodynamics of intravenous ciprofloxacin in seriously ill patients.

Some life tests result in few or no failures. In such cases, it is difficult to assess reliability with traditional life tests that record only time to failure. For some devices, it is possible to obtain degradation measurements over time, and these measurements may contain useful information about product reliability. Even with little or no censoring, there may be important practical advantages to analyzing degradation data. If failure is defined in terms of a specified level of degradation, a degradation model defines a particular time-to-failure distribution. Generally it is not possible to obtain a closed-form expression for this distribution. The purpose of this work is to develop statistical methods for using degradation measures to estimate a time-to-failure distribution for a broad class of degradation models. We use a nonlinear mixed-effects model and develop methods based on Monte Carlo simulation to obtain point estimates and confidence intervals for reliability assessment.

Using Degradation Measures to Estimate a Time-to-Failure Distribution

On developpe une approche basee sur une innovation due a Phillips (1983) sur les approximations des fonctions de densite

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Semi-nonparametric maximum likelihood estimation

Enterohepatic recycling occurs by biliary excretion and intestinal reabsorption of a solute, sometimes with hepatic conjugation and intestinal deconjugation. Cycling is often associated with multiple peaks and a longer apparent half-life in a plasma concentration-time profile. Factors affecting biliary excretion include drug characteristics (chemical structure, polarity and molecular size), transport across sinusoidal plasma membrane and canniculae membranes, biotransformation and possible reabsorption from intrahepatic bile ductules. Intestinal reabsorption to complete the enterohepatic cycle may depend on hydrolysis of a drug conjugate by gut bacteria. Bioavailability is also affected by the extent of intestinal absorption, gut-wall P-glycoprotein efflux and gut-wall metabolism. Recently, there has been a considerable increase in our understanding of the role of transporters, of gene expression of intestinal and hepatic enzymes, and of hepatic zonation. Drugs, disease and genetics may result in induced or inhibited activity of transporters and metabolising enzymes. Reduced expression of one transporter, for example hepatic canalicular multidrug resistance-associated protein (MRP) 2, is often associated with enhanced expression of others, for example the usually quiescent basolateral efflux MRP3, to limit hepatic toxicity. In addition, physiologically relevant pharmacokinetic models, which describe enterohepatic recirculation in terms of its determinants (such as sporadic gall bladder emptying), have been developed. In general, enterohepatic recirculation may prolong the pharmacological effect of certain drugs and drug metabolites. Of particular importance is the potential amplifying effect of enterohepatic variability in defining differences in the bioavailability, apparent volume of distribution and clearance of a given compound. Genetic abnormalities, disease states, orally administered adsorbents and certain coadministered drugs all affect enterohepatic recycling.

Enterohepatic circulation: physiological, pharmacokinetic and clinical implications.

Individual pharmacokinetic parameters can be viewed as independent realizations of a random variable. The probability density function of the variable is assumed to be specified by its first two mo...

Jean-François Boisvieux

Papers

Alternative Approaches to Estimation of Population Pharmacokinetic Parameters: Comparison with the Nonlinear Mixed-Effect Model

A Time-Lag Model for Pharmacokinetics of Drugs Subject to Enterohepatic Circulation

Modelling behavioral syndromes using Bayesian networks.

Finite element simulation of gas transport in proximal respiratory airways: comparison with experimental data.

Quantitative Analysis of Gas Transport in the Central Airways