Comparison of three physiologically based pharmacokinetic models of benzene disposition

Bois, Frédéric Y.; Woodruff, Tracey J.; Spear, Robert C.

doi:10.1016/0041-008x(91)90291-l

Cited by 47 publications

(23 citation statements)

References 23 publications

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“…In the longer term, it would be exciting to couple the present work with pharmacokinetic modeling of the transport, transformation, and fates of key chemical constituents within the body. Such methods are presently being applied to inhalation exposure to gaseous pollutants, such as benzene (Bois et al, 1991) and hold considerable promise for improving our understanding of the health effects of air pollutants.…”

Section: Future Directionsmentioning

confidence: 99%

Predicting Regional Lung Deposition of Environmental Tobacco Smoke Particles

Nazaroff¹,

Hung²,

Sasse³

et al. 1993

Aerosol Science and Technology

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Inhalation exposure to environmental tobacco smoke (ETS) particles may increase health risks, but only to the extent that the particles deposit in the respiratory tract. We describe a technique to predict regional lung deposition of environmental tobacco smoke particles. Interpretation of particle size distribution measurements after cigarette combustion by a smoking machine in a test room yields an effective emissions profile. An aerosol dynamics model is used to predict indoor particle concentrations resulting from a specified combination of smoking frequency and building factors. By utilizing a lung deposition model, the rate of ETS mass accumulation in human lungs is then determined as a function of particle size and lung airway generation. Considering emissions of sidestream smoke only, residential exposures of nonsmokers to ETS are predicted to cause rates of total respiratory tract particle deposition in the range of 0.4-0.7 pg/day per kg of body weight for light smoking in a well-ventilated residence and 8-13 pg/day per kg for moderately heavy smoking in a poorly ventilated residence. Emissions of sidestream plus mainstream smoke lead to predicted deposition rates about a factor of 4 higher. This technique should be useful for evaluating health risks and control techniques associated with exposure to ETS particles.

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Section: Future Directionsmentioning

confidence: 99%

Predicting Regional Lung Deposition of Environmental Tobacco Smoke Particles

Nazaroff¹,

Hung²,

Sasse³

et al. 1993

Aerosol Science and Technology

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“…The MC method is based on a reconstruction of the prior probability distributions of the parameters involved and produces the probability distribution of the scaled in vivo clearance, which includes a description of the parameter variability. This approach, although widely used in other pharmacokinetic modeling areas (Farrar et al, 1989;Hattis et al, 1990;Bois et al, 1991;Gearhart et al, 1993;Krewski et al, 1995), has several major drawbacks when applied to in vitro-in vivo clearance predictions. Reconstructing a prior statistical distribution from (as a rule) a small sample can often introduce a dmd.aspetjournals.org significant bias.…”

Section: Discussionmentioning

confidence: 99%

“…The usual procedure for incorporating measures of variability and uncertainty into pharmacokinetic modeling is Monte Carlo (MC 1 ) simulation (Farrar et al, 1989;Bois et al, 1991;Hattis et al, 1990;Gearhart et al, 1993;Krewski et al, 1995). The core of this procedure is the specification of prior model parameter probability distribution functions (pdfs).…”

Section: Methodsmentioning

confidence: 99%

“…This practice is a source of the following concerns. First, handling single values in the presence of significant variability and uncertainty is inappropriate and may be misleading (Farrar et al, 1989;Bois et al, 1991;Hattis et al, 1990;Gearhart et al, 1993;Krewski et al, 1995). Usually derived from a small sample, the mean may not be representative or even meaningful.…”

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confidence: 99%

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Incorporating Measures of Variability and Uncertainty into the Prediction of in Vivo Hepatic Clearance from in Vitro Data

Nestorov

Gueorguieva²,

Jones³

et al. 2002

Drug Metab Dispos

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ABSTRACT:The existing procedures for quantitative in vitro-in vivo clearance prediction can be significantly biased either by totally neglecting the existing variability and uncertainty by using mean parameter values or by implementing Monte Carlo simulation with statistical distribution of the parameters reconstructed from very small sets of data. The aim of the present study is to develop a methodology for the prediction of in vivo hepatic clearance in the presence of semiquantitative or qualitative data and accounting for the existing uncertainty and variability. The method consists of two steps: 1) transformation of the information available into fuzzy sets (fuzzification); and 2) computation of the in vivo clearance using arithmetic operations with fuzzy sets. To illustrate the approach, rat hepatocyte and microsomal data for eight benzodiazepine compounds are used. A comparison with a standard Monte Carlo procedure is made. The methodology proposed can be used when Monte Carlo simulation may be biased or cannot be implemented. The obtained fuzzy in vivo clearance can be used subsequently in fuzzy simulations of pharmacokinetic models.The ability to predict pharmacokinetic events in vivo, especially in humans, from in vitro data and other relevant information is of great importance both to academia in providing a quantitative framework for identification and investigation of the key processes involved and to industry in facilitating drug selection and development. Of all the pharmacokinetic parameters, most work in this endeavor has concentrated on the prediction of hepatic (metabolic) clearance. It usually comprises a series of sequential steps, starting from the estimation of intrinsic clearance in the in vitro system, through the identification of appropriate scaling coefficients, and ending with the implementation of a liver model. The ultimate goal is to achieve as accurate a quantitative prediction of the in vivo hepatic clearance as possible.The information used and generated throughout the in vitro-in vivo clearance prediction process is characterized by a large degree of uncertainty and significant variation in the experimental values Iwatsubo et al., 1997; Lavè et al., 1997;Obach et al., 1997) due to a number of highly related reasons. These include the complexity and sometimes unknown nature of the phenomena involved, the imperfect instrumentation and information processing tools, and the high inherent variability of the biological systems. The terms variability and uncertainty are used almost interchangeably in the pharmacokinetic and metabolism literature. It should be noted, however, that variability is an inherent property of the system of interest; it can be observed and recorded but not changed. In contrast, uncertainty relates to variations due to errors in assumptions, hypotheses, observations, experiments, and handling of the system studied. Accordingly, uncertainty in the information available can be decreased and theoretically eliminated by implementing "ideal" experiments and data-pro...

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“…The results of the field studies illustrated the utility of monitoring workers for exposures at numerous times throughout the day, particularly when jobspecific tasks may indicate a potential for exposure (121 ). Although PBPK models are powerful and have many successful applications, they require knowledge of a much larger number of variables, some of which are difficult to obtain quantitative information (122 ).…”

Section: Assessment Of Exposure To Vocsmentioning

confidence: 99%

Breath Analysis: Potential for Clinical Diagnosis and Exposure Assessment

Cao¹,

Duan²

2006

Clinical Chemistry

364

238

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Breath tests are among the least invasive methods available for clinical diagnosis, disease state monitoring, and environmental exposure assessment. In recent years, interest in breath analysis for clinical purposes has increased. This review is intended to describe the potential applications of breath tests, including clinical diagnosis of diseases and monitoring of environmental pollutant exposure, with emphasis on oxidative stress, lung diseases, metabolic disorder, gastroenteric diseases, and some other applications. The application of breath tests in assessment of exposure to volatile organic compounds is also addressed. Finally, both the advantages and limitations of breath analysis are summarized and discussed.

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Comparison of three physiologically based pharmacokinetic models of benzene disposition

Cited by 47 publications

References 23 publications

Predicting Regional Lung Deposition of Environmental Tobacco Smoke Particles

Predicting Regional Lung Deposition of Environmental Tobacco Smoke Particles

Incorporating Measures of Variability and Uncertainty into the Prediction of in Vivo Hepatic Clearance from in Vitro Data

Breath Analysis: Potential for Clinical Diagnosis and Exposure Assessment

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