A Bayesian population PBPK model for multiroute chloroform exposure

Yang, Yuching; Xu, Xu; Georgopoulos, Panos G.

doi:10.1038/jes.2009.29

Cited by 39 publications

(20 citation statements)

References 58 publications

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“…The body is subdivided into various compartments representing specific organs or homogeneous groups of tissues linked and irrigated by blood vessels (Yang et al, 2010). The output (lung dose, blood dose and GI_tract dose) from the ExDoM model was used as input for PBPK model.…”

Section: Application Of a Pbpk Model For Calculating The Dose Of Metamentioning

confidence: 99%

Personal Exposure and Dose of Inhaled Ambient Particulate Matter Bound Metals in Five European Cities

Mammi-Galani

Chalvatzaki

Lazaridis

2016

Aerosol Air Qual. Res.

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The objective of the current study is the determination of the personal exposure and dose of ambient particulate matterbound metals in human tissues at five European cities. The accumulation in human body of lead (Pb), arsenic (As) and cadmium (Cd), in five European cities (Athens, Seville, Rome, Frankfurt and Zabrze) was calculated using an exposure and dose assessment model, ExDoM, and a pharmacokinetic model, PBPK. The study subjects are adult Caucasian nonsmoker males. It was calculated that the highest dose of particulate matter is received from a resident of Seville, due to the higher ambient PM 10 levels in the city compared to the other sites. First, the current study showed that the European Union thresholds of particle-bound Pb, Cd and As concentrations were not exceeded in the cities under study. As regard the dose of Pb and As the higher dose is calculated for Athens and Seville, respectively. The highest dose of Cd is found at Zabrze, due to the high industrial activity in the city. It was calculated that after one day of exposure, the highest accumulation of Pb occurred in blood, muscles and bones. Furthermore, the highest deposition of Cd occurred in the lungs and intestines and for As in the lung and muscles. The heavy metals intake, calculated in this study, was very low in comparison with the recommended WHO levels for heavy metals intake from all types of exposure (inhalation, ingestion).

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Section: Application Of a Pbpk Model For Calculating The Dose Of Metamentioning

confidence: 99%

Personal Exposure and Dose of Inhaled Ambient Particulate Matter Bound Metals in Five European Cities

Mammi-Galani

Chalvatzaki

Lazaridis

2016

Aerosol Air Qual. Res.

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“…Related work in applying Bayesian techniques to PBPK modeling to the toxicokinetics of environmental xenobiotics must also be mentioned . Those authors were primarily concerned with forward predictions of exposure profiles that were consistent with observed PK profiles.…”

Section: Discussionmentioning

confidence: 99%

A Novel Method for Assessing Drug Degradation Product Safety Using Physiologically-Based Pharmacokinetic Models and Stochastic Risk Assessment

Nguyen

Stamatis

Kirsch

2015

Journal of Pharmaceutical Sciences

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“…In a typical Bayesian analysis these distributions are produced by Markov-chain Monte Carlo (MCMC) methods. The reader is referred to [44] for an introduction on the Bayesian hierarchical approach and to [33,43,[55][56][57][58] for related applications in physiologically based toxicokinetic and pharmacokinetic modelling.…”

Section: The Bayesian Perspectivementioning

confidence: 99%

Combining the ‘bottom up’ and ‘top down’ approaches in pharmacokinetic modelling: fittingPBPKmodels to observed clinical data

Tsamandouras

Rostami‐Hodjegan

Aarons

2014

Brit J Clinical Pharma

219

186

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Pharmacokinetic models range from being entirely exploratory and empirical, to semi-mechanistic and ultimately complex physiologically based pharmacokinetic (PBPK) models. This choice is conditional on the modelling purpose as well as the amount and quality of the available data. The main advantage of PBPK models is that they can be used to extrapolate outside the studied population and experimental conditions. The trade-off for this advantage is a complex system of differential equations with a considerable number of model parameters. When these parameters cannot be informed from in vitro or in silico experiments they are usually optimized with respect to observed clinical data. Parameter estimation in complex models is a challenging task associated with many methodological issues which are discussed here with specific recommendations. Concepts such as structural and practical identifiability are described with regards to PBPK modelling and the value of experimental design and sensitivity analyses is sketched out. Parameter estimation approaches are discussed, while we also highlight the importance of not neglecting the covariance structure between model parameters and the uncertainty and population variability that is associated with them. Finally the possibility of using model order reduction techniques and minimal semi-mechanistic models that retain the physiological-mechanistic nature only in the parts of the model which are relevant to the desired modelling purpose is emphasized. Careful attention to all the above issues allows us to integrate successfully information from in vitro or in silico experiments together with information deriving from observed clinical data and develop mechanistically sound models with clinical relevance.

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A Bayesian population PBPK model for multiroute chloroform exposure

Cited by 39 publications

References 58 publications

Personal Exposure and Dose of Inhaled Ambient Particulate Matter Bound Metals in Five European Cities

Personal Exposure and Dose of Inhaled Ambient Particulate Matter Bound Metals in Five European Cities

A Novel Method for Assessing Drug Degradation Product Safety Using Physiologically-Based Pharmacokinetic Models and Stochastic Risk Assessment

Combining the ‘bottom up’ and ‘top down’ approaches in pharmacokinetic modelling: fittingPBPKmodels to observed clinical data

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