Research to develop a predicting system of mammalian subacute toxicity (3) construction of a predictive toxicokinetics model

Yamaguchi, Takaaki; Yabuki, Masashi; Saito, Shoji; Watanabe, Tomoyuki; Nishimura, Hiroshi; Isobe, Naohiko; Shono, Fumiaki; Matsuo, Masaru

doi:10.1016/s0045-6535(96)00342-6

Cited by 7 publications

(4 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The prediction of biochemical and physicochemical parameters for PBTK models continuesto present a challenge.Development of empirical or mechanistic algorithms is one way of making rapid construction of PBTK models possible (Yamaguchi et al 1996;Krishnan 1996, 1998). We have developed and validated mechanistic algorithms for predicting blood:airand tissue:bloodPCs of organic chemicals from molecular structure information (Poulin and Krishnan 1996), and recently demonstrated that Q l can be used, instead of V max and K m , to describe CL h of HMVOCs in PBTK models (Poulin and Krishnan 1998).…”

Section: Discussionmentioning

confidence: 99%

“…where RAM = rate of the amount of chemical metabolized (mg/hr) CL int = intrinsic clearance ( = V max / K m for ® rst order conditions) V max = maximal velocity (mg/hr) K m = af® nity constant (mg/L) C vl = chemical concentration in venous blood leaving liver (mg/L) Few researchers (Fiserova-Bergerova 1985;Johanson and Naslund 1988;Yamaguchi et al 1996;Poulin and Krishnan 1998) have calculated RAM within PBTK models as follows:…”

Section: Describing Hepatic Metabolism In Pbtk Modelsmentioning

confidence: 99%

See 1 more Smart Citation

Molecular Structure-Based Prediction of the Toxicokinetics of Inhaled Vapors in Humans

Poulin

Krishnan

1999

Int J Toxicol

View full text Add to dashboard Cite

The objectives of the present study were: (1) to evaluate the adequacy of setting hepatic extraction ratio (E) equal to 0 or 1 in physiologically based toxicokinetic (PBTK) models to generate the theoretically plausible envelope of venous blood concentration (Cv) profiles, and (2) to couple this approach with molecular structure-based estimation of blood:air and tissue: blood partition coefficients (PCs) to predictthe Cv profiles of volatile organic chemicals (VOCs) in humans. Setting E= 0 or 1 in PBTK models provided simulations of Cv envelopes that contained the Cv values determined in humans exposed to low concentrations of dichloromethane(DCM), ethylbenzene (EBZ), toluene (TOL), m-xylene(XYL), trichloroethy-lene (TCE), and 1,1,1-trichloroethane(TRI). Following the validation of using E= 0 or 1 in conventional PBTK models to predict the theoretically plausible envelope of Cv, a quantitative structure-toxicokinetic relationship (QSTkR) model was constructed. The QSTkR model used molecular structure information as the sole input to predict the PCs and considered E= 0 or 1 to generate simulations of the envelope of Cv. The experimental data on Cv were in most cases within the envelopes simulated using QSTkR models for DCM, EBZ, TOL, and XYL, but were outside the envelopes for TCE and TRI. The discrepancy observed between the Cv envelopes obtained using PBTK and QSTkR models can be explained by the fact that blood:air PCs of some VOCs were under-predicted while using molecular structure information. The modeling framework presented in this article represents the first animal-replacement tool that can provide a priori predictions of the toxicokinetic profiles of VOCs prior to laboratory experiments.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Describing Hepatic Metabolism In Pbtk Modelsmentioning

confidence: 99%

Molecular Structure-Based Prediction of the Toxicokinetics of Inhaled Vapors in Humans

Poulin

Krishnan

1999

Int J Toxicol

View full text Add to dashboard Cite

show abstract

“…Several PBPK models were developed and validated in the environmental sciences and pharmaceutical academia 1–6. So far, however, PBPK models were rarely used in drug discovery.…”

Section: Introductionmentioning

confidence: 99%

“…Thus, mechanism‐based PBPK models of drug disposition using only in vitro and in silico input data can potentially be developed also in the early drug discovery. In contrast, the conventional PBPK models of drug disposition available in the literature4,5 could not be used in drug discovery because their input parameters were estimated by optimization requiring extensive collection of in vivo data including tissue kinetics.…”

Section: Introductionmentioning

confidence: 99%

Prediction of Pharmacokinetics Prior to In Vivo Studies. II. Generic Physiologically Based Pharmacokinetic Models of Drug Disposition

Poulin

Theil

2002

Journal of Pharmaceutical Sciences

280

199

View full text Add to dashboard Cite

Physiologically-Based Pharmacokinetic (PBPK) Models in Toxicity Testing and Risk Assessment

Lipscomb

Haddad

Poet

et al. 2012

Advances in Experimental Medicine and Biology

View full text Add to dashboard Cite

Physiologically-based pharmacokinetic (PBPK) modeling offers a scientifically-sound framework for integrating mechanistic data on absorption, distribution, metabolism and elimination to predict the time-course of parent chemical, metabolite(s) or biomarkers in the exposed organism. A major advantage of PBPK models is their ability to forecast the impact of specific mechanistic processes and determinants on the tissue dose. In this regard, they facilitate integration of data obtained with in vitro and in silico methods, for making predictions of the tissue dosimetry in the whole animal, thus reducing and/or refining the use of animals in pharmacokinetic and toxicity studies. This chapter presents the principles and practice of PBPK modeling, as well as the application of these models in toxicity testing and health risk assessments.

show abstract

Research to develop a predicting system of mammalian subacute toxicity (3) construction of a predictive toxicokinetics model

Cited by 7 publications

References 15 publications

Molecular Structure-Based Prediction of the Toxicokinetics of Inhaled Vapors in Humans

Molecular Structure-Based Prediction of the Toxicokinetics of Inhaled Vapors in Humans

Prediction of Pharmacokinetics Prior to In Vivo Studies. II. Generic Physiologically Based Pharmacokinetic Models of Drug Disposition

Physiologically-Based Pharmacokinetic (PBPK) Models in Toxicity Testing and Risk Assessment

Contact Info

Product

Resources

About