Influence of lipophilicity and lysosomal accumulation on tissue
distribution kinetics of basic drugs: A physiologically based
pharmacokinetic model

Yamashita, Koichi; Ishizaki, Junko; Ohkuma, Shoji; Miyamoto, K

doi:10.1358/mf.2002.24.2.677131

Cited by 52 publications

(36 citation statements)

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“…Excluding the fraction un-ionized terms from calculations led to the underprediction of V ss for most of the strongly basic compounds by 2-to 4-fold. Per the pH partition hypothesis, such pH gradients have been thought to enhance the partition of basic drugs into tissues and certain subcellular organelles, such as lysosomes, whereas the pH tends to be lower than that in blood (Harashima et al, 1984;Yokogawa et al, 2002;Gong et al, 2007). This observation led to the incorporation of pH effects into modified tissue composition equations that, among other modifications, helped to improve the prediction of V ss for strong bases using physicochemical property data (Rodgers et al, 2005).…”

Section: Discussionmentioning

confidence: 99%

Prediction of V_ss from In Vitro Tissue-Binding Studies

Berry¹,

Roberts²,

Be³

et al. 2009

Drug Metab Dispos

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ABSTRACT:To predict volume of distribution at steady-state (V ss ), empirical (e.g., allometry) and mechanistic (using physicochemical property data and plasma protein binding) methods have been used. None of these approaches has been able to predict V ss accurately for the total compliment of a wide range of drugs. Therefore, alternative approaches would be of value. This study evaluates the utility of in vitro nonspecific tissue-binding measurements in predicting V ss for a wide range of drugs in rats. Literature as well as proprietary compounds were studied. It was found that in vitro tissue-binding measurements combined with calculated effects of the pH partition hypothesis often predict V ss more accurately than other available mechanistic methods and that this approach can compliment existing methods. The V ss values for some compounds were not accurately predicted using either nonspecific tissue-binding experiments or other available mechanistic methods. The V ss for these drugs may not be describable by nonspecific tissue binding alone; there may be significant specific components to the mechanism of distribution for these drugs, such as pH-dependent uptake into lysosomes (primarily strongly basic drugs), active transport, and/or enterohepatic recirculation. A lack of prediction for certain drugs warrants further investigation into these mechanisms and their application to more accurate prediction of V ss by mechanistic means.The apparent volume of distribution at steady state (V ss ) is one of the primary descriptive terms derived from pharmacokinetic (PK) analysis of the concentration-time profile after intravenous administration of drugs.

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Section: Discussionmentioning

confidence: 99%

Prediction of V_ss from In Vitro Tissue-Binding Studies

Berry¹,

Roberts²,

Be³

et al. 2009

Drug Metab Dispos

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“…Cathepsin D, a lysosomal protease, can either induce the cleavage of Bid, which leads to cytochrome c release and subsequent caspase activation (Stoka et al, 2001), or trigger Bax activation, which induces the selective release of mitochondrial AIF (Bidere et al, 2003). Imipramine could then act at the lysosomal level, but also through modification of the lipid raft structure and functions (Yokogawa et al, 2002).…”

Section: Discussionmentioning

confidence: 99%

Overcoming resistance to γ-rays in squamous carcinoma cells by poly-drug elevation of ceramide levels

et al. 2004

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“…These and many other such models rely upon data derived from in vivo studies to estimate the extent of tissue distribution. Although computational models for predicting in vivo tissue/plasma partition coefficients from physicochemical and biochemical properties have been developed (Yokogawa et al, 1990(Yokogawa et al, , 2002Poulin and Theil, 2000;Rodgers, 2003), these are not generally applicable, being appropriate only for a particular class of basic compounds (Rodgers, 2003), for bases in general (Yokogawa et al, 1990(Yokogawa et al, , 2002, or requiring modification of the fundamental model, depending upon distribution characteristics that cannot be established in advance with any certainty for novel compounds (Poulin and Theil, 2000). Furthermore, many of the published PBPK models for the rat also utilize estimates of clearance determined in vivo Bernareggi and Rowland, 1991;Blakey et al, 1997).…”

Section: Introductionmentioning

confidence: 99%

“…The parameter P m S m (Fig. 1) was optimized across the training set and fixed at the same value for all compounds.Intracellular space/interstitial fluid (unbound) partition coefficients (Kp IC:IFu ) were calculated for each compound using a model developed by Yokogawa et al (1990Yokogawa et al ( , 2002, which predicts tissue partition coefficients from a measure of lipophilicity and appropriate estimates of tissue lipid content. In this work, an estimate of the effective in vivo lipophilicity was used in the calculation, rather than a measure of actual lipophilicity (i.e., an experimental or calculated logP).…”

mentioning

confidence: 99%

Application of a Generic Physiologically Based Pharmacokinetic Model to the Estimation of Xenobiotic Levels in Rat Plasma

Brightman¹,

Leahy²,

Searle³

et al. 2005

Drug Metab Dispos

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ABSTRACT:The routine assessment of xenobiotic in vivo kinetic behavior is currently dependent upon data obtained through animal experimentation, although in vitro surrogates for determining key absorption, distribution, metabolism, and elimination properties are available. Here we present a unique, generic, physiologically based pharmacokinetic (PBPK) model and demonstrate its application to the estimation of rat plasma pharmacokinetics, following intravenous dosing, from in vitro data alone. The model was parameterized through an optimization process, using a training set of in vivo data taken from the literature and validated using a separate test set of in vivo discovery compound data. On average, the vertical divergence of the predicted plasma concentrations from the observed data, on a semilog concentration-time plot, was approximately 0.5 log unit. Around 70% of all the predicted values of a standardized measure of area under the concentration-time curve (AUC) were within 3-fold of the observed values, as were over 90% of the training set t 1/2 predictions and 60% of those for the test set; however, there was a tendency to overpredict t 1/2 for the test set compounds. The capability of the model to rank compounds according to a given criterion was also assessed: of the 25% of the test set compounds ranked by the model as having the largest values for AUC, 61% were correctly identified. These validation results lead us to conclude that the generic PBPK model is potentially a powerful and cost-effective tool for predicting the mammalian pharmacokinetics of a wide range of organic compounds, from readily available in vitro inputs only.Physiologically based pharmacokinetic (PBPK) models are mathematical descriptions of the flow of blood throughout the body, developed for the simulation of xenobiotic absorption, distribution, and elimination. The essential concepts were outlined over 60 years ago in a farsighted paper (Teorell, 1937) that presented many of the mathematical relationships required to simulate blood flow and tissue distribution.Simulation modeling ideas were developed further by Mapleson (1973), to explain the effect of anesthetics, and early attempts to apply the approach to drugs were published in the 1960s by Bellman et al. (1961). Probably the most important contributions in that period were made by Bischoff and Dedrick (1968), who demonstrated that PBPK models could be used for the a priori prediction of the pharmacokinetics of thiopental. During the following decades, developments were made by academics such as Rowland (Rowland, 1986), Sugiyama (Sugiyama and Ito, 1998), and Amidon (Yu and Amidon, 1999), as well as scientists working in the environmental health field, in particular Anderson and Clewell (Andersen et al., 2002). Recent reviews (Grass and Sinko, 2002;Leahy, 2003) have discussed the application of these approaches to the prediction of pharmacokinetics in drug discovery.It is of interest to us to apply the PBPK approach to the estimation of plasma levels in animals from in vitro d...

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Influence of lipophilicity and lysosomal accumulation on tissue distribution kinetics of basic drugs: A physiologically based pharmacokinetic model

Cited by 52 publications

References 0 publications

Prediction of V_ss from In Vitro Tissue-Binding Studies

Prediction of V_ss from In Vitro Tissue-Binding Studies

Overcoming resistance to γ-rays in squamous carcinoma cells by poly-drug elevation of ceramide levels

Application of a Generic Physiologically Based Pharmacokinetic Model to the Estimation of Xenobiotic Levels in Rat Plasma

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Influence of lipophilicity and lysosomal accumulation on tissue distribution kinetics of basic drugs: A physiologically based pharmacokinetic model

Cited by 52 publications

References 0 publications

Prediction of Vss from In Vitro Tissue-Binding Studies

Prediction of Vss from In Vitro Tissue-Binding Studies

Overcoming resistance to γ-rays in squamous carcinoma cells by poly-drug elevation of ceramide levels

Application of a Generic Physiologically Based Pharmacokinetic Model to the Estimation of Xenobiotic Levels in Rat Plasma

Contact Info

Product

Resources

About

Prediction of V_ss from In Vitro Tissue-Binding Studies

Prediction of V_ss from In Vitro Tissue-Binding Studies