Only
a small fraction of chemicals possesses adequate in
vivo toxicokinetic data for assessing potential hazards.
The aim of the present study was to model the plasma and hepatic pharmacokinetics
of more than 50 disparate types of chemicals and drugs after virtual
oral administrations in rats. The models were based on reported pharmacokinetics
determined after oral administration to rats. An inverse relationship
was observed between no-observed-effect levels after oral administration
and chemical absorbance rates evaluated for cell permeability (r = −0.98, p < 0.001, n = 17). For a varied selection of more than 30 chemicals,
the plasma concentration curves and the maximum concentrations obtained
using a simple one-compartment model (recently recommended as a high-throughput
toxicokinetic model) and a simple physiologically based pharmacokinetic
(PBPK) model (consisting of chemical receptor, metabolizing, and central
compartments) were highly consistent. The hepatic and plasma concentrations
and the hepatic and plasma areas under the concentration–time
curves of more than 50 chemicals were roughly correlated; however,
differences were evident between the PBPK-modeled values in livers and
empirically obtained values in plasma. Of the compounds selected
for analysis, only seven had the lowest observed effect level (LOEL)
values for hepatoxicity listed in the Hazard Evaluation Support System
Integrated Platform in Japan. For these seven compounds, the LOEL
values and the areas under the hepatic concentration–time curves
estimated using PBPK modeling were inversely correlated (r = −0.78, p < 0.05, n = 7). This study provides important information to help simulate
the high hepatic levels of potent hepatotoxic compounds. Using suitable
PBPK parameters, the present models could estimate the plasma/hepatic
concentrations of chemicals and drugs after oral doses using both
PBPK forward and reverse dosimetry, thereby indicating the potential
value of this modeling approach in predicting hepatic toxicity as
a part of risk assessments of chemicals absorbed in the human body.
Recently
developed high-throughput in vitro assays in combination
with computational models could provide alternatives to animal testing.
The purpose of the present study was to model the plasma, hepatic,
and renal pharmacokinetics of approximately 150 structurally varied
types of drugs, food components, and industrial chemicals after virtual
external oral dosing in rats and to determine the relationship between
the simulated internal concentrations in tissue/plasma and their lowest-observed-effect
levels. The model parameters were based on rat plasma data from the
literature and empirically determined pharmacokinetics measured after
oral administrations to rats carried out to evaluate hepatotoxic or
nephrotic potentials. To ensure that the analyzed substances exhibited
a broad diversity of chemical structures, their structure-based location
in the chemical space underwent projection onto a two-dimensional
plane, as reported previously, using generative topographic mapping.
A high-throughput in silico one-compartment model and a physiologically
based pharmacokinetic (PBPK) model consisting of chemical receptor
(gut), metabolizing (liver), central (main), and excreting (kidney)
compartments were developed in parallel. For 159 disparate chemicals,
the maximum plasma concentrations and the areas under the concentration–time
curves obtained by one-compartment models and modified simple PBPK
models were closely correlated. However, there were differences between
the PBPK modeled and empirically obtained hepatic/renal concentrations
and plasma maximal concentrations/areas under the concentration–time
curves of the 159 chemicals. For a few compounds, the lowest-observed-effect
levels were available for hepatotoxicity and nephrotoxicity in the
Hazard Evaluation Support System Integrated Platform in Japan. The
areas under the renal or hepatic concentration–time curves
estimated using PBPK modeling were inversely associated with these
lowest-observed-effect levels. Using PBPK forward dosimetry could
provide the plasma/tissue concentrations of drugs and chemicals after
oral dosing, thereby facilitating estimates of nephrotoxic or hepatotoxic
potential as a part of the risk assessment.
To facilitate development of the androgen receptor inhibitor, enzalutamide, we developed and validated methods for simultaneous determination of enzalutamide, its carboxylic acid metabolite (M1), and N-desmethyl enzalutamide (M2) in plasma from mice, rats, and dogs, and brain from mice. Following addition of stable isotope-labeled internal standards, plasma and brain samples (0.05 and 0.3 mL, respectively) were mixed with 0.1% formic acid and extracted with tert-butyl methyl ether, and then injected into a liquid chromatography-tandem mass spectrometry system. The eluent was monitored in positive electrospray ionization mode. To bracket the concentrations of the drug and metabolites in study samples, calibration curves were constructed from 20 to 50000 ng/mL for plasma and 10 to 25000 ng/g for brain. Validation data demonstrated that these methods were selective, reproducible, and accurate. Using these methods, brain-to-plasma concentration ratios in mice were determined to be 0.72 for enzalutamide, 0.048 for M1, and 1.4 for M2.
Dynamic recrystallization in Ti-1100 was investigated. Ti-1100 is one of near α titanium alloys and contains Si for improving high temperature mechanical properties. Ti-1100 exhibits martensitic transformation by quenching into iced brine after solid solution treatment. Hereafter specimens subjected to quenching into iced brine and to cooling in air after solid solution treatment are called IBQ specimen and AC specimen, respectively. After tensile test at high temperature, IBQ specimen exhibits morphological change from lath structure to equiaxed structure, but AC specimen does not. It is indicated that dynamic recrystallization occurs during the tensile test of IBQ specimen. Effect of silicide on the dynamic recrystallization was investigated using two specimens: one included more silicide precipitates and the other less. The former specimen shows smaller recrystallized grains than the latter. It is indicated that the specimen including more silicides exhibits smaller recrystallized grains.
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