IL-10: a tacrolimus-specific cytotoxic mediator in ongoing allograft rejection.
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Administration, Oral↗
Biomedical subjects
K Krishnan
Publications and source records attributed to K Krishnan.
A spreadsheet program for modeling quantitative structure-pharmacokinetic relationships for inhaled volatile organics in humans.
The extent and profile of target tissue exposure to toxicants depend upon the pharmacokinetic processes, namely, absorption, distribution, metabolism and excretion. The present study developed a spreadsheet program to simulate the pharmacokinetics of inhaled volatile organic chemicals (VOCs) in humans based on information from molecular structure. The approach involved the construction of a human physiologically-based pharmacokinetic (PBPK) model, and the estimation of its parameters based on quantitative structure-property relationships (QSPRs) in an Excel spreadsheet. The compartments of the PBPK model consisted of liver, adipose tissue, poorly perfused tissues and richly perfused tissues connected by circulating blood. The parameters required were: human physiological parameters such as cardiac output, breathing rate, tissue volumes and tissue blood flow rates (obtained from the biomedical literature), tissue/air partition coefficients (obtained using QSPRs developed with rat data), blood/air partition coefficients (Pb) and hepatic clearance (CL). Using literature data on human Pb and CL for several VOCs (alkanes, alkenes, haloalkanes and aromatic hydrocarbons), multi-linear additive QSPR models were developed. The numerical contributions to human Pb and CL were obtained for eleven structural fragments (CH3, CH2, CH, C, C [double bond] C, H, Cl, Br, F, benzene ring, and H in the benzene ring structure). Using these data as input, the PBPK model written in an Excel spreadsheet simulated the inhalation pharmacokinetics of ethylbenzene (33 ppm, 7 h) and dichloromethane (100 ppm, 6 h) in humans exposed to these chemicals. The QSPRs developed in this study should be useful for predicting the inhalation pharmacokinetics of VOCs in humans, prior to testing and experimentation.
Animals↗
A physiologically based description of ethylene oxide dosimetry in the rat.
A physiologically based pharmacokinetic (PB-PK) model providing a quantitative description of ethylene oxide (ETO) dosimetry in the rat was developed by integrating information on physiology, tissue solubility of ETO, and rate constants for ETO metabolism and binding. The PB-PK model consisted of nine compartments; liver, lung, testis, brain, fat, venous blood, arterial blood, richly perfused and poorly perfused tissues. The tissue: air partition coefficients of ETO, determined by vial equilibration, were similar among the various tissues (range 44-83). The rate constants for glutathione (GSH) conjugation, hydrolysis, and hemoglobin (Hb)- and DNA-binding were estimated from published data and by conducting in vivo inhalation exposure studies. The model adequately predicted the concentrations of Hb and DNA adducts, hepatic and extrahepatic GSH, and urinary N-acetyl-S-(2-hydroxyethyl)-cysteine following inhalation exposures of 1.2 to 1,200 ppm and intravenous administration of 1 to 100 mg/kg of ETO in male Fischer-344 and Sprague-Dawley rats. There was no evidence of nonlinearity in the overall elimination of ETO in the dose range examined. However, nonlinearities in the components of this first order elimination process (namely GSH conjugation, hydrolysis, exhalation) were found to occur at high exposure concentrations. Characterization of the individual metabolic pathways that affect the tissue dosimetry of ETO is important for interspecies extrapolation and risk assessment for this chemical.
Animals↗
A simple index for representing the discrepancy between simulations of physiological pharmacokinetic models and experimental data.
The objective of this study was to develop an index that would provide a quantitative measure of the degree of discrepancy between simulations of physiologically based pharmacokinetic (PBPK) models and experimental data. The approach we developed involves the calculation of the root mean square of the error (representing the difference between the individual simulated and experimental values for each sampling point in a time course curve), and dividing it by the root mean square of the experimental values. The resulting numerical values of discrepancy measures for several data sets (each corresponding to an end point) obtained in a single experimental study are then combined on the basis of a weighting proportional to the number of data points contained in each data set. Such consolidated discrepancy indices obtained from several experiments (e.g., exposure scenarios, doses, routes, species) are averaged to get an overall discrepancy index, referred to as the PBPK index. This empirical index reflects the overall, weighted average percent difference between the a priori PBPK model simulations and experimental data. The proposed methodology is illustrated using previously published experimental and simulated data on dichloromethane pharmacokinetics in humans. The application of this kind of a "quantitative" method should help remove the ambiguity in communicating the degree of concordance or discrepancy between PBPK model simulations and experimental data.
Animals↗
An approach for incorporating tissue composition data into physiologically based pharmacokinetic models.
The objective of this study was to develop an approach for incorporating tissue composition data into physiologically based pharmacokinetic (PBPK) models in order to facilitate "built-in" calculation of tissue: air partition coefficients (PCs) of volatile organic chemicals. The approach involved characterizing tissue compartments within PBPK models as a mixture of neutral lipids, phospholipids, and water (instead of using the conventional description of them as "empty" boxes). This approach enabled automated calculation of the tissue solubility of chemicals from n-octanol and water solubility data, since these data approximate those of solubility in tissue lipids and water. Tissue solubility was divided by the saturable vapor concentration at 37 degrees C to estimate the tissue: air PCs within PBPK models, according to the method of Poulin and Krishnan (1995c). The highest and lowest lipid and water levels for human muscle, liver, and adipose tissues were obtained from the literature and incorporated within the tissue composition-based PBPK model to calculate the tissue: air PCs of dichloromethane (DCM) and simulate the pharmacokinetics of DCM in humans. The PC values predicted for human tissues were comparable to those estimated using rat tissues in cases where the relative levels of lipids and water were comparable in both species. These results suggest that the default assumption of using rat tissue: air PCs in human PBPK models may be acceptable for certain tissues (liver, adipose tissues), but questionable for others (e.g., muscle). The PBPK modeling exercise indicated that the interindividual differences in tissue dose arising from variations of tissue: air PCs may not be reflected sufficiently by venous blood concentrations. Overall, the present approach of incorporating tissue composition data into PBPK models would not only enhance the biological basis of these models but also provide a means of evaluating the impact of interindividual and interspecies differences in tissue composition on the tissue dose surrogates used in PBPK-based risk assessments.
Adipose Tissue↗
Patterns of liver injury induced by mixtures of halogenated hydrocarbons: a predictable event?
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Animals↗
Assessment of occupational health risk during unusual workshifts: review of the needs and solutions for modifying environmental and biological limit values for volatile organic solvents.
Aspects of occupational health risk assessment for unusual workshifts are discussed in relation to the question of: 1) using a suitable model for adjusting occupational exposure limits, and 2) assessing the influence of altered work schedules on biological exposure limits. The relative importance of two separate approaches, i.e., mathematical and pharmacokinetic, for the adjustment of exposure limits is discussed. Emphasis is placed on the usefulness of a physiologically based pharmacokinetic model for the exposure limits adjustments during prolonged work hours. The influence of prolonged work schedules on biological exposure limits is discussed and it is concluded that the latter do not have to be adjusted for unusual workshifts. Research needs arising as a result of unusual workshifts and pertaining to the practice of industrial hygiene and biological monitoring are suggested.
Humans↗