Brad Reisfeld

Cytochromes P450: a structure-based summary of biotransformations using representative substrates.

Cytochromes P450 (CYPs) are a superfamily of enzymes that metabolize the majority of xenobiotics in humans. This review presents a structure-based outline of CYP-catalyzed biotransformations of selected substrates, representing diverse structural classes of chemicals, ranging from drugs to toxicants. Data are presented in a tabular format for easy reference, with visual representations of all substrates and sites-of-attack. The major metabolites, isozymes responsible, chemical classification, and other information related to the biotransformation are provided. Pharmacophores proposed for the major CYP isozymes are discussed. This visual combination of substrates and biotransformation sites can serve as a useful reference for researchers.

Computational toxicology of chloroform: reverse dosimetry using Bayesian inference, Markov chain Monte Carlo simulation, and human biomonitoring data.

BACKGROUND One problem of interpreting population-based biomonitoring data is the reconstruction of corresponding external exposure in cases where no such data are available. OBJECTIVES We demonstrate the use of a computational framework that integrates physiologically based pharmacokinetic (PBPK) modeling, Bayesian inference, and Markov chain Monte Carlo simulation to obtain a population estimate of environmental chloroform source concentrations consistent with human biomonitoring data. The biomonitoring data consist of chloroform blood concentrations measured as part of the Third National Health and Nutrition Examination Survey (NHANES III), and for which no corresponding exposure data were collected. METHODS We used a combined PBPK and shower exposure model to consider several routes and sources of exposure: ingestion of tap water, inhalation of ambient household air, and inhalation and dermal absorption while showering. We determined posterior distributions for chloroform concentration in tap water and ambient household air using U.S. Environmental Protection Agency Total Exposure Assessment Methodology (TEAM) data as prior distributions for the Bayesian analysis. RESULTS Posterior distributions for exposure indicate that 95% of the population represented by the NHANES III data had likely chloroform exposures < or = 67 microg/L [corrected] in tap water and < or = 0.02 microg/L in ambient household air. CONCLUSIONS Our results demonstrate the application of computer simulation to aid in the interpretation of human biomonitoring data in the context of the exposure-health evaluation-risk assessment continuum. These results should be considered as a demonstration of the method and can be improved with the addition of more detailed data.

Non-isothermal flow of a liquid film on a horizontal cylinder

We consider the flow of a viscous liquid film on the surface of a cylinder that is heated or cooled. Lubrication theory is used to study a thin film under the influence of gravity, capillary, thermocapillary, and intermolecular forces. We derive evolution equations for the interface shapes as a function of the azimuthal angle about the cylinder that govern the behaviour of the film subject to the above coupled forces. We use both analytical and numerical techniques to elucidate the dynamics and steady states of the thin layer over a wide range of thermal conditions and material properties. Finally, we extend our derivation to the case of three-dimensional dynamics and explore the stability of the film to small axial disturbances.

Nonlinear stability of a heated thin liquid film with variable viscosity

The stability of a heated liquid film subjected to surface tension and van der Waals forces is explored in the case where the fluid viscosity is temperature dependent. The limits of very large and very small Biot numbers are examined, and in these cases it is found that the evolution equation can be rescaled to return the model equation developed by Williams and Davis [J. Colloid Interface Sci. 90, 220 (1982)] for an isothermal film. The effect of variable viscosity is deduced and is found to reduce the rupture time of the film relative to the constant‐viscosity result.

Additive Synergism between Asbestos and Smoking in Lung Cancer Risk: A Systematic Review and Meta-Analysis.

Smoking and asbestos exposure are important risks for lung cancer. Several epidemiological studies have linked asbestos exposure and smoking to lung cancer. To reconcile and unify these results, we conducted a systematic review and meta-analysis to provide a quantitative estimate of the increased risk of lung cancer associated with asbestos exposure and cigarette smoking and to classify their interaction. Five electronic databases were searched from inception to May, 2015 for observational studies on lung cancer. All case-control (N = 10) and cohort (N = 7) studies were included in the analysis. We calculated pooled odds ratios (ORs), relative risks (RRs) and 95% confidence intervals (CIs) using a random-effects model for the association of asbestos exposure and smoking with lung cancer. Lung cancer patients who were not exposed to asbestos and non-smoking (A-S-) were compared with; (i) asbestos-exposed and non-smoking (A+S-), (ii) non-exposure to asbestos and smoking (A-S+), and (iii) asbestos-exposed and smoking (A+S+). Our meta-analysis showed a significant difference in risk of developing lung cancer among asbestos exposed and/or smoking workers compared to controls (A-S-), odds ratios for the disease (95% CI) were (i) 1.70 (A+S-, 1.31–2.21), (ii) 5.65; (A-S+, 3.38–9.42), (iii) 8.70 (A+S+, 5.8–13.10). The additive interaction index of synergy was 1.44 (95% CI = 1.26–1.77) and the multiplicative index = 0.91 (95% CI = 0.63–1.30). Corresponding values for cohort studies were 1.11 (95% CI = 1.00–1.28) and 0.51 (95% CI = 0.31–0.85). Our results point to an additive synergism for lung cancer with co-exposure of asbestos and cigarette smoking. Assessments of industrial health risks should take smoking and other airborne health risks when setting occupational asbestos exposure limits.

A Physiologically Based Pharmacokinetic Model of Rifampin in Mice

ABSTRACT One problem associated with regimen-based development of antituberculosis (anti-TB) drugs is the difficulty of a systematic and thorough in vivo evaluation of the large number of possible regimens that arise from consideration of multiple drugs tested together. A mathematical model capable of simulating the pharmacokinetics and pharmacodynamics of experimental combination chemotherapy of TB offers a way to mitigate this problem by extending the use of available data to investigate regimens that are not initially tested. In order to increase the available mathematical tools needed to support such a model for preclinical anti-TB drug development, we constructed a preliminary whole-body physiologically based pharmacokinetic (PBPK) model of rifampin in mice, using data from the literature. Interindividual variability was approximated using Monte Carlo (MC) simulation with assigned probability distributions for the model parameters. An MC sensitivity analysis was also performed to determine correlations between model parameters and plasma concentration to inform future model development. Model predictions for rifampin concentrations in plasma, liver, kidneys, and lungs, following oral administration, were generally in agreement with published experimental data from multiple studies. Sensitive model parameters included those descriptive of oral absorption, total clearance, and partitioning of rifampin between blood and muscle. This PBPK model can serve as a starting point for the integration of rifampin pharmacokinetics in mice into a larger mathematical framework, including the immune response to Mycobacterium tuberculosis infection, and pharmacokinetic models for other anti-TB drugs.

Epigenetic Alterations May Regulate Temporary Reversal of CD4+ T Cell Activation Caused by Trichloroethylene Exposure

Previous studies have shown that short-term (4 weeks) or chronic (32 weeks) exposure to trichloroethylene (TCE) in drinking water of female MRL+/+ mice generated CD4(+) T cells that secreted increased levels of interferon (IFN)-γ and expressed an activated (CD44(hi)CD62L(lo)) phenotype. In contrast, the current study of subchronic TCE exposure showed that midway in the disease process both of these parameters of CD4(+) T cell activation were reversed. This phase of the disease process may represent an attempt by the body to counteract the inflammatory effects of TCE. The decrease in CD4(+) T cell production of IFN-γ following subchronic TCE exposure could not be attributed to skewing toward a Th2 or Th17 phenotype or to an increase in Treg cells. Instead, the suppression corresponded to alterations in markers used to assess DNA methylation, namely increased expression of retrotransposons Iap (intracisternal A particle) and Muerv (murine endogenous retrovirus). Also observed was an increase in the expression of Dnmt1 (DNA methyltransferase-1) and decreased expression of several genes known to be downregulated by DNA methylation, namely Ifng, Il2, and Cdkn1a. CD4(+) T cells from a second study in which MRL+/+ mice were treated for 17 weeks with TCE showed a similar increase in Iap and decrease in Cdkn1a. In addition, DNA collected from the CD4(+) T cells in the second study showed TCE-decreased global DNA methylation. Thus, these results described the biphasic nature of TCE-induced alterations in CD4(+) T cell function and suggested that these changes represented potentially reversible alterations in epigenetic processes.

Association of HLA-B*5701 Genotypes and Abacavir-Induced Hypersensitivity Reaction: A Systematic Review and Meta-Analysis

OBJECTIVES This study aimed to systematically review and quantitatively synthesize the association between HLA-B*5701 and abacavir-induced hypersensitivity reaction (ABC-HSR). METHODS We searched for studies that investigated the association between HLA-B genotype and ABC-HSR and provided information about the frequency of carriers of HLA-B genotypes among cases and controls. We then performed a meta-analysis with a random-effects model to pool the data and to investigate the sources of heterogeneity. RESULTS From 1,026 articles identified, ten studies were included. Five using clinical manifestation as their diagnostic criteria, 409 and 1,883 subjects were included as cases and controls. Overall OR was 23.6 (95% CI = 15.4 - 36.3). Whereas, the another five studies using confirmed immunologic test as their diagnostic criteria, 110 and 1,968 subjects were included as cases and controls, respectively. The association of ABC-HSR was strong in this populations with HLA-B*5701. Overall OR was 1,056.2 (95% CI = 345.0 - 3,233.3). CONCLUSIONS Using meta-analysis technique, the association between HLA-B*5701 and ABC-HSR is strong in the studies using immunologic confirmation to identify ABC-HSR. These results support the US FDA recommendations for screening HLA-B*5701 allele before initiating abacavir therapy.

A physiologically based pharmacokinetic model for capreomycin.

ABSTRACT The emergence of multidrug-resistant tuberculosis (MDR-TB) has led to a renewed interest in the use of second-line antibiotic agents. Unfortunately, there are currently dearths of information, data, and computational models that can be used to help design rational regimens for administration of these drugs. To help fill this knowledge gap, an exploratory physiologically based pharmacokinetic (PBPK) model, supported by targeted experimental data, was developed to predict the absorption, distribution, metabolism, and excretion (ADME) of the second-line agent capreomycin, a cyclic peptide antibiotic often grouped with the aminoglycoside antibiotics. To account for interindividual variability, Bayesian inference and Monte Carlo methods were used for model calibration, validation, and testing. Along with the predictive PBPK model, the first for an antituberculosis agent, this study provides estimates of various key pharmacokinetic parameter distributions and supports a hypothesized mechanism for capreomycin transport into the kidney.

Physiologically based modeling of the pharmacokinetics of acetaminophen and its major metabolites in humans using a Bayesian population approach

The principal aim of this study was to develop, validate, and demonstrate a physiologically based pharmacokinetic (PBPK) model to predict and characterize the absorption, distribution, metabolism, and excretion of acetaminophen (APAP) in humans. A PBPK model was created that included pharmacologically and toxicologically relevant tissue compartments and incorporated mechanistic descriptions of the absorption and metabolism of APAP, such as gastric emptying time, cofactor kinetics, and transporter-mediated movement of conjugated metabolites in the liver. Through the use of a hierarchical Bayesian framework, unknown model parameters were estimated using a large training set of data from human pharmacokinetic studies, resulting in parameter distributions that account for data uncertainty and inter-study variability. Predictions from the model showed good agreement to a diverse test set of data across several measures, including plasma concentrations over time, renal clearance, APAP absorption, and pharmacokinetic and exposure metrics. The utility of the model was then demonstrated through predictions of cofactor depletion, dose response of several pharmacokinetic endpoints, and the relationship between APAP biomarker levels in the plasma and those in the liver. The model addressed several limitations in previous PBPK models for APAP, and it is anticipated that it will be useful in predicting the pharmacokinetics of APAP in a number of contexts, such as extrapolating across doses, estimating internal concentrations, quantifying population variability, assessing possible impacts of drug coadministration, and, when coupled with a suitable pharmacodynamic model, predicting toxicity.