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The developmental effects of NMP are well studied in Sprague-Dawley rats following oral, inhalation, and dermal routes of exposure. Short-term and chronic occupational exposure limit (OEL) values were derived using an updated physiologically based pharmacokinetic (PBPK) model for NMP, along with benchmark dose modeling. Two suitable developmental endpoints were evaluated for human health risk assessment: (1) for acute exposures, the increased incidence of skeletal malformations, an effect noted only at oral doses that were toxic to the dam and fetus; and (2) for repeated exposures to NMP, changes in fetal/pup body weight. Where possible, data from multiple studies were pooled to increase the predictive power of the dose-response data sets. For the purposes of internal dose estimation, the window of susceptibility was estimated for each endpoint, and was used in the dose-response modeling. A point of departure value of 390 mg/L (in terms of peak NMP in blood) was calculated for skeletal malformations based on pooled data from oral and inhalation studies. Acceptable dose-response model fits were not obtained using the pooled data for fetal/pup body weight changes. These data sets were also assessed individually, from which the geometric mean value obtained from the inhalation studies (470 mg*hr/L), was used to derive the chronic OEL. A PBPK model for NMP in humans was used to calculate human equivalent concentrations corresponding to the internal dose point of departure values. Application of a net uncertainty factor of 20-21, which incorporates data-derived extrapolation factors, to the point of departure values yields short-term and chronic occupational exposure limit values of 86 and 24 ppm, respectively., (Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.)

The concept that the product of the concentration (C) of a substance and the length of time (t) it is administered produces a fixed level of effect for a given endpoint has been ascribed to Fritz Haber, who was a German scientist in the early 1900s. He contended that the acute lethality of war gases could be assessed by the amount of the gas in a cubic meter of air (i.e. the concentration) multiplied by the time in min that the animal had to breathe the air before death ensued (i.e. C x t=k). While Haber recognized that C x t=k was applicable only under certain conditions, many toxicologists have used his rule to analyze experimental data whether or not their chemicals, biological endpoints, and exposure scenarios were suitable candidates for the rule. The fact that the relationship between C and t is linear on a log-log scale and could easily be solved by hand, led to early acceptance among toxicologists, particularly in the field of entomology. In 1940, a statistician named Bliss provided an elegant treatment on the relationships among exposure time, concentration, and the toxicity of insecticides. He proposed solutions for when the log-log plot of C and t was composed of two or more rectilinear segments, for when the log-log plot was curvilinear, and for when the slope of the dosage-mortality curve was a function of C. Despite the fact that Haber's rule can underestimate or overestimate effects (and consequently risks), it has been used in various settings by regulatory bodies. Examples are presented from the literature of data sets that follow Haber's rule as well as those that do not. Haber's rule is put into perspective by showing that it is simply a special case in a family of power law curves relating concentration and duration of exposure to a fixed level of response for a given endpoint. Also shown is how this power law family can be used to examine the three-dimensional surface relating C, t, and varying levels of response. The time has come to move beyond the limited view of C and t relationships inferred by Haber's rule to the use of the broader family of curves of which this rule is a special case.

In vitro and in vivo butadiene (BD) metabolism data from laboratory animals were integrated into a rodent physiologically based pharmacokinetic (PBPK) model with flow- and diffusion-limited compartments. The resulting model describes experimental data from multiple sources under scenarios such as closed chamber inhalation and nose-only flow-through inhalation exposures. Incorporation of diurnal glutathione (GSH) variation allows accurate simulation of GSH changes observed in air control nose-only exposures and BD exposures. An isolated tissue model based on rate parameters determined in vitro predicts the decrease in epoxide concentrations in intact animals during the time lag between exsanguination and tissue removal for tissues capable of epoxide biotransformation, providing a better indication of in vivo dosimetry. Further refinements of the model are required relative to model predictions of an important BD metabolite, diepoxybutane.

Benzene, an important industrial solvent, is also present in unleaded gasoline and cigarette smoke. The hematotoxic effects of benzene in humans are well documented and include aplastic anemia and pancytopenia, and acute myelogenous leukemia. A combination of metabolites (hydroquinone and phenol for example) is apparently necessary to duplicate the hematotoxic effect of benzene, perhaps due in part to the synergistic effect of phenol on myeloperoxidase-mediated oxidation of hydroquinone to the reactive metabolite benzoquinone. Since benzene and its hydroxylated metabolites (phenol, hydroquinone and catechol) are substrates for the same cytochrome P450 enzymes, competitive interactions among the metabolites are possible. In vivo data on metabolite formation by mice exposed to various benzene concentrations are consistent with competitive inhibition of phenol oxidation by benzene. In vitro studies of the metabolic oxidation of benzene, phenol and hydroquinone are consistent with the mechanism of competitive interaction among the metabolites. The dosimetry of benzene and its metabolites in the target tissue, bone marrow, depends on the balance of activation processes such as enzymatic oxidation and deactivation processes such as conjugation and excretion. Phenol, the primary benzene metabolite, can undergo both oxidation and conjugation. Thus, the potential exists for competition among various enzymes for phenol. However, zonal localization of Phase I and Phase II enzymes in various regions of the liver acinus regulates this competition. Biologically-based dosimetry models that incorporate the important determinants of benzene flux, including interactions with other chemicals, will enable prediction of target tissue doses of benzene and metabolites at low exposure concentrations relevant for humans.