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Combined Exposures to Hydrogen Cyanide and Carbon Monoxide in Army Operations: Initial Report 5 Pharmacokinetics and Mathematical Modeling for Assessing Toxicity of Mixtures of Chemicals Several approaches exist that could be used to evaluate the hazard presented by co-exposure to CO and HCN. It is commonly believed that the chemicals act independently if exposure to Chemical B does not change the severity of the toxic response to a given exposure to Chemical A. This is normally the case if the two chemicals cause their respective toxicities following entirely unrelated modes of action, the physiological, biochemical, or other series of processes that cumulatively cause toxic responses. When the modes of action share common elements, potential for non-independence in the combined dose response curve exists. Where this occurs, the non-independence can take a form of sub-additive, additive, or super-additive (also sometimes called synergistic effects). An additive response generally occurs when the dose response curves to the individual chemicals are parallel and can be added together to predict the combined response. A sub-additive response occurs when the combined response is somewhat less than expected through simple addition but greater than the response expected from either chemical alone. The super-additive response occurs when the combined response is greater than simple addition of the individual responses occurs. Mathematical approaches have been developed for these respective approaches; however, the choice of which approach to use is driven by the review of literature indicating which mode of interaction occurs. As reviewed earlier in this report, there are several studies that indicate that high doses of HCN and CO may exert additive toxic responses. The underlying mode of action for toxicity of CO and HCN share some common elements; therefore, additive responses are plausible. Few reports suggested super-additive, sub-additive, or independent responses. However, these toxicity studies conducted were generally at very high exposure levels and extrapolation to relatively low levels is required. It is uncertain whether the response to the mixture would be additive at the levels germane to the assessment of combined exposures at low levels. For pharmacokinetic as well as pharmacodynamic reasons, potential for super-additive responses for any mixture is more likely as dose increases; thus, when additive responses may exist at high dose, it is unlikely that super-additive responses would occur in the range of extrapolation. The possibility that independence or sub-additive responses may occur cannot be discounted. However, in light of the weak database of relevant studies, the committee agrees that assuming an additive response is the most reasonable approach. While other mathematical approaches may exist, by far the most common approach for assessing the combined hazard to chemical mixtures is the “hazard quotient” (HQ), which is also called the “hazard index” (HI) This approach is endorsed for use in applications such as this application by the U.S. Environmental Protection Agency (EPA 2000), American Conference of Governmental Industrial Hygienists (ACGIH 2006), the U.S. Occupational Safety and Health Administration (29 CFR 1910.1000 ), and the Agency for Toxic Substances and Disease Registry (ATSDR 2004). EPA recommends the HQ for mixtures where toxicity is dose additive, which is consistent with the current hazard evaluation. Specifically, EPA (2000) defines a HI for the assessment of combined exposure to components of a mixture as the sum of quotients of exposure to each component divided by the Acceptable Level for that chemical. The generic formula for the HI is:
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Combined Exposures to Hydrogen Cyanide and Carbon Monoxide in Army Operations: Initial Report where HI = hazard index, E = exposure level to component i, and AL = acceptable level to component i. If the HI exceeds 1.0, overexposure is indicated. ACGIH, OSHA and ATSDR’s formulations are mathematically identical. The assumption that underlies the validity of the use of this model is that the shapes of the dose response curves (or more precisely, the exposure-response curves) are similar. One unique aspect of the Army’s proposed implementation of the HQ is the use of an internal measure of dose (COHb) with an external measure of dose (HCN in air). However, as COHb is a measure of dose rather than response, the combination of an internal and external measure of dose appears to be consistent with EPA guidance. The Army proposes using the Coburn-Foster-Kane (CFK) equation to calculate carboxyhemoglobin (COHb) levels from CO air data that can be measured in real-time. The real time monitoring of CO provides an exceptional ability to observe the pulsitile spikes (seconds) in the ambient air in the armored vehicle after the cannon is fired. The changes in COHb are much slower, on the order of minutes to a few hours. Factors controlling the rate of change of CO binding to hemoglobin are CO concentration in the air, breathing rate (workload), and the diffusion rate of CO into lung blood. The CFK model has been validated, but as with any model, is not always accurate and typically has not been tested in environments such as in armored vehicles where the air concentration changes dynamically. Due to the fact that COHb changes over a slower time course than air concentrations, use of a running fifteen minute average for air CO would likely be more appropriate although has not been thoroughly analyzed. The committee recommends that the Army assess the validity of the CFK in the context of armored vehicles both using instantaneous measured data and various running averages. This should take into account the typical firing intervals, including the rapid firing sequences and the sequences of infrequent firing that are representative of actual conditions. After firing a round, the gases are at a peak and decline in concentration due to ventilation. When rounds are fired more frequently, exposures increase in parallel. Thus, the exposure is rarely if at all at steady state, and almost always subject to short peaks and declining levels. The ability of the exposure assessment strategy to detect a potential overexposure will therefore depend in large part on the appropriate selection of an averaging interval. The use of running averages for HCN exposure assessment copes with this difficulty by ensuring that a short peak exposure is not missed, i.e., selection of start and stop times for averaging are essentially moot since every configuration is calculated. The use of the internal measure of dose, via the CFK equation’s calculation of % COHb likewise copes with the highly intermittent exposure by calculating an integrated measure of dose through the biomarker, wherein the biological process serves as the means of integration. An alternate to mathematical models such as the HQ is the use of physiologically based pharmacokinetic (PBPK) modeling. PBPK has been used to understand interactions between individual chemicals found in a chemical mixture once the chemical mixture has entered the body of laboratory animals or humans. Inhaled solvents have received the greatest attention with PBPK modeling. Solvent toxicity of a chemical mixture such as central nervous system effects may be governed by the brain: blood partition coefficient for each chemical, while other toxicities are mediated by the formation of reactive metabolites. The use of PBPK models to predict the metabolic clearance of solvent mixtures from the body has received the greatest attention (Haddad et al. 2001) by quantitatively describing the competitive metabolism of each solvent by the same enzymatic system (e.g., P450 isoforms). The impact of solvent mixtures on individual solvent pharmacokinetics is governed by the exposure level of each solvent in the solvent mixture, chemical specific properties of each solvent such as its affinity for the metabolizing enzyme and thermodynamic properties (blood: air and tissue: blood partition coefficients). While a PBPK model has addressed CO as a byproduct of solvent metabolism, currently there are no PBPK models for CO and HCN mixtures. In the case of CO and HCN, a computational research effort designed to understand possible mechanistic interactions (hypothesis generation) between CO and HCN is warranted.
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Combined Exposures to Hydrogen Cyanide and Carbon Monoxide in Army Operations: Initial Report The Army reports that exposures to HCN appear to be low most of the time such that HCN may not contribute substantially to the HQ calculation for HCN and CO. By implication, if this is true, then HCN exposures may not warrant assessment. In practice if a chemical is 5% or less of occupational exposure limit as a maximum exposure, the chemical may be considered as minor contributor to the toxicity of a mixture of chemicals. In the current assessment, it is not clear that HCN exposure is low enough to warrant the elimination of monitoring activities, and as long as HCN is monitored, it should be included in the HQ calculation.