Revised assessment of cancer risk to dichloromethane II. Application of probabilistic methods to cancer risk determinations

Update of a cohort mortality study of workers exposed to methylene chloride employed at a plant producing cellulose triacetate film base

“…The unit risk value derived by David et al (2006) corresponds to an approximate 1 in 10,000 risk of lung and liver tumours for lifetime methylene chloride exposure of 30 ppm and suggests that it is unlikely that excesses of lung and liver tumours would be observed in the epidemiological studies, especially those of the lower exposed film workers. The Brantham film workers cohort, like the other four groups, experienced reduced overall mortality, reduced mortality from cancer and lower mortality than expected for lung cancer.…”

“…Indeed, one section of the population who are homozygotic null (non-conjugators) for the GSTT1 polymorphism (typically 15 to 25%) are predicted to be at no increased cancer risk from exposure to methylene chloride because they show no GSTT1-dependent metabolism and lack the capacity to bioactivate methylene chloride. David et al (2006) describe how risk assessments using PBPK modelling have become increasingly more refined since the EPA unit risk value of 4.7 9 10 -7 per 1 lg/m 3 was derived (EPA 1991) and have culminated in a much lower estimate of risk. David et al (2006) calculated a median unit risk value of 9.33 9 10 -10 per 1 lg/m 3 for combined liver and lung tumours using their updated PBPK model incorporating improved metabolic and physiological parameters, and the distribution of genetic polymorphisms for metabolism, approximately a factor of 500 lower than the EPA unit risk value.…”

A multi-route model of nicotine–cotinine pharmacokinetics, pharmacodynamics and brain nicotinic acetylcholine receptor binding in humans

“…distribution in the model space, correlations between the parameters and their distribution across i.v and oral routes of exposure. Nonetheless, as David et al caution (David et al, 2006), posterior parameter distributions derived by MCMC analysis should not replace parameter estimates made directly or by simulation from data sets representing larger populations without careful justification. The effective volume of distribution based on tissue volumes and partition coefficients was somewhat less than what others have reported from classical compartmental analyses.…”

Genetic Susceptibility and the Setting of Occupational Health Standards

“…A good example of the utility of genotype data in risk assessments is dichloromethane (DCM), a substance widely used in industry for degreasing metal. Lung and liver tumors have been observed in mice exposed to DCM by inhalation (13). The role of polymorphisms in genes encoding for DCM-metabolizing enzymes, such as CYP2E1 and GSTTI, was recognized as integral to the development of tumors in experimental animals (45,46).…”

“…The role of polymorphisms in genes encoding for DCM-metabolizing enzymes, such as CYP2E1 and GSTTI, was recognized as integral to the development of tumors in experimental animals (45,46). David et al (13) provided the most recent QRA of DCM inhalation exposure for the general population using a state-of-the-science probabilistic methodology, improved metabolic parameters for CYP2EI and GSTTI activators, and improved physiological parameters. The researchers found that the unit risk was reduced by a factor of more than 100 from previously published risk assessments.…”