Assessing chemical mixture risk and incorporating science findings into regulatory practices

Thanks to proposition 65, Californians are warned that a, “product contains chemicals known to the State of California to cause cancer and birth defects of other reproductive harm”. While being informed of products that contain harmful chemicals is important, the omnipresence of these signs found everywhere from Starbucks to parking garages seems to negate the impact of these messages (yes, it appears nothing can get between people and their morning coffee!).

 

Of course most people do want to avoid harmful products, but this goal becomes nearly impossible when everything seems to cause cancer, birth defects and reproductive harm. Clearly, we need a new way to address the risk assessment of chemicals and the regulatory policies dictating exposure to such products. 

 

Numerous legislative measures require the evaluation of health risks posed by chemical products. Traditional risk assessment focused on understanding the health impact of chemicals in isolation. Recently, however, the focus has moved to understanding chemical mixtures; rarely are chemicals encountered in isolation and chemicals can interact in a variety of ways that makes health risk estimates based off of individual chemicals inaccurate. Despite knowledge that mixture effects of the toxicity of chemicals exist, calculating the risks associated with mixtures faces numerous challenges such as the overwhelming number of combinations.

 

There are currently over 80,000 chemicals in mass production and about 700 new chemicals added annually. Clearly, an efficient means to evaluate the safety of these chemicals and their interactions is important. While mixture-dose response methods have been important in addressing the risk of chemical mixtures, they require knowledge of the components and potency of a chemical mixture; thus, these methods have been severely limited by data requirements and the ability to extrapolate responses.

 

Dr. James Englehardt at the University of Miami proposes a new algorithm to increase efficiency in chemical risk assessment. This algorithm allows for mixture dose-response assessment with greatly reduced data requirements. Furthermore, it allows for extrapolation of responses outside of current data sets. These properties can allow for better predictions of where risk can be anticipated. This could potentially help prevent harm in situations where we do not have enough knowledge to assume harm may occur.

 

So, does increased efficiency in assessing risks of chemicals and chemical mixtures equate to quicker and better policies regarding exposure?

 

Unfortunately, the translation of scientific findings regarding the health effects of chemicals into appropriate regulatory practices has been notoriously slow in the US. Chemical companies have managed to postpone the release of health assessments of numerous compounds such as formaldehyde, styrene and dioxin for years. By delaying the release of scientific findings on the adverse health effects these compounds may have, chemical corporations have managed to put exposure regulations for these compounds on hold. This means not only does health risk assessment need to be efficient, there should also be an efficient way to create regulatory processes based on scientific findings.

 

While this model appears to increase the efficiency of evaluating a dose response effect of chemicals and chemical mixtures, it does not address how these findings will be incorporated into regulatory processes. Perhaps with this more predictive model, however, we can move from a more retroactive approach to chemical safety to a more precautionary approach. This means that regulation of exposure should be limited until it is deemed safe, rather than limited only after it is found unsafe.