Sunday, February 23, 2014

NOELs & LOELs which form the Basis of OELs

In a previous blog I made the statement that, from my perspective, the basic approach of the ACGIH TLV Committee breaks down to taking a NOEL (No Observed Effect Level) or LOEL (Low Observed Effect Level) from a toxicological study in animals and dividing it by a safety factor.    The resulting Occupational Exposure Limit (OEL) is designed to protect “nearly all” workers from the adverse health effect that was seen in the animal model.

Since the NOEL or LOEL are important in this process, it would seem worthwhile to investigate them further.  The NOEL as its name implies is the dose where there is no observable adverse effect on the tested animals.  In a practical sense it is the dose whose results are indistinguishable from the control group.  The comparison between the responses of animal test groups is typically done with statistical tests to determine if there was as statistically significant effect caused by the dose.   In my work with Toxicologists I saw that their pretest estimation of the highest dose that would produce a NOEL was much sought after and the matter of a lot of deliberation on their part.   Indeed, they know that the NOEL (or LOEL) will drive a measure of the allowable exposure to that substance which is what we have in any established OEL.

Some folks make the distinction between the No Observed Effect Level (NOEL) and the No Observed Adverse Effect Level (NOAEL).  The NOEL being where no dose related effect can be discerned.   The NOAEL indicating that no adverse health effect occurs at that exposure.   For the purpose of this discussion let’s consider them the same.

Note that the LOEL (or LOAEL) is a dose in a test group that just missed being a NOEL (or NOAEL).  That is, it was just a tad too high so that a slight but statistically significant adverse health effect was detected.

So when we have a repeat dose toxicology study with a NOEL does that mean that we have truly found a threshold dose below which NOTHING bad will happen to any rat given this or a lower dose?   The clear answer to that question is NO.    The fact of the matter is that a true threshold for any large population (that is, ALL rats or ALL people), if it exists, is essentially impossible to determine given the above methodology of testing groups of animals with 5 to 50 animals in each group.    It is a matter of statistical reality that is best described by the binomial theorem.  

I will not go into the details of this theorem here except to state that it predicts the occurrence of chance events given some level of true effect or a true relationship (e.g., half of all coin flips will be heads).   Casino operators know all about this theorem and it is the reason that they will always have the “house” edge and will always come out on top for any game they offer in the long run.  However, I digress; the cold truth is that it has been convincingly shown that zero response (i.e., the NOEL) in toxicology studies could represent a response level as high as 20%. Indeed, based on a computer simulation study, Leisenring and Ryan (1992) show that the average NOEL for quantal data as described above actually could be a 3 to 21% adverse response level depending on the experimental design and shape of the dose-response curve.

So on the strength of this reality let’s assume that the typical NOEL represents, on average, a 10% effect level in rats.  Well, most of us are clearly not rats and we may be more or less susceptible to the toxic effects of the substance.   Thus, besides the uncertainty born of testing a limited number of animals, we have another reason that safety (or uncertainty) factors are applied to (divided into) NOELs and LOELs with larger factors being applied to LOELs for obvious reasons.   I will discuss the sizing of safety/uncertainty factors in a future blog but I think you can see that it could be considered a tricky business, at the end of which we have an OEL designed to protect “nearly all” but without any reasonable quantitative explaination as to what that means.

Staying with the NOEL for now, one might ask is there a more elegant way to get to the NOEL operationally defined as the estimated 10% effect level?   Fortunately, the answer is YES.  The EPA has developed a very nice piece of PC freeware entitled:  Benchmark Dose Modeling Software (BMDS). The software uses all the dose-response data in the toxicological study, not just the NOEL, and then calculates the estimated BMD or Benchmark Dose along with its uncertainty bounds.  If you set the BMD to 10% you have a more elegant way of estimating the NOEL.  Online training modules on the theory and use of this freeware are available at:
You may or may not want to become a BMDS maven but I urge you to at least look at it.  The take-away from all this is that given typical toxicological data we essentially cannot prove the existence of a true threshold, although one may indeed truly exist.  We can describe the level of predicted risk at any dose at or below any exposure including the exposure at the OEL along with its uncertainty using modeling.   That will also be the subject of a future blog.

Leisenring, A.J., and L. Ryan: Statistical properties of the NOAEL. Regul. Toxicol. Pharmacol. 15:161-171 (1992).

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