Safety factors, data extrapolation

NOAEL (no-observed-adverse-effect level) is defined as the highest dose at which no adverse effects are observed in the most susceptible animal species. The NOAEL is used as a basis for setting human safety standards for acceptable daily intakes (ADIs), taking into account uncertainty factors for extrapolation from animals to humans and inter-individual variabilities of humans. The adequacy of any margin of safety or margin of exposure must consider the nature and quality of the available hazard identification and dose-response data and the reliability and relevance of the exposure estimations. In some cases, no adverse endpoint can be identified such as for many naturally occurring compounds that are widespread in foods. In that case, an ADI Not Specified is assigned. ... 

The fixed safety factors are apphed in this EPA method. The safety factors used are based on arbitrary extrapolation values of 10 going from (i) the laboratory (single species) to the held (whole ecosystem) situation and (ii) acute to chronic toxicity data. A similar approach is used to derive critical limits for surface water. 

There are of course many mathematically complex ways to perform a risk assessment, but first key questions about the biological data must be resolved. The most sensitive endpoint must be defined along with relevant toxicity and dose-response data. A standard risk assessment approach that is often used is the so-called divide by 10 rule . Dividing the dose by 10 applies a safety factor to ensure that even the most sensitive individuals are protected. Animal studies are typically used to establish a dose-response curve and the most sensitive endpoint. From the dose-response curve a NOAEL dose or no observed adverse effect level is derived. This is the dose at which there appears to be no adverse effects in the animal studies at a particular endpoint, which could be cancer, liver damage, or a neuro-behavioral effect. This dose is then divided by 10 if the animal data are in any way thought to be inadequate. For example, there may be a great deal of variability, or there were adverse effects at the lowest dose, or there were only tests of short-term exposure to the chemical. An additional factor of 10 is used when extrapolating from animals to humans. Last, a factor of 10 is used to account for variability in the human population or to account for sensitive individuals such as children or the elderly. The final number is the reference dose (RfD) or acceptable daily intake (ADI). This process is summarized below. 

Humans are more sensitive chan the test animals, so caution is required in extrapolating animal data to humans. The authors estimated a 6,650-fold safety factor between the EC50 for these threshold values and the CS concentration likely to cause the least detectable corneal damage in the human eye. 

An important outcome of the JECFA evaluation is the establishment of an ADI for a food additive. The ADI is based on the available toxicological data and the no adverse effect level in the relevant species. JECFA defines the ADI as an estimate of the amount of a food additive, expressed on a body weight basis, that can be ingested daily over a lifetime without appreciable health risk (8). JECFA utilizes animal data to determine the ADI based on the highest no-observed-adverse-effect level (NOAEL), and a safety factor is applied to the NOAEL to provide a margin of safety when extrapolating animal data to humans. JECFA typically uses safety factors of 50, 100, or 200 in the determination of an ADI. The NOAEL is divided by the safety factor to calculate the ADI. The food additive is considered safe for its intended use if the human exposure does not exceed the ADI on a chronic basis. This type of information may potentially be used to help assess the safety of a pharmaceutical excipient that is also used as a food additive, based on a comparison of the ADI to the estimated daily intake of the excipient. 

Human toxicity data, especially the median lethal dose, is extrapolated from animals or from accidental poisoning, homicides and suicides. Extrapolations from animal data are educated estimates which consider the differences in species and building in a safety factor. If a lethal dose is 10 mg/kg in a rat and we consider a human to be 10 times more sensitive 1 mg/kg will have another 10-fold safety margin. Animal testing also involves using what may seem as ridiculous doses in order to cover the safety factor. To find a statistically valid effect which occurs once in one million subjects, several million animals would have to be used, which is exhorbitantly... 

The safety factor is a number that reflects the degree or amount of uncertainty that must be considered when experimental data are extrapolated to the human population. When the quality and quantity of dose-response data are high, the uncertainty factor is low when the data are inadequate or equivocal, the uncertainty factor must be larger... 

Safety factor approach for chemicals that cause deterministic effects. Traditional toxicologic procedures for chemicals that can induce deterministic effects, which are assumed to have a threshold dose, define RfD for humans or animals as some fraction of NOAEL. This fraction is determined by establishing safety factors to account for weaknesses and uncertainties in the data and in the extrapolation from animals to humans. In the safety factor approach, doses below RfD are assumed not to result in a response because they are below the threshold of toxicity (Dourson and Stara, 1983 Renwick and Lazarus, 1998 Weil, 1972). 

Third, safety factors are based on a "no-adverse-effect" level. Testing In more than one animal species provides a better reflection of what to expect In the human, and allows extrapolation of safety data from the animal to the human by the use of a safety factor. In determining an ADI for humans, the FDA applies a safety factor to the highest "no-adverse-eflfect" level determined in an appropriate animal study. The safety factor Is Intended to account for differences between the animal and human and to provide an adequate margin of safety for the consumer. 

Calculations are performed to obtain values for the predicted environmental concentration (PEC) and the predicted non-effect environmental concentration (PNEC). Calculations of PEC are based on known release rates and dilution factors in the environment. To estimate PNEC, one divides the LC50 or EC50 for the most sensitive species tested in the laboratory by an arbitrary safety factor (often 1000). This allows room for the great uncertainty in extrapolating from laboratory toxicity data for one species to expected field toxicity for other species. 

In estimating the cumulative risk of a chemical in LCA, dose-response extrapolations can be based on toxicological benchmarks. Such a benchmark approach is considered more appropriate for use in comparative assessment contexts, such as in an LCA study. Benchmarks are an exposure measure associated with a consistent change in response, such as the 10% or even the 50% effect level. Regulatory-based measures do not necessarily provide a consistent risk basis for comparison, as they were often never developed for use in such a comparative context or to facilitate low dose-response extrapolation. Other data differences include the use of median, rather than extreme, data in the fate and exposure modeling, as well as the consideration of safety factors only as part of the uncertainty assessment and not as an integral part of the toxicological effects data. 

The existing methods available for scientifically defensible risk characterization are not yet ideal since each step has an associated uncertainty resulting from data limitation and incomplete knowledge on exact mechanism of action of the toxic chemical on the human body. For noncancer end points, safety factors or uncertainty factors are applied since these effects are assumed to have a threshold below which no adverse effect is expected to be observed. US EPA has used the concept of a reference concentration (RfC) to estimate acceptable daily human exposure from HAPs. The RfC was adapted for inhalation studies based on a reference dose (RfD) method previously used for oral exposure assessment. The derivation of the RfC differs from that for the RfD in the use of dosimetric adjustment to extrapolate the exposure concentration for animals to a human equivalent concentration. Both are estimates, with uncertainty spaiming perhaps an order of magnitude, of a daily exposure to the human population, including sensitive subgroups, which would be without appreciable risk of deleterious effects over a lifetime. 

Scientists then determine the appropriate uncertainty (or safety) factors to apply to the no-observed-adverse-effect level (NOAEL) or lowest-observed-adverse-effect level (LOAEL) for the critical effect, based on considerations of the available toxicity, toxicodynamic, and toxicokinetic data. Uncertainty factors (UFs) used in the estimation of safe doses are necessary reductions to account for the lack of data and inherent uncertainty in these extrapolations. Other areas of uncertainty include extrapolations of subchronic-to-chronic exposure, LOAEL to NOAEL, and use of an incomplete database. The major assumptions underlying each of these UFs are described in Table 1. 

The main purpose of the toxicity tests just described is to provide a data base that can be used to evaluate the hazard and assess the risk associated with the use of a pesticide. In practice the no observable effect level (NOEL) found in the most sensitive animal species tested in chronic studies is used. To extrapolate a safe dose for human consumption, a safety factor of 100 is usually used. For example, if the NOEL in the most sensitive animal species e.g. the dog from the chronic feeding study, was 10 mg/kg of body weight, then the acceptable daily intake (ADI) for man would be... 

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