Dr. Michael J. Csicsaky, RTA Regulatory Toxicology for DW Experts: where do „parametric values” come from? - a short introduction by 10 easy lessons - PL/06/IB/EN/01

The „parametric values” in Annex B serve different purposes: PL/06/IB/EN/01 (a) Some are aimed at the protection of the distribution net from corrosion (pH, hardness) (b) Others are there for esthetical reasons (iron, manganese) (c) Most of them protect human health against toxic insult Only group (c) parameters are toxicologically derived ! If we understand how these limit values were derived, we can also derive health based limit values for hence unregulated substances or special scenarios.

PL/06/IB/EN/01 So, let’s find a safe „maximum value”. But how can we do it, and how safe is safe enough?

Statement by Theophrastus Bombastus von Hohenheim (Paracelsus)‏ 500 years old and still valid! Lesson 1 PL/06/IB/EN/01 What does this mean in terms of drinking water safety? Let us try to define a contaminant concentration in drinking water which is low enough to be non-toxic ( = not harmful to human health) ! What was he trying to say? Toxicity is not a property inherent to a substance, but just a matter of dosage

Classical approach: Lesson 2 PL/06/IB/EN/01 We run an experiment on animals where we use different dosages from high to low and count the losses in each dose group; then we use paper and pencil to determine the no-effect-level (NOEL). It is also called the no-adverse-effect-level (NOAEL). Let’s go back to the beginning of the last century and use NICOTINE as an example. Nicotine is a potent BIOCIDE.

Graphical determination of the no-effect-level on metric paper Case A: an experimental NOEL was obtained at a dose of 10 mg/kg Lesson 2, continued PL/06/IB/EN/01 No observable effect level (NOEL)‏ LD 50 = 50 mg/kg Curve fitted by eye 50% Lowest observable effect level (LOEL)‏ ? ?

Graphical determination of the no-effect-level on metric paper Case B: an experimental NOEL was not detected Lesson 2, continued PL/06/IB/EN/01 No observable effect level (NOEL)‏ LD 50 = 50 mg/kg Curve fitted by eye 50% Lowest observable effect level (LOEL)‏ ? ? ? ? ? Dataset Dose [mg/kg] Mortality [%]

The graphical determination of a no-effect-level on metric paper is imprecise: How can we do better? Lesson 2, continued PL/06/IB/EN/01 Sigmoid dose response curves are indicative of the presence of 3 subpopulations within the test population. The „sensitives“ react already to low doses, the „normals“ to intermediate doses and the „insensitives“ to high doses. Typically, the distribution of sensitivity follows the „normal distribution“ (Gaussian distribution, bell-shaped curve). Consequence: If the linear y-axis of the graph of the dose-response function is replaced by a non-linear y-axis corresponding to the normal distribution, the graph connecting the measured data becomes a straight line. This is what we call a „linearising transformation“ of a dataset. Advantage: Extrapolation towards the low dose range is easier to do and the results are more reliable!

Graphical determination of no-effect-level on probability paper in cases where no experimental NOEL was obtained Lesson 2, continued PL/06/IB/EN/01 NOAEL (extrapol.) < 9 mg/kg LD 50 = 50 mg/kg LOAEL = 20 mg/kg

What are the PRO´s and CON´s of the continued use of NOAEL / LOAEL as toxicity parameters ? Lesson 2, continued PL/06/IB/EN/01 PROs: huge background literature for comparisons generally accepted as starting points for standard setting CONs: the experimentally determined NOAEL, but to some extend also the LOAEL, are a function of the number of animals per dose group and the sensitivity distribution within that group; they only allow for comparisons with other substances if the group size is standardised (OECD guidelines!) and the sensitivity variance is low (inbred / outbred strains)‏ Example: if only 1 % of the test animals are hypersensitive, their reaction will be missed with a 5:1 probability if there are only 20 animals per dose group (the LOAEL will be too high) the shape of the dose-response curve is disregarded (the LOAEL or NOAEL is based on the observation in just one dose group)‏

Lesson 3 PL/06/IB/EN/01 What could be an alternative ? - The EPA approach We might use a model fit to find the upper limit of the dose, where 10% of all tested animals would show an adverse effect. The interpolated „benchmark dose“ could substitute the experimental LOAEL which is typically of the order of 5 % (1 animal in 20 exposed animals shows an adverse effect).

Modern approach, sophisticated level = curve fitting by dedicated computer software like BMDS Lesson 3, continued PL/06/IB/EN/01 Threshold level = 9 mg/kg? LD 50 = 50 mg/kg 10% Benchmark Dose (where 10% of all ex- posed are affected)‏ All data points with error bars Curve fitted by software (after internal linearising transformation)‏

PRO´s and CON´s of the benchmark dose procedure (BMDL10)‏ Lesson 3, continued PL/06/IB/EN/01 PRO´s It does not help us finding the „true“ effect threshold dose separating the highest tolerated dose (no-adverse-effect-level) from the lowest dose where unwanted effects are produced (adverse-effect-level) – simply because the probit-transformation does not allow extrapolations to zero. It works quite well, however, if we estimate the dose for an effect probability of say 1 in The benchmark dose method uses the full information gained from all dose groups, the BMD estimate is therefore more stable as compared to a LOAEL estimate based on just one dose group. On top of that, „statistical noise“ in the data will be compensated by using the lower bound 95%-limit on dose instead of the central estimate of the dose. CON´s

How safe is safe enough: compensating for the „noise“ in the data Lesson 4 PL/06/IB/EN/01 All biological measurements are corrupted by statistical noise; if you repeat an experiment, it is highly unlikely that you get exactly the same result twice. If you repeat it a hundred times, the distribution of individual values within the same dose group will follow the normal distribution (Gaussian „bell-shaped” curve). The 90% confidence limits are indicated by the error bars around the data points. To make your dose estimate safer, you would therefore want to incorporate the 95% upper limit of the confidence interval around the central estimate into your safe dose calculations instead of the central estimate itself. Unfortunately, this is rarely done in NOAEL / LOAEL – based standard setting.

How safe is safe enough: compensating for the uncertainty of the model Lesson 5 PL/06/IB/EN/01 best fit = central estimate of model parameters 95% lower confidence limit on BMD = BMDL

How safe is safe enough: compensating for exposure variability and variation of sensitivity Lesson 6 PL/06/IB/EN/01 In animal experimentation, all animals of a given group have a similar sensitivity and receive the same dose of a test substance. In a real-life situation of human beings, this would rarely happen. If we would have to judge the health risk from a drinking water contaminant, we would not only have to take into account - a scaling factor considering the differences in size and metabolic turnover between experimental animals and human beings, but also - variability of consumption (uptake, time pattern)‏ - variability of sensitivity (babies, infants, diseased, elderly people) For each risk group, we would have to build a conservative exposure scenario, calculate the daily uptake and compare it to the specific LOAEL for the particular group under consideration. The issue of animal --> man transfer

How safe is safe enough: compensating for exposure variability and variation of sensitivity Lesson 6, continued PL/06/IB/EN/01 Coming from NOAELs / LOAELs determined by animal experimentation, “safety margins” have to be applied when these parameters are adapted to be used with human beings: Typically, NOAELs / LOAELs determined by animal experimentation are reduced by a factor of 100 before they are applied in standard setting for human beings. We need conservative „scaling factors“ for adapting animal exposures to equivalent human exposures We need a safety factor for the wider range of uptake and possible differences in resorption between humans and experimental animals We need a safety factor for the wider range of sensitivity in human populations as compared to experimental animals

How safe is safe enough: compensating for exposure variability and variation of sensitivity Lesson 6, continued PL/06/IB/EN/01 A pragmatic approach is the „worst case scenario“ which combines the upper limit of consumption with the upper limit of sensitivity, e.g.: a baby of 500 g is fed on baby food prepared with 800 ml water per day If we find that a given exposure gives no rise to concern in the worst case scenario, we do not have to check the other scenarios. However, if an exposure causes a risk only to the most sensitive group, one possible option might be to e.g. issue a warning not to use this drinking water for the preparation of baby food, while other uses of drinking water might still seem acceptable from a toxicological point of view.

How safe is safe enough: compensating for exposure variability and variation of sensitivity Lesson 7 PL/06/IB/EN/01 While the application of a „worst case scenario“ leads to an implicite, but unquantified „overprotection“ of less sensitive groups with lower water consumption, there is a tendency in health science to try to quantify all sources of variance along the pathway from exposure to health effect. Standard “default values” (e.g., 2 l water consumption per day) are re- placed by distribution models (e.g., 0.2 to 5 l per day) and subsequently fed into computer models simulating all plausible combinations; the result is something like “a certain exposure level is safe for 99% of the population”. While the probabilistic approach allows for a more precise modelling of exposures and health outcomes in human populations, there is a theoretical risk that safety margins between tolerable exposures and actual exposures will be reduced in future at the risk of bad surprises if new toxicological insights require a lowering of NOAELs / LOAELs. This is called the probabilistic approach.

How safe is safe enough: the special case of carcinogens and ionising radiation Lesson 8 PL/06/IB/EN/01 The use of NOAELs or LOAELs as starting points for limit setting is limited to substances, for which the existence of an effect threshold can be assumed. This basic assumption does not hold for carcinogens and ionising radiation. It is assumed, however, that any exposure above zero increases the risk of contracting cancer. To estimate the health risk from a given exposure (e.g. arsenic), a linear extrapolation is made from the dose associated with a 10% cancer risk to the cancer risk of the dose under consideration. The dose has to be calculated as a lifetime dose (exposure concentration times duration of exposure, considering resorption efficiency) An acceptable size of the cancer risk has to be fixed before the correspon- ding exposure level can be derived. In general, life-time risks of the order of 1 in are considered acceptable in environmental settings.

How safe is safe enough: compensating for exposure uncertainty and variation of sensitivity Lesson 8, continued PL/06/IB/EN/01

Safety Margin versus Margin of Exposure (MOE)‏ Lesson 9 PL/06/IB/EN/01 A safety margin is the distance between actual exposure levels for a given toxic substance and a toxicologically derived and/or legally enforced limit value. If an overexposure occurs, the health risk will remain zero as long as the limit value is not reached. A margin of exposure is the distance between actual exposure levels for a given carcinogen and a toxicologically derived and/or legally enforced limit value. If an overexposure occurs, the health risk will be increased in proportion to the increase in lifetime dose – irrespective of the existence of a limit value.

How safe is safe enough: the comedian approach Lesson 10 PL/06/IB/EN/01 Karl Valentin I would like to rent an old mine. Yes, of course! But safe! From meteorites. Okay, but safety matters more to me than scarcity. Liesl Karlstadt And you would really like to live in there? But it is scaring in there! Safe from what? But meteorites are very rare.

How safe is safe enough: the administrative approach Lesson 10, continued PL/06/IB/EN/01 A non-zero health impact is not always feasable (think of current lead standard), especially not in the case of carcinogens and radionuclides. But who decides on the acceptability of health risks which cannot be easily averted? In the first place, it is the law maker; but he may be taken to court if the standards seem to be not strict enough to some. In that case, a scientifically sound basis of proposed standards is essential. Which toxicological endpoints are negligible, and which constitute a potential health hazard requiring legislative action? And if so, how would a limit value have to be derived in order to satisfy legal requirements? The linkage of toxicological and legal aspects will be addressed in the following presentation by Mr. Konietzka.