Characterization of the human kinetic adjustment factor for the health risk assessment of environmental contaminants

Abstract

A default uncertainty factor of 3.16 (√10) is applied to account for interindividual variability in toxicokinetics when performing non-cancer risk assessments. Using relevant human data for specific chemicals, as WHO/IPCS suggests, it is possible to evaluate, and replace when appropriate, this default factor by quantifying chemical-specific adjustment factors for interindividual variability in toxicokinetics (also referred to as the human kinetic adjustment factor, HKAF). The HKAF has been determined based on the distributions of pharmacokinetic parameters (e.g., half-life, area under the curve, maximum blood concentration) in relevant populations. This article focuses on the current state of knowledge of the use of physiologically based algorithms and models in characterizing the HKAF for environmental contaminants. The recent modeling efforts on the computation of HKAF as a function of the characteristics of the population, chemical and its mode of action (dose metrics), as well as exposure scenario of relevance to the assessment are reviewed here. The results of these studies, taken together, suggest the HKAF varies as a function of the sensitive subpopulation and dose metrics of interest, exposure conditions considered (route, duration, and intensity), metabolic pathways involved and theoretical model underlying its computation. The HKAF seldom exceeded the default value of 3.16, except in very young children (i.e., <≈ 3 months) and when the parent compound is the toxic moiety. Overall, from a public health perspective, the current state of knowledge generally suggest that the default uncertainty factor is sufficient to account for human variability in non-cancer risk assessments of environmental contaminants.

Evolution of chemical-specific adjustment factors (CSAF) based on recent international experience; increasing utility and facilitating regulatory acceptance

“…95th) to its central tendency (e.g. median) in the population (Meek et al 2002;Silverman et al 1999), such as illustrated for benzene, chloroform, and other solvents by Valcke and Krishnan (2014). Alternatively, they are calculated as the ratio between the values for an upper percentile in a presumed susceptible subpopulation and the central tendency in the general healthy population.…”

“…These investigations also tended to include multiple dose metrics without specifying which may be most relevant. Some authors, such as Clewell et al (2004), Valcke and Krishnan (2014) and Valcke and Krishnan (2011) computed HK AF as a function of the exposure route and duration by simulating exposure to concentrations that were determined based on route-specific chronic and acute guidelines of interest. Similarly, M€ ork et al (2014) simulated exposure concentrations corresponding to the RfC for styrene, toluene, and methyl chloride, and M€ ork and Johanson (2010) simulated exposures to an acetone concentration (29 ppm) proposed previously in the literature for the purposes of RfC and RfD determination .…”

An assessment of the impact of multi‐route co‐exposures on human variability in toxicokinetics: A case study with binary and quaternary mixtures of volatile drinking water contaminants

“…The use of such equations ensures that physiological parameters are coherent to a given combination of body weight/height and age values while authorizing age‐specific variations in the relationships between the physiological parameters and their determinants (Valcke & Krishnan, ). Besides, as only slight gender‐related pharmacokinetic differences are expected between males and females for VOCs such as those studied herein (Clewell et al, ; Sarangapani et al, ), gender‐specific equations that are available for several parameters were averaged together into a single common equation for both males and females, as described in Valcke and Krishnan (, , , ).…”

Diagnosis, monitoring and prevention of exposure-related non-communicable diseases in the living and working environment: DiMoPEx-project is designed to determine the impacts of environmental exposure on human health

“…Data from indirect approaches have to be extrapolated to the effective dose in the population by considering pollutant transport processes, accumulation and fate processes in the environment, exposure scenarios, demographic and geographic attributes, lifestyle behavior, human constitution and the pharmacokinetics of the agent. Moreover, an estimation of individual exposure has to include the intra-individual variability of these extrapolation factors within the population [ 36 , 37 ]. Each extrapolation model should be validated in respect of its performance and uncertainty.…”