Cefic-lri Programme | European Chemical Industry Council

LRI-B22: Human exposure assessment framework for complex substances


Existing human exposure models were mainly developed and calibrated with data for mono-constituent substances. In many situations, however, humans may come into contact with multiple chemicals simultaneously, as in the case of use of a formulated product containing multiple substances or upon the contact with a complex substance (e.g. essential oils), which by definition is comprised of multiple individual constituents. The fact that these constituents may have different physicochemical properties makes complex substance exposure assessments particularly challenging.

This project aims to investigate the mechanisms and processes influencing inhalation and dermal external exposure to multiple chemicals originating from a common source (terminology aligned with WHO/IPCS framework, [1]) like a liquid complex substance. In this scenario, the interactions between the individual constituents of a complex substance may impact their exposure potential/bioaccessibility by governing the factors needed to predict the associated diffusion and mass transfer kinetics of inhalation and dermal exposures during and post-application, e.g. air-liquid and dermal-liquid partitioning equilibria. Appropriate solution thermodynamics models may be capable of offering a reasonable scientific explanation of the constituents’ interactions effect to accurately predict the true nature of human external (co-)exposure and enable a “whole substance” approach to exposure assessment of complex substances.

An example of a simple solution thermodynamics model is the Raoult’s law that can be applied when the constituents of interest are assumed to behave as if they were in an “ideal” liquid. The deviation from ideality, however, will increase with increasing differences between the molecular environments of the pure solute compared to that of the solvent. For such “non-ideal” liquids (e.g. solvent and solute has a large difference in polarity; non-hydrocarbon constituents are structurally diverse) it may be more appropriate to estimate air-liquid and dermal-liquid partitioning equilibria of substance constituents using other methods, e.g. UNIFAC .

UNIFAC is a mechanistic equation-of-state model that uses the functional groups present on the molecules in a solution to calculate the activity coefficients characterizing inter-molecular interactions . These activity coefficients can be determined experimentally or computationally [2]. The information is then used to predict the equilibrium partitioning behavior of the molecules in the model system. More recently, attempts have been made to explore the utility of the UNIFAC method for advancing in silico dermal absorption models [3] and for predicting phthalates emissions from polymer mixtures [4]. In addition, the Advanced REACH Tool [5] for worker exposure modeling already integrates the UNIFAC-based rules [6; 7], although, their predictive power has never been tested with measured data.

[1] Meek, M.E., Boobis, A.R., Crofton, K.M., Heinemeyer, G., van Raaij, M., Vickers, C., 2011. Risk assessment of combined exposure to multiple chemcials: a WHO/IPCS framework. Regulatory toxicology and pharmacology, 60, S1-S14.
[2] Fredenslund A, Jones R, Prausnitz JM. (1975) Group contribution estimation of activity coefficients in nonideal liquid mixtures. AlChE J; 21: 1086–99.
[3] Miller, M.A., Kasting, G., 2015. A spreadsheet-based method for simultaneously estimating the disposition of multiple ingredients applied to skin. Pharmaceutics, Drug Delivery and Pharmaceutical Technology. DOI 10.1002/jps.24450.
[4] Addington, C., 2018. ISES-ISEE 2018 annual meeting, 29.08.2018, Ottawa. Prediction of Composition and Emission Characteristics of Articles in Support of Exposure Assessment Cody Addington, Oak Ridge Institute for Science and Education, United States.
[5] Van Tongeren, M., Fransman, W., Spankie, S., Tischer, M., Brouwer, D., Schinkel, J., Cherrie, J.W., Tielemans, E., 2011. Advanced REACH Tool: Development and Application of the Substance Emission Potential Modifying Factor. Ann. Occup. Hyg., Vol. 55, No. 9, pp. 980–988, 2011. doi:10.1093/annhyg/mer093.
[6] Fransman, W., Cherrie, J.W., Van Tongeren, M., Schneider, T., Tischer, M., Schinkel, J., Marquart, H., Warren, N., Spankie, S., Kromhout, H., Tielemans, E., 2010. Development of a mechanistic model for the Advanced REACH Tool (ART) version 1.5. Available online at https://www.advancedreachtool.com/assets-1.5.12110.3/doc/ART%20Mechanistic%20model%20report_v1_5_20130118.pdf (last accessed on 01.02.2019).
[7] Gmehling, J., Wittig, R., Lohnmann, J., Joh, R., 2002. A Modified UNIFAC (Dortmund) Model. 4. Revision and Extension. Ind. Eng. Chem. Res., 2002, 41 (6), pp 1678–1688. DOI: 10.1021/ie0108043


The project is expected to increase current understanding of key mechanisms impacting inhalation and dermal external exposure of complex substances to allow derivation of realistic and representative exposure estimates. The results of this study should facilitate tiered approach to human exposure assessment of complex substances by determining circumstances, under which the interactions between complex substance constituents overrule the effect of other exposure determinants.

Furthermore, the findings may also lay groundwork for future development of improved computational tools to predict bio-accessibility of additives from polymer mixtures and elastomers for the purpose of human health exposure assessment and hazard classification.


It is advised that this project is structured in a manner that ensures regular delivery of the work products and timely review of the project deliverables by the LRI monitoring team.
The following activities are proposed to be included:

1. Gap assessment:

  • Literature review on the factors and mechanisms governing inhalation and dermal exposure to complex substances;
  • Identification of available measured exposure datasets (e.g. volatilization rates or partitioning coefficients) and/or recommendations to generate new data suitable for comparison with predicted exposure;

2. Identification of complex substances to focus on, covering potentially constituents of regulatory concern and/or of wide range of chemistries/properties. This should be done by the researchers in consultation with the LRI monitoring team based on a systematic analysis of relevant information.

NOTE: it is considered to be more feasible/practical to start investigating synthesized complex substances of pre-defined composition, assuming that the complex substances and formulated mixtures behave similarly in terms of the resulted external exposure. In the absence of good tools to assess the pre-mixed products, it is unreasonable to initiate the project with non-pre-mixed naturally occurring complex substances/UVCBs, where another layer of complexity of analytical characterization of the composition is introduced;

3. Scenario-based exposure modeling to selected complex substances for key worker and consumer exposure scenarios (to be identified by the researchers in consultation with LRI monitoring team) using:

  • Existing human exposure models (e.g. TRA, ART, ConsExpo, SkinPerm, Petrorisk, Product Intake Fraction).
  • Refined models (based on Raoultian and non-Raoultian solution thermodynamics models, or more complex quantum chemistry-based equilibrium thermodynamics models like COSMO-RS).

4. Series of dedicated scenario-based exposure experiments (where necessary) to generate evaluation datasets.

5. Evaluation of exposure predictions with measured data to conclude on the fit-for-purpose of the identified human exposure models and their practical implementation for the key exposure scenarios considered.

This project is expected to complement and leverage other LRI activities in this area (e.g. B13, ECO42, and B19). The successful research group is advised to take into account the findings and outcomes of such other work. Exploring possibility to use the deliverables in a regulatory context (e.g. REACH, BPR) is strongly encouraged.

Related links

Download here the full version of the RfP LRI-B22.

Timing: 18-24 months

LRI funding: €300 000

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