The mixture assessment or allocation factor: conceptual background, estimation algorithms and a case study example.

Current approaches for the prospective regulatory assessment of chemicals do not account sufficiently for elevated mixture risks. The Mixture Assessment Factor (MAF, better labeled a Mixture Allocation Factor) has been suggested for mixtures of industrial chemicals in the EU's Chemicals Strategy for Sustainability, as a pragmatic tool to account for potential mixture risks already during the risk and safety assessment of individual chemicals. The MAF is to be applied in scenarios in which specific mixture risk assessments are not possible, due to a lack of data and/or the complexity of the relevant exposure scenarios. Several approaches and algorithms for calculating a MAF have been suggested in the literature. The MAF_exact, which is a member of the larger MAF_ceiling class, is defined as the maximum fraction of the risk quotient of each chemical that is still acceptable to occur in a mixture, without the sum of risk quotients exceeding 1. This paper provides a comparative overview of the different MAF types discussed in the literature. It argues that the MAF_exact is the most promising approach in the context of chemical registration and authorization under regulatory frameworks such as REACH because this approach ensures a protection level that is similar to the protection level used in the current safety assessment of individual chemicals under REACH. Other MAF approaches either disproportionally impact low-risk substances, without leading to any appreciable risk reduction, or hamper risk communication because they lead to fluctuating residual risks after the MAF application. The paper also presents a case study comparing the different MAF approaches and finally discusses the MAF concept in the wider context of chemical regulation. [ABSTRACT FROM AUTHOR]