MCDA applications in chemical alternatives assessment: a narrative review

This article reviews the application of multicriteria decision analysis (MCDA) in chemical alternatives assessment (CAA) and presents an overview of how the methodology has been applied within CAA. The study aimed to identify research that uses MCDA to identify the most harmful or least problematic chemicals and evaluate its current use in CAA. The study supports the Partnership for the Assessment of Risks from Chemicals (PARC) in developing a toolbox for safe and sustainable by design (SSbD). 520 studies were analysed, and 21 studies were included. Although MCDA in CAA is still emerging, it shows growth potential in decision analysis and chemical alternatives assessment. The reviewed studies cover various CAA applications and methodological approaches. Multiattribute utility theory (MAUT) is the most often used, followed by Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), ÉLimination Et Choix Traduisant la REalité (ELECTRE), and analytic hierarchy process (AHP). Experimental data and in silico data have been used with roughly equal frequency as input data. Group decision-making involving stakeholders with conflicting interests is rarely addressed, with parameter weighting and problem structuring usually handled by authors, sometimes with expert input. Another little discussed topic is the use of external normalisation of input data. In silico generated predictions on chemical alternatives’ properties come with varying degrees of uncertainty, remaining an issue in CAA with MCDA.