Ecotoxicological assessment of pharmaceuticals and personal care products using predictive toxicology approaches
With their widespread and ever increasing use, active pharmaceutical ingredients (API) and personal care products (PCP) represent contaminants of emerging concern for the aquatic and terrestrial environments. Today, numerous countries worldwide have issued regulations and guidance to cover the environmental risk assessment of these substances, but in many cases the necessary hazard data is missing or incomplete.
In their comprehensive review, Kar et al. (2020) first present a qualitative and quantitative overview of the pharmaceuticals and PCPs (globally referred to as ‘PPCPs’) of highest environmental concern, then discuss how predictive toxicology approaches can be applied to complement hazard data packages, but also to design environmentally friendlier PPCPs.
Commonly found APIs in the environment include a number of antibiotics, beta-blockers, analgesics and non-steroidal inflammatory drugs (NSAIDs), antineoplastic/anticancer compounds, blood-lipid lowering agents, CNS acting drugs, antiviral and anti-parasitic drugs, hormones and metabolites of the above. Frequently detected PCPs are in the categories of disinfectants and bactericides, fragrances, insect repellants, preservatives and UV filters/sunscreen agents. Because most PCPs are designed for external use, metabolic changes inside the body are less relevant for these substances.
The use of in silico tools to predict the hazardous properties of PPCPs is growing, in line with the efforts to reduce animal testing in toxicology and ecotoxicology. Predictive tools comprise QSTR (quantitative structure-toxicity relationship models, i.e. (Q)SAR systems in which the toxicity endpoints are modelled and predicted), interspecies QSTR (i-QSTR/QTTR) models, read-across, pharmacophore (toxicophore)-based approaches and molecular docking applications. An array of expert systems for the prediction of chemical toxicities also exists, built upon experimental data and/or rules derived from such data (e.g. OECD (Q)SAR Toolbox, ECOSAR, CATALOGIC, etc.).
Kar and collaborators review the main endpoints for in silico modelling of ecotoxicity as well as existing ecotoxicity databases in relation to PPCPs. The authors then critically analyze SAR and (Q)SAR studies for ecotoxicological assessment of PPCPs (e.g. existing models, imperative features responsible for ecotoxicity and fate) and finally discuss challenges such as mixture toxicity and the impact of metabolism.
This publication, written a series of experts in the field, is a very good source of useful data on PPCPs in the environment, environmental risk assessment methodologies across various regions, existing in silico tools/databases for environmental endpoints, comprising detailed information and concrete examples.
