PBT assessment and prioritization of contaminants of emerging concern: Pharmaceuticals

Abstract

The strong and widespread use of pharmaceuticals, together with incorrect disposal procedures, has recently made these products contaminants of emerging concern (CEC). Unfortunately, little is known about pharmaceuticals' environmental behaviour and ecotoxicity, so that EMEA (European Medicines Agency) released guidelines for the pharmaceuticals' environmental risk assessment. In particular, there is a severe lack of information about persistence, bioaccumulation and toxicity (PBT) of the majority of the thousands of substances on the market. Computational tools, like QSAR (Quantitative Structure Activity Relationship) models, are the only way to screen large sets of chemicals in short time, with the aim of ranking, highlighting and prioritizing the most environmentally hazardous for focusing further experimental studies. In this work we propose a screening method to assess the potential persistence, bioaccumulation and toxicity of more than 1200 pharmaceutical ingredients, based on the application of two different QSAR models. We applied the Insubria-PBT Index, a MLR (Multiple Linear Regression) QSAR model based on four simple molecular descriptors, implemented in QSARINS software, and able to synthesize the PBT potential in a unique cumulative value and the US-EPA PBT Profiler that assesses the PBT behaviour evaluating separately P, B and T. Particular attention was given to the study of Applicability Domain in order to provide reliable predictions. An agreement of 86% was found between the two models and a priority list of 35 pharmaceuticals, highlighted as potential PBTs by consensus, was proposed for further experimental validation. Moreover, the results of this computational screening are in agreement with preliminary experimental data in the literature. This study shows how in silico models can be applied in the hazard assessment to perform preliminary screening and prioritization of chemicals, and how the identification of the structural features, mainly associated with the potential PBT behaviour of the prioritized pharmaceuticals, is particularly relevant to perform the rational a priori design of new, environmentally safer, pharmaceuticals.

Keywords: PBT; Pharmaceuticals; Prioritization; QSAR; Screening.