Environmental Risk Assessments of Multiclass Pharmaceutical Active Compounds: Selection of High Priority Concern Pharmaceuticals Using Entropy-Utility Functions Publisher Pubmed



Golbaz S¹ ; Yaghmaeian K¹ ; Isazadeh S² ; Zamanzadeh M¹ Show Affiliations
Source: Environmental Science and Pollution Research Published:2021

Abstract

This research aimed to identify high-risk pharmaceutically active compounds (PhACs) by analyzing occurrence (O), persistence (P), bioaccumulation (B), and toxicity (T) of 62 drugs which are widely used in Iran. A comprehensive approach was taken in risk assessment of the selected PhACs and in their prioritization using multiple-criteria decision analysis (MCDA) such as utility functions and principal component analysis (PCA). In practice, assigning weight to each criterion (i.e., O, P, B, and T) for risk assessment of PhACs is a challenge. In this research, the impact of giving both equal and unequal weight to each criterion by using a quantitative entropy method was studied. For risk assessment, two exposure approaches (consumption rate and occurrence of PhACs) and three MCDA approaches (PCA and utility functions with and without equal weights for each criterion) were compared. The utility function using equal weights for all O, P, B, and T criteria showed that thioridazine, pimozide, chlorpromazine, sertraline, clomipramine, and aripiprazole were at the highest level of risk, with concern score of 0.75, 0.75, 0.67, 0.58, 0.58, and 0.58, respectively. Unequal weight approach included additional compounds such as fluoxetine, citalopram, and methadone as a priority. All three MCDA approaches showed that sedatives and antidepressants were prevalent PhACs in the risk-based priority lists. However, the exposure-based approaches showed antibiotics and analgesics as the pharmaceutical of the highest priority. Overall, selection of the high priority concern pharmaceuticals depends on the prioritization approach employed. However, the utility function using unequal weights is a more conservative and effective approach for prioritization. © 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.