Antiviral substances are considered emerging contaminants. Once released into the environment, they may affect organisms through complex and often still-unknown mechanisms. This study focuses on a class of antiviral substances with potential use in treating COVID-19 patients, aiming to identify specific structural characteristics that significantly contribute to their ecotoxicity. An empirical approach called quantitative structure–activity relationship (QSAR) was used for this purpose. The study examined 13 antiviral substances: atazanavir, daclatasvir, darunavir, emtricitabine, favipiravir, lopinavir, nirmatrelvir, oseltamivir, remdesivir, ribavirin, ritonavir, and sofosbuvir. The ecotoxicity of these antivirals was assessed using three tests: the Aliivibrio fischeri test, the Chlorella sp. test, and the Pseudomonas putida test. These three microorganisms represent different trophic levels in aquatic and soil ecosystems. Ecotoxicity was expressed as EC₂₀ and EC₅₀, and these values served as the dependent variables in the QSAR models. A large set of numerical descriptors calculated from the molecular structures of the antivirals was used as an independent variable. EC₂₀-based QSAR models offer insight into the effects of antivirals under sub-lethal exposure conditions. The results indicated that sub-lethal exposure in Aliivibrio fischeri was associated with favorable electronic properties and compact structures that promote cellular accumulation, while long-range fragments reduced toxicity. In Chlorella sp., sub-lethal exposure was driven by optimal molecular size, chain length, and specific electronic groups enabling cell penetration and biochemical inhibition. For sub-lethal exposure in P. putida, lipophilicity and reactive group geometry enhanced toxicity, while high short-range polarity mitigated it by limiting membrane permeability. Acute toxicity patterns showed similar trade-offs: strong electronic reactivity increased potency, but steric bulk, long-range polarity, or unfavorable mass distribution frequently restricted bioavailability and reduced toxic effects. Overall, the models demonstrated that antiviral toxicity results from a balance of electronic activity, structural accessibility, and physicochemical constraints, providing a mechanistic basis for predicting the environmental risk of selected antiviral substances.

The increasing presence of SARS-CoV-2 antivirals (SASs) in wastewater threatens aquatic ecosystems, making it necessary to better understand their removal efficiency during biological treatment. This study evaluates the removal percentages, kinetic mechanisms, and toxicity profiles of six SASs, daclatasvir (DCV), darunavir (DRV), favipiravir (FAV), lopinavir (LOP), remdesivir (REM), and ritonavir (RIT), using activated sludge. A full factorial design combined with response surface methodology (RSM) was used to assess the impact of pH, temperature (T), and mixed liquor suspended solids (MLSS) on SAS removal and microbial stability. The results distinguished two dominant removal pathways. DCV and LOP were primarily removed by adsorption, whereas DRV, FAV, REM and RIT were predominantly removed through biodegradation involving enzymatic transformation and bacterial co-metabolism. RSM achieved a desirability score of 0.772 and identified the optimal operating conditions (pH = 6.08, MLSS = 4.41 g/L, and T = 44.99 °C), resulting in removal efficiencies above 93% for all compounds except DRV, which remained the limiting compound with a maximum removal efficiency of 66%. Perturbation analysis showed that all tested factors have a distinct influence on process performance. These established kinetic trends should support further investigations into advanced biological wastewater treatment methods and precise ecotoxicity profiling of emerging biotransformation products.

This study investigated the removal of SARS-CoV-2 antivirals substances (SASs) in wastewater treatment systems through kinetic analysis and response surface modeling based on a full factorial experimental design (3³). Quadratic models best described the removal of most SASs, revealing nonlinear interactions among experimental factors and identifying the SASs mixture ratio as the key determinant of removal efficiency. Based on their removal behavior, the investigated SASs were classified into three groups: reversible adsorption (FAV, REM), enhanced bioavailability (DCV, DRV) and irreversible adsorption (LOP, RIT). LOP and RIT exhibited the highest adsorption affinities and formed the initial layer on activated sludge, whereas the limited removal of DRV and FAV reduced the overall treatment efficiency. The increased bacterial Colony-Forming Unit (CFU) suggests enhanced microbial activity, which may have promoted extracellular polymeric substance (EPS) production, contributing to reduced toxicity toward Aliivibrio fischeri. Finally, integrating RSM-derived polynomial models with artificial intelligence offers a promising approach for predicting and optimizing the removal of SARS-CoV-2 antivirals in conventional wastewater treatment plants.

The increasing presence of SARS-CoV-2 antiviral substances (SASs) in wastewater threatens aquatic ecosystems, making it necessary to better understand their removal efficiency during photooxidative treatment. The aim of this study was to evaluate UV-C/H₂O₂ and UV-C/S₂O₈²⁻ processes for treating thirteen SASs (atazanavir, daclatasvir, darunavir, emtricitabine, favipiravir, lopinavir, nirmatrelvir, oseltamivir, remdesivir, ribavirin, ritonavir, sofosbuvir, and umifenovir). The influence of pH and oxidant concentration on antivirals’ degradation was studied through full factorial plan and response surface modeling. It was established that degradation by both photooxidative processes obeys pseudo-first-order kinetic regime. Degradation kinetics of SASs is highly dependent on both process parameters, [SAS]:[OX], and pH, respectively, except for UMF in the UV-C/H₂O₂ process where the process is dependent only on pH. Regarding the reaction kinetics, in most cases degradation kinetics in UV-C/S₂O₈²⁻ processes are several times faster in comparison to UV-C/H₂O₂ process.