Comparison of Measured and Predicted Bioconcentration Estimates of Pharmaceuticals in Fish Plasma and Prediction of Chronic Risk

Using the fish plasma model to evaluate potential effects of pharmaceuticals in effluent from a large urban wastewater treatment plant

Several pharmaceuticals and personal care products (PPCPs) were evaluated using the fish plasma model (FPM) for juvenile Chinook salmon exposed to effluent from a large urban wastewater treatment plant. The FPM compares fish plasma concentrations to therapeutic values determined in human plasma as an indication of potential adverse effects. We used human Cmax values, which are the maximum plasma concentration for a minimum therapeutic dose. Observed and predicted plasma concentrations from juvenile Chinook salmon exposed to a dilution series of whole wastewater effluent were compared to 1%Cmax values to determine Response Ratios (RR) ([plasma]/1%Cmax) for assessment of possible adverse effects. Several PPCPs were found to approach or exceed an RR of 1, indicating potential effects in fish. We also predicted plasma concentrations from measured water concentrations and determined that several of the values were close to or below the analytical reporting limit (RL) indicating potential plasma concentrations for a large number of PPCPs that were below detection. Additionally, the 1%Cmax was less than the RL for several analytes, which could impede predictions of possible effect concentrations. A comparison of observed and predicted plasma concentrations found that observed values were frequently much higher than values predicted with water concentrations, especially for low log10Dow compounds. The observed versus predicted values using the human volume of distribution (Vd), were generally much closer in agreement. These data appear to support the selection of whole-body concentrations to predict plasma values, which relies more on estimating simple partitioning within the fish instead of uptake via water. Overall, these observations highlight the frequently underestimated predicted plasma concentrations and potential to cause adverse effects in fish. Using measured plasma concentrations or predicted values from whole-body concentrations along with improved prediction models and reductions in analytical detection limits will foster more accurate risk assessments of pharmaceutical exposure for fish.

What Approaches Should be Used to Prioritize Pharmaceuticals and Personal Care Products for Research on Environmental and Human Health Exposure and Effects?

Pharmaceuticals and personal care products (PPCPs) are released from multiple anthropogenic sources and thus have a ubiquitous presence in the environment. The environmental exposure and potential effects of PPCPs on biota and humans has aroused concern within the scientific community and the public. Risk assessments are commonly conducted to evaluate the likelihood of chemicals including PPCPs that pose health threats to organisms inhabiting various environmental compartments and humans. Because thousands of PPCPs are currently used, it is impractical to assess the environmental risk of all of them due to data limitations; in addition, new PPCPs are continually being produced. Prioritization approaches, based either on exposure, hazard, or risk, provide a possible means by which those PPCPs that are likely to pose the greatest risk to the environment are identified, thereby enabling more effective allocation of resources in environmental monitoring programs in specific geographical locations and ecotoxicological investigations. In the present review, the importance and current knowledge concerning PPCP occurrence and risk are discussed and priorities for future research are proposed, in terms of PPCP exposure (e.g., optimization of exposure modeling in freshwater ecosystems and more monitoring of PPCPs in the marine environment) or hazard (e.g., differential risk of PPCPs to lower vs. higher trophic level species and risks to human health). Recommended research questions for the next 10 years are also provided, which can be answered by future studies on prioritization of PPCPs. Environ Toxicol Chem 2024;43:488-501. © 2022 SETAC.

Multimodal Model to Predict Tissue-to-Blood Partition Coefficients of Chemicals in Mammals and Fish

Tissue-to-blood partition coefficients (Ptb) are key parameters for assessing toxicokinetics of xenobiotics in organisms, yet their experimental data were lacking. Experimental methods for measuring Ptb values are inefficient, underscoring the urgent need for prediction models. However, most existing models failed to fully exploit Ptb data from diverse sources, and their applicability domain (AD) was limited. The current study developed a multimodal model capable of processing and integrating textual (categorical features) and numerical information (molecular descriptors/fingerprints) to simultaneously predict Ptb values across various species, tissues, blood matrices, and measurement methods. Artificial neural network algorithms with embedding layers were used for the multimodal modeling. The corresponding unimodal models were developed for comparison. Results showed that the multimodal model outperformed unimodal models. To enhance the reliability of the model, a method considering categorical features, weighted molecular similarity density, and weighted inconsistency in molecular activities of structure-activity landscapes was used to characterize the AD. The model constrained by the AD exhibited better prediction accuracy for the validation set, with the determination coefficient, root mean-square error, and mean absolute error being 0.843, 0.276, and 0.213 log units, respectively. The multimodal model coupled with the AD characterization can serve as an efficient tool for internal exposure assessment of chemicals.

Multi-task machine learning models for simultaneous prediction of tissue-to-blood partition coefficients of chemicals in mammals

Tissue-to-blood partition coefficients (Ptb) are crucial for assessing the distribution of chemicals in organisms. Given the lack of experimental data and laborious nature of experimental methods, there is an urgent need to develop efficient predictive models. With the help of machine learning algorithms, i,e., random forest (RF), and artificial neural network (ANN), this study developed multi-task (MT) models that can simultaneously predict Ptb values for various mammalian tissues, including liver, muscle, brain, lung, and adipose. Single-task (ST) models using partial least squares regression, RF, and ANN algorithms for each endpoint were established for comparison. Overall, the performances of MT models were superior to those of ST models. The MT model using ANN algorithms showed the highest prediction accuracy with determination coefficients ranging from 0.704 to 0.886, root mean square errors between 0.223 and 0.410, and mean absolute errors ranging from 0.178 to 0.285 log units. Results showed that lipophilicity and polarizability of molecules significantly influence their partition behavior in organisms. Applicability domains (ADs) of the models were characterized by weighted molecular similarity density, and weighted inconsistency in molecular activities of structure-activity landscapes. When constrained by ADs, the models displayed enhanced predictive accuracy, making them valuable tools for the risk assessment and management of chemicals.

Pharmaceuticals and personal care products (PPCPs) in surface water and fish from three Asian countries: Species-specific bioaccumulation and potential ecological risks

In Asian developing countries, undeveloped and ineffective sewer systems are causing surface water pollution by a lot of contaminants, especially pharmaceuticals and personal care products (PPCPs). Therefore, the risks for freshwater fauna need to be assessed. The present study aimed at: i) elucidating the contamination status; ii) evaluating the bioaccumulation; and iii) assessing the potential risks of PPCP residues in surface water and freshwater fish from three Asian countries. We measured 43 PPCPs in the plasma of several fish species as well as ambient water samples collected from India (Chennai and Bengaluru), Indonesia (Jakarta and Tangerang), and Vietnam (Hanoi and Hoa Binh). In addition, the validity of the existing fish blood-water partitioning model based solely on the lipophilicity of chemicals is assessed for ionizable and readily metabolizable PPCPs. When comparing bioaccumulation factors calculated from the PPCP concentrations measured in the fish and water (BAF_measured) with bioconcentration factors predicted from their pH-dependent octanol-water partition coefficient (BCF_predicted), close values (within an order of magnitude) were observed for 58-91 % of the detected compounds. Nevertheless, up to 110 times higher plasma BAF_measured than the BCF_predicted were found for the antihistamine chlorpheniramine in tilapia but not in other fish species. The plasma BAF_measured values of the compound were significantly different in the three fish species (tilapia > carp > catfish), possibly due to species-specific differences in toxicokinetics (e.g., plasma protein binding and hepatic metabolism). Results of potential risk evaluation based on the PPCP concentrations measured in the fish plasma suggested that chlorpheniramine, triclosan, haloperidol, triclocarban, diclofenac, and diphenhydramine can pose potential adverse effects on wild fish. Results of potential risk evaluation based on the PPCP concentrations measured in the surface water indicated high ecological risks of carbamazepine, sulfamethoxazole, erythromycin, and triclosan on Asian freshwater ecosystems.

Pharmacology beyond the patient - The environmental risks of human drugs

BACKGROUND

The presence of pharmaceuticals in the environment is a growing global concern and although environmental risk assessment is required for approval of new drugs in Europe and the USA, the adequacy of the current triggers and the effects-based assessments has been questioned.

OBJECTIVE

To provide a comprehensive analysis of all regulatory compliant aquatic ecotoxicity data and evaluate the current triggers and effects-based environmental assessments to facilitate the development of more efficient approaches for pharmaceuticals toxicity testing.

METHODS

Publicly-available regulatory compliant ecotoxicity data for drugs targeting human proteins was compiled together with pharmacological information including drug targets, Cmax and lipophilicity. Possible links between these factors and the ecotoxicity data for effects on, growth, mortality and/or reproduction, were evaluated. The environmental risks were then assessed based on a combined analysis of drug toxicity and predicted environmental concentrations based on European patient consumption data.

RESULTS

For most (88%) of the of 975 approved small molecule drugs targeting human proteins a complete set of regulatory compliant ecotoxicity data in the public domain was lacking, highlighting the need for both intelligent approaches to prioritize legacy human drugs for a tailored environmental risk assessment and a transparent database that captures environmental data. We show that presence/absence of drug-target orthologues are predictive of susceptible species for the more potent drugs. Drugs that target the endocrine system represent the highest potency and greatest risk. However, for most drugs (>80%) with a full set of ecotoxicity data, risk quotients assuming worst-case exposure assessments were below one in all European countries indicating low environmental risks for the endpoints assessed.

CONCLUSION

We believe that the presented analysis can guide improvements to current testing procedures, and provide valuable approaches for prioritising legacy drugs (i.e. those registered before 2006) for further ecotoxicity testing. For drugs where effects of possible concern (e.g. behaviour) are not captured in regulatory tests, additional mechanistic testing may be required to provide the highest confidence for avoiding environmental impacts.

Concentrating mixtures of neuroactive pharmaceuticals and altered neurotransmitter levels in the brain of fish exposed to a wastewater effluent

Fish can be exposed to a variety of neuroactive pharmaceuticals via the effluent discharges from wastewater treatment plants and concerns have arisen regarding their potential impacts on fish behaviour and ecology. In this study, we investigated the uptake of 14 neuroactive pharmaceuticals from a treated wastewater effluent into blood plasma and brain regions of roach (Rutilus rutilus) after exposure for 15days. We show that a complex mixture of pharmaceuticals including, 6 selective serotonin reuptake inhibitors, a serotonin-noradrenaline reuptake inhibitor, 3 atypical antipsychotics, 2 tricyclic antidepressants and a benzodiazepine, concentrate in different regions of the brain including the telencephalon, hypothalamus, optic tectum and hindbrain of effluent-exposed fish. Pharmaceuticals, with the exception of nordiazepam, were between 3-40 fold higher in brain compared with blood plasma, showing these neuroactive drugs are readily uptaken, into brain tissues in fish. To assess for the potential for any adverse ecotoxicological effects, the effect ratio was calculated from human therapeutic plasma concentrations (HtPCs) and the measured or predicted fish plasma concentrations of pharmaceuticals. After accounting for a safety factor of 1000, the effect ratios indicated that fluoxetine, norfluoxetine, sertraline, and amitriptyline warrant prioritisation for risk assessment studies. Furthermore, although plasma concentrations of all the pharmaceuticals were between 33 and 5714-fold below HtPCs, alterations in serotonin, glutamate, acetylcholine and tryptophan concentrations were observed in different brain regions of effluent-exposed fish. This study highlights the importance of determining the potential health effects arising from the concentration of complex environmental mixtures in risk assessment studies.

Risks associated with the environmental release of pharmaceuticals on the U.S. Food and Drug Administration "flush list"

A select few prescription drugs can be especially harmful and, in some cases, fatal with just one dose when not used as prescribed. Therefore, the U. S. Food and Drug Administration (FDA) recommends that expired, unwanted, or otherwise unused portions of most of these drugs be disposed of quickly through a take-back program. If such an option is not readily available, FDA recommends that they be flushed down the sink or toilet. The goal of the current investigation was to evaluate the ecological and human-health risks associated with the environmental release of the 15 active pharmaceutical ingredients (APIs) currently on the FDA "flush list". The evaluation suggests that even when highly conservative assumptions are used-including that the entire API mass supplied for clinical use is flushed, all relevant sources in addition to clinical use of the API are considered, and no metabolic loss, environmental degradation, or dilution of wastewater effluents are used in estimating environmental concentrations-most of these APIs present a negligible eco-toxicological risk, both as individual compounds and as a mixture. For a few of these APIs, additional eco-toxicological data will need to be developed. Using similar conservative assumptions for human-health risks, all 15 APIs present negligible risk through ingestion of water and fish.

Uptake and Metabolism of Human Pharmaceuticals by Fish: A Case Study with the Opioid Analgesic Tramadol

Recent species-extrapolation approaches to the prediction of the potential effects of pharmaceuticals present in the environment on wild fish are based on the assumption that pharmacokinetics and metabolism in humans and fish are comparable. To test this hypothesis, we exposed fathead minnows to the opiate pro-drug tramadol and examined uptake from the water into the blood and brain and the metabolism of the drug into its main metabolites. We found that plasma concentrations could be predicted reasonably accurately based on the lipophilicity of the drug once the pH of the water was taken into account. The concentrations of the drug and its main metabolites were higher in the brain than in the plasma, and the observed brain and plasma concentration ratios were within the range of values reported in mammalian species. This fish species was able to metabolize the pro-drug tramadol into the highly active metabolite O-desmethyl tramadol and the inactive metabolite N-desmethyl tramadol in a similar manner to that of mammals. However, we found that concentration ratios of O-desmethyl tramadol to tramadol were lower in the fish than values in most humans administered the drug. Our pharmacokinetic data of tramadol in fish help bridge the gap between widely available mammalian pharmacological data and potential effects on aquatic organisms and highlight the importance of understanding drug uptake and metabolism in fish to enable the full implementation of predictive toxicology approaches.

Determining potential adverse effects in marine fish exposed to pharmaceuticals and personal care products with the fish plasma model and whole-body tissue concentrations

The Fish Plasma Model (FPM) was applied to water exposure and tissue concentrations in fish collected from two wastewater treatment plant impacted estuarine sites. In this study we compared predicted fish plasma concentrations to Cmax values for humans, which represents the maximum plasma concentration for the minimum therapeutic dose. The results of this study show that predictions of plasma concentrations for a variety of pharmaceutical and personal care products (PPCPs) from effluent concentrations resulted in 37 compounds (54%) exceeding the response ratio (RR = Fish [Plasma]/1%Cmax_total) of 1 compared to 3 compounds (14%) detected with values generated with estuarine receiving water concentrations. When plasma concentrations were modeled from observed whole-body tissue residues, 16 compounds out of 24 detected for Chinook (67%) and 7 of 14 (50%) for sculpin resulted in an RR_tissue value greater than 1, which highlights the importance of this dose metric over that using estuarine water. Because the tissue residue approach resulted in a high percentage of compounds with calculated response ratios exceeding a value of unity, we believe this is a more accurate representation for exposure in the field. Predicting plasma concentrations from tissue residues improves our ability to assess the potential for adverse effects in fish because exposure from all sources is captured. Tissue residues are also more likely to represent steady-state conditions compared to those from water exposure because of the inherent reduction in variability usually observed for field data and the time course for bioaccumulation. We also examined the RR in a toxic unit approach to highlight the importance of considering multiple compounds exhibiting a similar mechanism of action.

Testing the "read-across hypothesis" by investigating the effects of ibuprofen on fish

Human pharmaceuticals present in the environment have the potential to cause adverse effects on non-target organisms. The "read-across hypothesis" stipulates that pharmaceuticals will exhibit similar biological effects across species (e.g. human and fish) if the molecular target has been conserved and the effective drug concentrations are reached (Cmax). We tested this hypothesis by evaluating if ibuprofen, a non-selective inhibitor of prostaglandins and the cyclooxygenase (COX) enzyme, can mimic its primary effect in humans, on fish, at comparable plasma concentrations. The endpoints, prostaglandin E metabolite (PGEM) levels and the mRNA expression of COX (ptgs) gene, were measured in the gills of control and exposed fathead minnows (Pimephales promelas), using enzyme-immunoassay and quantitative real-time PCR (qPCR). Fish were exposed, for 24-72 h, to measured water concentrations of 9 (n = 12), 370 (n = 40) and 470 μg ibuprofen/L (n = 12). Water and blood plasma concentrations were determined using LC-MS/MS. Results showed that PGEM levels in fish exposed to 370 and 470 μg ibuprofen/L were significantly decreased compared to control fish, when mean plasma ibuprofen concentrations were 1.8-5.6-fold below the Cmax. The plasma ibuprofen concentrations and PGEM levels varied greatly between individuals. In fish exposed to 9 μg ibuprofen/L, when the mean plasma ibuprofen concentration was 224-fold below Cmax, no change in PGEM levels was observed. These data provide evidence for the read-across hypothesis, but suggest establishing a direct dose-response between internal plasma and PGEM is difficult, and would require significantly larger numbers of fish to overcome the inter-individual variation.