▼ VIEWPOINT
Effects of HUMAN PHARMACEUTICALS on Aquatic Life: Next Steps How do human pharmaceuticals get into the environment, and what are their effects? V IRGINI A L . CUNNINGH A M Gl a xoSmithK line M A RY BUZBY Merck a nd Co., Inc. THOM AS HUTCHINSON Astr a Zeneca FR A NK M ASTROCCO Pfizer, Inc. NEIL PA RKE Eli Lilly a nd Co. NICHOL AS RODEN Schering-Plough Corp.
P
harmaceuticals are designed to cure and treat disease and help people be healthy. However, the active pharmaceutical ingre dients (APIs) in these medicines, as either the original drug or its metabolites, can be released into the environment and be present in very low, but detectable, concentrations (1–5). This is primarily from patient excretion, which makes its way into sewage treatment plants (STPs) or sep tic systems. Along the way, some of these pharma ceutical substances are not completely degraded during treatment. As a result, some portions can be released into the environment via wastewater effluent. The potential also exists for release to the en vironment from sludge application to land, but here we will only consider direct release to surface waters. Some medicines may also enter the environment from disposal of unused products. Although com prehensive data are not currently available, the quantity of pharmaceutical compounds potentially released into the environment this way is suspected © 2006 American Chemical Society
to be small compared with that released into the environment from direct patient use. APIs can also enter the environment from farms, domestic animals, or manufacturing operations. The issues specific to other release scenarios are beyond the scope of this paper and have been discussed in depth elsewhere (6, 7). Although some APIs have been measured in drinking water (8, 9), the scientific consensus is that pharmaceuticals at the low levels detected in the environment do not pose an appreciable risk to human health (10). However, the possible effects of these substances on aquatic life are currently not well understood. Until now, conventional tests and assessments for the effects of APIs have been based on acute (short-term) endpoints, with assessment factors applied to the acute data to extrapolate to chronic (long-term) effects. As more chronic tests are reported, this approach does not appear to be valid for predicting chronic effects of some APIs, and more mechanistic approaches, such as comparative pharmacology, are being examined. june 1, 2006 / Environmental Science & Technology n 3457
How are potential impacts to aquatic life characterized? Answering this question requires a better under standing of both the exposure potential (i.e., the ex tent to which aquatic life might be exposed to these compounds) and the effects potential (i.e., wheth er the compounds are present and at what levels they may affect aquatic life). In practice, the answer typically involves two concepts: the predicted envi ronmental concentration (PEC) and the predicted no-effect concentration (PNEC).
Use of the watershed approach allows better understanding of the cumulative impact of human activities. PEC is based on the physical, chemical, and bi ological fate properties of the molecule, as well as hydrological information on STP effluent flows and surface-water flows. PNEC estimates concentrations at which potential effects on aquatic organisms and ecosystems might occur. In general, if PEC is less than PNEC (PEC/PNEC < 1), the environmental risk is deemed acceptable. This approach to envi ronmental risk assessment is called the risk char acterization ratio method. Where available, actual measured environmental concentrations should also be used in the assessment.
How are concentrations estimated? One approach for estimating environmental con centrations uses a simple averaging method. For this method, the total amount of the API introduced into a geographical area is estimated, and the average STP effluent flow data are used to calculate overall average concentration. Typical examples are pro vided in regulatory guidelines (11, 12). However, this simple averaging method discounts the consider able number and variability of factors affecting en vironmental concentrations, including the spatial scales—typically, local, regional, and continental— most appropriate for the assessment. At these large scales, multiple STPs usually con tribute to API concentrations in surface waters. De pending on the use of the final PECs, it may make sense to separately parameterize each individual STP for population, per capita waste flow, dilution, and removal (i.e., treatment type) and estimate a distribu tion of PECs. When a geographic area contains vari ous types of STPs with different removal efficiencies, overall removal can be weighted. However, the in creasing complexity of general averaging methods for calculating PECs that attempt to reflect the diversity of environments has led to the development of spa tially explicit models based on watersheds. (A water shed is a geographic area in which water, sediments, and dissolved materials drain to a common outlet.) 3458 n Environmental Science & Technology / june 1, 2006
Use of the watershed approach allows better un derstanding of the cumulative impact of human ac tivities. It is particularly useful with substances that enter the environment solely from human use, such as pharmaceuticals. Ideally, these models contain data on regional STPs and local assessments conducted on each plant. The output is then aggregated into tables and maps that can be used to predict local and regional concentrations at the appropriate resolution. These models rely on equations similar to those previously cited to predict environmental concen trations. These refined exposure-assessment tools should enhance the accuracy of current local and re gional exposure estimation methods and ultimately allow assessments on the scale of large areas. Two generally available GIS-based models are used for predicting PECs for pharmaceuticals in the environ ment: Pharmaceutical Assessment and Transport Evaluation (PhATE) for the U.S. (13) and GeographyReferenced Regional Exposure Assessment Tool for European Rivers (GREAT-ER) for Europe (14). PhATE uses a mass balance approach to model PECs. Input parameters include fractional removals of APIs due to metabolism, wastewater and drinkingwater treatment, and in-stream losses. Concentra tions in river segments are calculated from upstream and STP effluent contributions and losses arising from in‑stream mechanisms or flow diversions (e.g., human withdrawals). The model generates predicted concentrations at low and mean flows for STP efflu ents and surface waters. The current version of PhATE does not consider veterinary pharmaceuticals or septic-system discharges because these releases are through pathways other than an STP. PECs resulting from discharges into estuarine or marine environ ments are not predicted either. (PhATE is available upon consultation from
[email protected].) GREAT-ER is also a watershed (catchment) ap proach. Output is given as spatial distributions, with color-coded river maps that identify areas of high and low concentrations. The simulated concentra tions can be displayed as mean or other percentile values on the basis of the spatial and temporal dis tribution of river flows. Several weighting methods, including volume, length, and flow increments, are also used to calculate an overall catchment PEC. GREAT-ER has been applied to pharmaceuticals for several catchments across the EU (15). (GREAT-ER may be obtained from www.great-er.org.) These watershed models are generally easy to use. At a screening level, only the per capita use of API is required to estimate a PEC. When the user runs the model, the load is automatically distrib uted according to the populations served by each STP, removal is assumed to be zero, and the sur face water dilution is calculated from the specific wastewater and river flows for each STP. If a more refined assessment is required, PhATE and GREATER can include user-specified parameters, such as biodegradation rates and STP removal rates. One model for estimating STP removals is WW-Treat (16), which is similar to SimpleTreat (17), a non-equilib rium steady-state model that predicts the fate of new chemicals in a conventional STP from a minimal
How are effects on aquatic life estimated? Potential adverse aquatic effects in field popula tions are usually predicted from laboratory acute and chronic ecotoxicity data in species such as al gae, crustaceans, and fish (19). Because the primary mode of entry into the environment for most APIs is through STPs, the environmental risk assessment for the aquatic compartment is the first priority. If data are available that suggest that the compound is likely to resist degradation and highly sorb to sludges and sediments, then a terrestrial environmental risk assessment is also carried out. This allows the pre diction of the potential for the compound to impact terrestrial organisms as well as its potential impact to humans exposed to sludge-amended soil. Historically, the most common method of es timating the PNEC of an API in the aquatic en vironment has been to conduct a suite of tests to determine the acute effects concentration (EC50) or the lethal concentration (LC50) for 50% of the test organisms. Then, an assessment factor has been ap
FIGURE 1
Distribution of lowest acute EC50 or LC50 values for algae (n = 38), invertebrates (n = 67), and fish (n = 51) with human active pharmaceutical ingredients 60 % by organism class
data set. However, WW-Treat assumes that the total chemical, not just the dissolved fraction, is available for biodegradation. This modification is important for compounds that are biodegradable and highly sorbed to activated sludge; further details are pro vided elsewhere (18). Selection criteria for the most appropriate PEC or PECs to use in a risk assessment are still being determined. One method currently being evaluated uses the 90th percentile PEC from the probability distribution. Depending on the assessment, either low-flow or mean-flow conditions can be evaluated. In either case, the 90th percentile appears to be rea sonable to use because it considers the range of data points without bias from statistical outliers.
Algae
Invertebrates
Fish
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40
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EC50 or LC50 (mg/L)
plied to the lowest EC50 (or LC50, for the most sen sitive species). However, other techniques are now becoming available that may allow a better assess ment of the PNEC. We have recently reviewed the algal, invertebrate, and fish acute EC50 values for APIs that have been re ported in the peer-reviewed scientific literature (ref erences available in Supporting Information). For current purposes, the lowest EC50 data value from a standard regulatory test—measuring growth inhibi tion or mortality—was used to represent a conserva tive case. Figure 1 presents the results, and Table 1
TA B L E 1
APIs for which acute aquatic ecotoxicity data are available in the scientific literature Medical treatment
Compounds
Anti-infectives (including antibacte- acriflavine, aminosidine, amopyroquin, amoxicillin, azithromycin, bacitracin, clarithrorials, antifungals, antivirals, antipara- mycin, dirithromycin, erythromycin, famciclovir, flumequine, isoniazid, linocomycin, siticals and HIV-related treatments) lomefloxacin, merthiolate, metronidazole, nitrofurazone, ofloxacin, oxytetracycline, quinacrine, streptomycin, sulfadiazine, sulfamerazine, sulfamethazine, sulfamethoxazole, sulfisoxazole, tetracycline Analgesic and anti-inflammatory
acetaminophen (paracetamol), acetylsalicylic acid, budesonide, citalopram, diclofenac, ibuprofen, naproxen, prednisone, quinacrine, tramadol
Neuroscience
amobarbital, amphetamine, caffeine, diazepam, fluoxetine, fluvoxamine, nefazodone, paroxetine, pentobarbital, secobarbital, sertraline, thiopental
Cardiovascular
acebutolol, atenolol, captopril, carvedilol, clofibrate, clofibrinic acid, fenofibrate, losartan, metoprolol, nadolol, nisoldipine, perindopril erbumine, propranolol, verapamil
Gastrointestinal and metabolic
acarbose, cimetidine, famotidine, lansoprazole, metformin, quinine
Endocrine systems
17-ethinylestradiol, 17-estradiol, diethylstilbestrol, testosterone
Other
alendronate, bicalutamide, carbamazepine, chloramine T, cisapride, cyclosporine, dorzolamide, etidronic acid, finasteride, flutamide, gemfibrozil, iopromide, metaproterenol, methotrexate, nicotine, salicylic acid, tolazoline, warfarin
june 1, 2006 / Environmental Science & Technology n 3459
lists the APIs included in the data set along with the specific medical conditions they prevent or treat. The data in Figure 1 indicate that pharmaceu ticals, in general, do not exhibit high acute eco toxicity; that is, the vast majority do not produce lethal effects in aquatic life at concentrations 90% of the
The data in Figure 1 indicate that pharmaceuticals, in general, do not exhibit high acute ecotoxicity. compounds have lowest acute EC50 values of >1 mg/ L, whereas only 1% of the compounds have lowest acute EC50 values of 48,600) in fish (21). These large ACRs indicate that in some cases, acute values and traditional assessment factors are not protective of chronic effects. In contrast, ACRs in crustaceans, such as copepods and Daphnia magna, are also much lower for the mammalian estrogen receptor agonist 17-ethinylestradiol (10.2 and 16.4, respectively) (21). One reason for the limitation of this methodol ogy is that some ACR models have historically been developed with compounds whose primary mode of ecotoxicity is nonspecific narcosis (22). This type of toxicity is related to the chemical’s ability to parti tion into lipids and can be modeled with parame
TA B L E 2
Reference pharmaceuticals for ecotoxicology research based on the pharmacological mode of action Adapted from Ref. 21. API
Therapeutic class
API
Therapeutic class
Acetaminophen Acetylsalicylic acid Bleomycin Captopril Carbamazepine Clofibric acid Clotrimazole Cyclophosphamide Diazepam Diclofenac Enalapril Estradiol Ethynylestradiol Fadrozole Flutamide Fluoxetine Ibuprofen
Analgesic NSAID Cytotoxic anticancer ACE inhibitor Antiepileptic Lipid lowering P450 inhibitor Cytostatic Antiepileptic Analgesic ACE inhibitor Estrogen agonist Estrogen agonist Aromatase inhibitor Androgen antagonist SSRI NSAID
Ketoconazole Lovastatin Metformin Metoprolol Mevastatin Mevinolin Mitomycin C Nalidixic acid Naproxen Paracetamol Propranolol Quinidine Ranitidine Tamoxifen Taxol Trenbolone ZM189,154
P450 inhibitor Lipid-lowering Antidiabetic Beta-blocker (B1 receptor) Lipid-lowering Lipid-lowering Cytotoxic anticancer Fluoroquinolone NSAID Analgesic Beta-blocker (B2 receptor) Antiarrthymic Antiulcerant Estrogen antagonist Antineoplastic Androgen agonist Estrogen antagonist
ACE, angiotensin-converting enzyme; API, active pharmaceutical ingredient; NSAID, nonsteroidal anti-inflammatory drug; SSRI, selective serotonin reuptake i nhibitor.
3460 n Environmental Science & Technology / june 1, 2006
ters such as the octanol–water partition coefficient (log P). However, pharmaceuticals exert specific phar macological effects that may lead to particular toxicological effects not readily explained by sim ple relationships. Given these complexities, many scientists are developing mechanistic tools (e.g., hormone receptor biology) in order to understand patterns of chronic effects in different groups of aquatic organisms. This is likely to ultimately save resources and provide other benefits, such as re ducing animal experimentation. Indeed, many of the tools used in drug discovery, from comparative modeling of mammalian versus fish pharmacolo gy data to the molecular biology of regulatory test species like D. magna, may help us understand the potential impacts on fish and other aquatic life (23, 24). Currently, no single assessment factor appears to apply to all aquatic species across a wide diver sity of APIs. It is therefore critically important that scientists from academia, government, and industry work together to consider a mechanistic assessment of potential chronic impacts on aquatic life. A recent international workshop recommended using the compounds listed in Table 2 to build a knowledge base around ecotoxicity ACRs for key pharmaceuticals that represent specific mecha nisms of drug action (21).
Currently, no single assessment factor appears to apply to all aquatic species across a wide diversity of APIs. This mechanistic approach could then be used to guide efficient selection of chronic ecotoxicity test protocols to strengthen the science supporting ro bust PNEC values. In the near term, the improved exposure and chronic ecotoxicity approaches are likely to be used in a deterministic mode (i.e., one PEC compared with one PNEC). In the future, per forming probabilistic assessments (i.e., distributions of concentrations compared with distributions of ef fects) by combining watershed modeling approach es and mechanistic ecotoxicity studies will also be possible. In either case, if PEC/PNEC ≥ 1, then ad ditional fate and/or effects studies may be needed to refine the PEC and PNEC values.
What are the next steps? Incorporating chronic ecotoxicity testing of aquatic life into assessment strategies is the likely next step toward increased understanding of environmental effects. Scientists are improving the PhATE model and working to expand the applicability of GREATER. Information in the scientific literature is being evaluated and used as a tool to formulate research strategies. These will allow us to better understand impacts to aquatic life, leverage existing mamma
lian data, and move to more mechanistic risk as sessment techniques (25). More research is needed to increase our knowledge and understanding of the fate of drugs in surface waters, their products of degradation, the complex issues of mixtures, and the role of environmental monitoring. Finally, we must recognize the importance of communicat ing scientific data, which has a role in informing a broader audience of the environmental safety of medicines. This will require collaborations among industry, other researchers, regulators, physicians, and the public. Virginia L. Cunningham is an environmental physical organic chemist at GlaxoSmithKline. Mary Buzby is an environmental chemist at Merck. Thomas Hutchinson is an ecotoxicologist at AstraZeneca. Frank Mastrocco is a toxicologist at Pfizer. Neil Parke is an environmental biologist and chemist at Eli Lilly. Nicholas Roden is an ecotoxicologist at Schering-Plough. Address correspondence to Cunningham at virginia.l.cunningham@ gsk.com.
Acknowledgments
The authors gratefully acknowledge the diverse contribu tions from representatives of other research-based pharma ceutical companies in addition to those represented by the authors and from the staff of Pharmaceutical Research and Manufacturers of America (PhRMA). In addition, the signif icant contributions of AMEC Earth and Environmental, Inc., and Quantum Management Group, Inc., are recognized with appreciation.
References
(1) Ternes, T. A. Occurrence of Drugs in German Sewage Treatment Plants and Rivers. Water Res. 1998, 32, 3245– 3260. (2) Halling-Sorensen, B.; et al. Occurrence, Fate and Effects of Pharmaceutical Substances in the Environment—A Review. Chemosphere 1998, 36, 357–393. (3) Kolpin, D. W.; et al. Pharmaceuticals, Hormones, and Oth er Organic Wastewater Contaminants in U.S. Streams, 1999–2000: A National Reconnaissance. Environ. Sci. Technol. 2002, 36, 1202–1211. (4) Kümmerer, K., Ed. Pharmaceuticals in the Environment, 2nd ed.; Springer-Verlag: New York, 2004. (5) Williams, R. T., Ed. Human Pharmaceuticals: Assessing the Impacts on Aquatic Ecosystems; SETAC Press: Pen sacola, FL, 2005. (6) Boxall, A. B. A.; et al. Are Veterinary Medicines Caus ing Environmental Risks? Environ. Sci. Technol. 2003, 37, 287A–294A. (7) Velagaleti, R.; et al. Impact of Current Good Manufactur ing Practices and Emission Regulations and Guidances on the Discharge of Pharmaceutical Chemicals into the Environment from Manufacturing, Use and Disposal. Environ. Health Perspect. 2002, 110, 213–220. (8) Stackelberg, P. E.; et al. Persistence of Pharmaceutical Compounds and Other Organic Wastewater Contam inants in a Conventional Drinking-Water-Treatment Plant. Sci. Total Environ. 2004, 329, 99–113. (9) Jones, O. A.; Lester, J. N.; Voulvoulis, N. Pharmaceuticals: A Threat To Drinking Water? Trends Biotechnol. 2005, 23, 163–167. (10) Schwab, B. W.; et al. Human Pharmaceuticals in U.S. Sur face Water: A Human Health Risk Assessment. Regul. Toxicol. Pharmacol. 2005, 42, 296–312. (11) Guidance for Industry—Environmental Assessment of Human Drug and Biologics Applications, CMC6 Revision 1; FDA Center for Drug Evaluation and Research: Rockville, MD, 1998; www.fda.gov/cber/gdlns/environ.pdf. (12) Guideline on the Environmental Risk Assessment of Medicinal Products for Human Use, CMCP/SWP/4447/draft; European Agency for the Evaluation of Medicinal Prod june 1, 2006 / Environmental Science & Technology n 3461
(13) (14)
(15) (16) (17)
(18) (19)
ucts: London, 2005; www.emea.eu.int/pdfs/human/ swp/444700en.pdf. Anderson, P. D.; et al. Screening Analysis of Human Phar maceutical Compounds in U.S. Surface Waters. Environ. Sci. Technol. 2004, 38, 838–849. Feijtel, T. C. J.; et al. Development of a Geography-Refer enced Regional Exposure Assessment Tool for European Rivers—GREAT-ER. Contribution to GREAT-ER #1. Chemosphere 1997, 34, 2351–2373. Schowanek, D.; Webb, S. Exposure Simulation for Phar maceuticals in European Surface Waters with GREATER. Toxicol. Lett. 2002, 131, 39–50. Cowan, C. E.; et al. An Improved Model for Predicting the Fate of Consumer Product Chemicals in Wastewa ter Treatment Plants. Water Res. 1993, 27, 561–573. Struijs, J.; Stoltenkamp, J.; van de Meent, D. A Spread sheet-Based Box Model to Predict the Fate of Xenobiot ics in a Municipal Wastewater Treatment Plant. Water Res. 1991, 25, 891–900. Fent, K.; Weston, A. A.; Caminada, D. Ecotoxicology of Human Pharmaceuticals. Aquat. Toxicol. 2006, 76, 122– 159. Versteeg, D. J.; et al. Environmental Exposure Modeling and Monitoring of Human Pharmaceuticals in the Envi ronment. In Human Pharmaceuticals: Assessing the Impacts on Aquatic Ecosystems; Williams, R. T., Ed.; SETAC Press: Pensacola, FL, 2005; pp 71–110.
3462 n Environmental Science & Technology / june 1, 2006
(20) Hutchinson, T. H.; et al. Development of Fish Tests for Endocrine Disruptors. Pure Appl. Chem. 2003, 75, 2343– 2353. (21) Ankley, G. T.; et al. A Framework for Assessing the Haz ard of Pharmaceutical Materials to Aquatic Species. In Human Pharmaceuticals: Assessing the Impacts on Aquatic Ecosystems; Williams, R. T., Ed.; SETAC Press: Pensa cola, FL, 2005; pp 183–237. (22) Verhaar, H. J. M.; van Leeuwen, C. J.; Hermens, J. L. M. Classifying Environmental Pollutants. 1: Structure–Ac tivity Relationships for Prediction of Aquatic Toxicity. Chemosphere 1992, 25, 471–491. (23) Huggett, D. B.; et al. Theoretical Model for Utilizing Mammalian Pharmacology and Safety Data to Prior itize Potential Impacts of Human Pharmaceuticals to Fish. Hum. Ecol. Risk Assess. 2003, 9, 1789–1799. (24) Huggett, D. B.; et al. The Role of Mammalian Data in Determining Pharmaceutical Responses in Aquatic Spe cies. In Human Pharmaceuticals: Assessing the Impacts on Aquatic Ecosystems; Williams, R. T., Ed.; SETAC Press: Pensacola, FL, 2005; pp 149–181. (25) Hutchinson, T. H.; et al. Current Research Needs to Improve the Science Supporting the Environmental Stewardship of Human Pharmaceuticals. In Human Pharmaceuticals: Assessing the Impacts on Aquatic Ecosystems; Williams, R. T., Ed.; SETAC Press: Pensacola, FL, 2005; pp 303–311.
