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VETERINARY MEDICINES AND THE ENVIRONMENT

2005· article· en· W4237366570 on OpenAlexaboutno aff
Alistair B.A. Boxall, Carol Long

Bibliographic record

VenueEnvironmental Toxicology and Chemistry · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicPesticide and Herbicide Environmental Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessLivestockEuropean unionAnimal welfareAgricultureSustainabilityProduct (mathematics)Animal healthVeterinary DrugsBiotechnologyEnvironmental planningEnvironmental protectionMedicineEnvironmental healthVeterinary medicineGeographyBiologyInternational trade

Abstract

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The development over the past 40 years of diverse new and modern veterinary medicines has enabled the veterinary profession to safeguard the health and welfare of livestock and companion and wild animals. These medicines also play an important role in the agricultural economy, sustainability, and production of more affordable, good-quality food for the consumer. In addition, veterinary medicines and the protection of public health are mutually dependent. During their use, however, veterinary medicines and their metabolites can be released to the environment either directly, when used as aqua-culture or pasture animal treatments, or indirectly, during the application of manure and slurry to land as a fertilizer. Like other substances, such as human medicines and plant protection products, animal health products undergo years of research and numerous trials to ensure their quality, safety, and efficacy. Before an animal health product is allowed to enter the market, it must be registered via a lengthy and complex process. In many regions, such as the United States, Europe, and Canada, an environmental assessment is now a key component of that process [1]. In the United States, environmental assessments have been required since the 1980s; in the European Union, assessments have been required from the 1990s. Over the years, a number of assessment guidelines have been developed [2], and the data from the assessments are becoming increasingly available to the scientific community. In the United States, for example, most assessments can be downloaded from the U.S. Food and Drug Administration Web site (www.fda.gov/cvm/efoi/ea/ea.htm). At the international scale, the Veterinary International Cooperation on Harmonisation in Brussels, Belgium, is currently working to harmonize the approaches for environmental risk assessment. They propose a two-phase approach. In Phase 1, the likelihood for environmental exposure is assessed [3], and for those substances moving on to Phase 2, the risks of a substance are determined by environmental fate (e.g., sorption and persistence in soils) and effects data (e.g., toxicity to fish, daphnids, algae, plants, microbes, and earthworms). Guidelines are already available for Phase 1, and Phase 2 guidelines should be finalized by the end of this year. Further details can be found at www.vich.eudra.org/htm/guidelines.htm. A number of recent monitoring studies have detected veterinary medicines in manure, soils, surface waters, and sediments [4]; generally, these data support the results of regulatory assessments that indicate exposure concentrations are well below effect concentrations from standard ecotoxicity studies. However, veterinary products contain biologically active substances that standard tests might not detect after long-term, low-level exposure. For example, sublethal effects have been reported on a range of organisms, including invertebrates and microbes at concentrations much lower than standard acute test concentrations. Certain substances can cause indirect effects on predatory species [5-8]. Studies have highlighted the potential effects of metabolites and degradation products, the effects of mixtures of substances, and the potential for environmental exposure contributing to the development of antibacterial-resistant microbes. Finally, researchers are questioning the suitability of many of the tools used to assess exposure. Veterinary medicines are often large, polar, multifunctional molecules that usually pass through an animal before being excreted and typically are released into the environment in feces. The factors affecting behavior in the environment could therefore be very different from those for other substances, such as pesticides and industrial compounds. For example, the sorption behavior of many veterinary medicines is different from that of neutral organic substances [e.g., 9]. Although a wealth of data are now available in the public domain on the behavior and effects of veterinary medicines in the environment, and the science continues to advance, much remains to be done. Numerous researchers across the world are studying the interactions of veterinary medicines with the environment, and it is timely to draw together the results of much of this work. Thus, in this issue of Environmental Toxicology and Chemistry, we have brought together a number of papers from Australia, North America, and Europe describing the behavior of veterinary medicines in the environment, their effect on aquatic and terrestrial organisms, and possible approaches for better assessing their environmental impacts in the future. We hope that this edition will encourage readers to apply their knowledge to understanding and contributing to the ongoing debate over the effects of veterinary medicines on the environment and to the development of regulatory guidelines that are based on sound science. These regulations are critical to establishing and maintaining consumer confidence in the safety, quality, and efficacy of products used in the animal health industry. We thank Dana Kolpin (U.S. Geological Survey), Jose Tarazona (INIA, Spain), and Hans Hoogland (Agency for Registration of Veterinary Medicinal Products, The Netherlands) for their help in bringing together the papers contained in this issue. We are also grateful to Susanne Zanker (IFAH) for her input to this editorial.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.068
Threshold uncertainty score0.227

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.003
Scholarly communication0.0080.004
Open science0.0010.006
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0680.013

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.201
Teacher spread0.195 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2005
Admission routes1
Has abstractyes

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