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Prioritization of pharmaceuticals for potential environmental hazard through leveraging a large scale mammalian pharmacological dataset
Citation:
Berninger, J., C. LaLone, Dan Villeneuve, AND G. Ankley. Prioritization of pharmaceuticals for potential environmental hazard through leveraging a large scale mammalian pharmacological dataset. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, 35(4):1007-1020, (2015).
Impact/Purpose:
There is a critical need to integrate exposure and toxicokinetic considerations with AOP knowledge to support risk assessments related to chemicals in the environment. A relatively unique, practical opportunity through which to approach this challenge involves assessing potential impacts of human and veterinary pharmaceuticals in aquatic environments. Aquatic organisms can be exposed to pharmaceuticals entering the environment, for example through human wastewater streams or via run off from livestock operations. Little information exists concerning the uptake, fate, and effects of these compounds in aquatic plants, vertebrates, and/or invertebrate species and it is impractical to conduct extensive toxicity testing, particularly for chronic and sub-lethal endpoints, for hundreds to thousands of pharmaceuticals that can occur in the aquatic environment. However, substantial information is available concerning pharmacokinetics (adsorption, distribution, metabolism, and elimination; ADME) and effects in therapeutic target species (e.g., humans, pest, livestock). Theoretically, through understanding of pathway conservation, these data collected largely in mammalian models, can be leveraged to aid prediction of potential risks to aquatic species and prioritize chemicals based on those with properties most likely to be problematic (e.g., those that are readily taken up and very slowly cleared from organisms). The present paper, reports on compilation of a large database of ADME data for pharmaceuticals and discusses how these data may be applied to aid prioritization of which pharmaceuticals may pose the greatest concern in the aquatic environment. Results contribute directly to two tasks within the Adverse Outcome Pathway Discovery and Development project of the CSS research program and should be a great resource to any program offices evaluating risks associated with pharmaceuticals in the environment as well as the broader scientific community.
Description:
To proceed in the investigation of potential effects of thousands of active pharmaceutical ingredients (API) which may enter the aquatic environment, a cohesive research strategy, specifically a prioritization is paramount. API are biologically active, with specific physiological targets, suggesting that models built solely on physical-chemical properties and exposure potential cannot be adequate for prioritization. Given the concomitant lack of available aquatic species data, the best available source for prioritization was the data generated during the extensive mammalian drug development process. Using the concept of read-across, mammalian pharmacokinetic data was utilized to prioritize API for the purposes of understanding potential biological consequences in the aquatic environment. The most commonly available ADME (absorption, distribution, metabolism, excretion) parameters (including: peak plasma concentration, apparent volume of distribution, clearance rate, half life) were collected and currated for 1070 API. Using these data a probabilistic model and scoring system were developed to prioritization score for each API across all four parameters and a final prioritization score across all parameters. Probabilistic models and the database strategy allow for the prioritization of API even when data are missing or the API is unknown. This ability to move beyond the available data to develop prioritizations and generate hypotheses provides makes this approach unique among available prioritization efforts.
