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The PhATE (Pharmaceutical Assessment and Transport Evaluation) model presented in this paper was developed as a tool to estimate concentrations of active pharmaceutical ingredients (APIs) in U.S. surface waters that result from patient use (or consumption) of medicines. PhATE uses a mass balance approach to model predicted environmental concentrations (PECs) in 11 watersheds selected to be representative of most hydrologic regions of the United States. The model divides rivers into discrete segments. It estimates the mass of API that enters a segment from upstream or from publicly owned treatment works (POTW) and is subsequently lost from the segment via in-stream loss mechanisms or flow diversions (i.e., man-made withdrawals). POTW discharge loads are estimated based on the population served, the API use per capita, the potential loss of the compound associated with human use (e.g., metabolism), and the portion of the API mass removed in the POTW. Simulations using three surrogate compounds showthat PECs generated by PhATE are generally within an order of magnitude of measured concentrations and that the cumulative probability distribution of PECs for all watersheds included in PhATE is consistent with the nationwide distribution of measured concentrations of the surrogate compounds. Model simulations for 11 APIs yielded four categories of results. (1) PECs fit measured data for two compounds. (2) PECs are below analytical method detection limits and thus are consistent with measured data for three compounds. (3) PECs are higher than (i.e., not consistent with) measured data for three compounds. However, this may be the consequence of as yet unidentified depletion mechanisms. (4) PECs are several orders of magnitude below some measured data but consistentwith most measured data forthree compounds. For the fourth category, closer examination of sampling locations suggests that the field-measured concentrations for these compounds do not accurately reflect human use. Overall, these results demonstrate that PhATE may be used to predict screening-level concentrations of APIs and related compounds in the environment as well as to evaluate the suitability of existing fate information for an API.

The pharmaceutical industry gives high priority to animal welfare in the process of drug discovery and safety assessment. In the context of environmental assessments of active pharmaceutical ingredients (APIs), existing U.S. Food and Drug Administration and draft European regulations may require testing of APIs for acute ecotoxicity to algae, daphnids, and fish (base-set ecotoxicity data used to derive the predicted no-effect concentration [PNECwater] from the most sensitive of three species). Subject to regulatory approval, it is proposed that testing can be moved from fish median lethal concentration (LC50) testing (typically using > or = 42 fish/API) to acute threshold tests using fewer fish (typically 10 fish/API). To support this strategy, we have collated base-set ecotoxicity data from regulatory studies of 91 APIs (names coded for commercial reasons). For 73 of the 91 APIs, the algal median effect concentration (EC50) and daphnid EC50 values were lower than or equal to the fish LC50 data. Thus, for approximately 80% of these APIs, algal and daphnid acute EC50 data could have been used in the absence of fish LC50 data to derive PNECwater values. For the other 18 APIs, use of an acute threshold test with a step-down factor of 3.2 is predicted to give comparable PNECwater outcomes. Based on this preliminary scenario of 91 APIs, this approach is predicted to reduce the total number of fish used from 3,822 to 1,025 (approximately 73%). The present study, although preliminary, suggests that the current regulatory requirement for fish LC50 data regarding APIs should be succeeded by fish acute threshold (step-down) test data, thereby achieving significant animal welfare benefits with no loss of data for PNECwater estimates.

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