Algorithm of calculation of Predicted No-effect Concentration (PNEC) for evaluation of the environmental risk of veterinary medicinal products
2019
Viviana Ciuca | V. V. Safta | Romeo Teodor CRISTINA
The environmental risk analysis for veterinary medicinal products is an assessment of their possible evolution, exposures, and effects and is structured according to the VICH GL6 (Phase I) and GL38 (Phase II) guides. The environmental risk assessment, an integral part of the veterinary medicinal product authorizations, interpreted and harmonized under the VICH guidelines, ensures the predictability and transparency of the results obtained. The route of distribution and the evolution in the environment are important factors for the concentration of the final exposure. Predicted No-Effect Concentration (PNEC) is the concentration of a substance in an environment below which adverse effects will most likely not occur during a long term or short term exposure. In environmental risk assessment, PNECs will be compared to predicted environmental concentration (PEC) to determine if the risk of a substance is acceptable or not. If PEC/PNECs<1, the risk is acceptable. The PNECs are usually calculated by dividing toxicological dose descriptors by an assessment factor. The endpoints most frequently used for deriving PNECs are mortality (LC50), growth (ECx or NOEC) and reproduction (ECx or NOEC). PNECs need to be derived from various environmental compartments (water, sediment, soil, air, etc.). The paper presents an algorithm for calculating predictable no-effect concentrations (PNEC) for environmental factors: soil, water, sediment required for environmental risk assessment of veterinary medicinal products. Based on this calculation algorithm, specialized interactive software has been developed to allow rapid and convenient determination of predictable no-effect concentrations, PNEC, for environmental factors: soil, water, sediment for veterinary medicinal products. It is a very useful tool for environmental risk assessment specialists.
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