Abstract:Environmental safety assessments, as mandated by many regulations, require that toxicity data is generated for up to three trophic levels, algae, aquatic invertebrates, and fish. Conducting these tests in vivo is resource-intensive, time-consuming, and causes undue suffering. Computational methods are fast and cost-efficient alternatives, however, their adaptation in regulatory settings has been slow, both due to low accuracy and narrow applicability domains. Here we present a new method for predicting chemica… Show more
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