Use of in silico and in vitro methods as a potential new approach methodologies (NAMs) for (photo)mutagenicity and phototoxicity risk assessment of agrochemicals

Chemical Space Networks Enhance Toxicity Recognition via Graph Embedding

Chemical space networks (CSNs) are a new effective strategy for detecting latent chemical patterns irrespective of defined coordinate systems based on molecular descriptors and fingerprints. CSNs can be a new powerful option as a new approach method and increase the capacity of assessing potential adverse impacts of chemicals on human health. Here, CSNs are shown to effectively characterize the toxicity of chemicals toward several human health end points, namely chromosomal aberrations, mutagenicity, carcinogenicity, developmental toxicity, skin irritation, estrogenicity, androgenicity, and hepatoxicity. In this work, we report how the content from CSNs structure can be embedded through graph neural networks into a metric space, which, for eight different toxicological human health end points, allows better discrimination of toxic and nontoxic chemicals. In fact, using embeddings returns, on average, an increase in predictive performances. In fact, embedding employment enhances the learning, leading to an increment of the classification performance of +12% in terms of the area under the ROC curve. Moreover, through a dedicated eXplainable Artificial Intelligence framework, a straight interpretation of results is provided through the detection of putative structural alerts related to a given toxicity. Hence, the proposed approach represents a step forward in the area of alternative methods and could lead to breakthrough innovations in the design of safer chemicals and drugs.

Perspectives on chick embryo models in developmental and reproductive toxicity screening

Teratology, the study of congenital anomalies and their causative factors intersects with developmental and reproductive toxicology, employing innovative methodologies. Evaluating the potential impacts of teratogens on fetal development and assessing human risk is an essential prerequisite in preclinical research. The chicken embryo model has emerged as a powerful tool for understanding human embryonic development due to its remarkable resemblance to humans. This model offers a unique platform for investigating the effects of substances on developing embryos, employing techniques such as ex ovo and in ovo assays, chorioallantoic membrane assays, and embryonic culture techniques. The advantages of chicken embryonic models include their accessibility, cost-effectiveness, and biological relevance to vertebrate development, enabling efficient screening of developmental toxicity. However, these models have limitations, such as the absence of a placenta and maternal metabolism, impacting the study of nutrient exchange and hormone regulation. Despite these limitations, understanding and mitigating the challenges posed by the absence of a placenta and maternal metabolism are critical for maximizing the utility of the chick embryo model in developmental toxicity testing. Indeed, the insights gained from utilizing these assays and their constraints can significantly contribute to our understanding of the developmental impacts of various agents. This review underscores the utilization of chicken embryonic models in developmental toxicity testing, highlighting their advantages and disadvantages by addressing the challenges posed by their physiological differences from mammalian systems.