Editorial: Advances in and applications of predictive toxicology: 2022

Abstract

While the first use of the term "Predictive Toxicology" was mainly focusing on in silico approaches and applied almost synonymously to computational toxicology (Helma, 2005) it has later been extended to describe models and assays complementary or as replacement to the classical descriptive in vivo toxicology (Dearden, 2015). Consequently, FDA's Predictive Toxicology roadmap published in 2017 lists "new methodologies and technologies to expand FDA's toxicology predictive capabilities and to potentially reduce the use of animal testing" (FDA, 2017). In December 2022 the FDA Modernization Act 2.0 was passed into US law removing the need for animal testing for every new drug development protocol. Together these regulatory changes offer the possibility of replacing animal testing in drug development with suitably validated Predictive Toxicology methods.Currently, Predictive Toxicology uses and integrates in silico, in chemico and in vitro approaches named "New Approach Methodologies (NAMs)" to predict the potential toxic effects of a chemical or drug on living organisms including humans, as well as to assess the safety and potential risks associated with exposure to chemicals, drugs, environmental pollutants, and other substances. Predictive Toxicology forms the backbone of the chemical next-generation risk assessment (NGRA), which integrates NAMs to assure human safety without animal testing (Alexander-White et al., 2022).The main areas delivering contributions to Predictive Toxicology with probably the greatest recent advancements are micro-physiological systems (MPS) (Roth, 2021), sometimes also termed as advanced cellular models (Pineiro-Llanes et al., 2023), new approaches in data science including analysis of omics data and systems toxicology (Steger-Hartmann et al., 2023), as well as physiologically based pharmacokinetic/toxicokinetic modeling and simulation. The progress in these areas is also illustrated through the manuscripts submitted to this Research Topic of Frontiers in Toxicology:Cairns et al. present an important milestone in implementing MPS in efficient toxicity testing of drugs. The study describes the development and the implementation

Metabolites in the regulatory risk assessment of pesticides in the EU

“…Currently used approaches such as QSAR systems are considered not yet sufficiently reliable but would provide additional useful information for regulatory work. Especially in the drug development field, in silico tools are being extensively used and could provide useful examples for pesticides toxicokinetics work (e.g., Fagerholm, 2007;Najjar et al, 2023;Rai et al, 2023), but their validity to predict metabolism data in a regulatory setting is so far considered limited.…”

Next generation risk assessment: an ab initio case study to assess the systemic safety of the cosmetic ingredient, benzyl salicylate, after dermal exposure

“…Since the seventh revision ( EU, 2003 ) of the European Directive 76/768/EEC ( EU, 2009 ) was published 20 years ago banning the use of animal studies due to ethical reasons, the cosmetics industry has been a major contributor for the development of new approach methodologies (NAMs). Therefore, next-generation risk assessments (NGRAs) of cosmetic ingredients are based on the strategic use of non-animal methods only, i.e., in vitro , in silico , and in chemico data, in an exposure-led and hypothesis-driven approach to deliver human-relevant safety decisions ( Najjar et al, 2023 ). The acceptance of this requires the demonstration of its consumer-protective application in the form of hypothetical case studies using NGRA principles ( Dent et al, 2018 ).…”