About this Research Topic

Background

An unprecedented increase in the number of synthesized chemicals has created a significant hurdle to rapidly screen and accurately assess their potential adverse biological effects, mainly due to the enormous costs and lengthy time-consuming nature of in vivo and in vitro toxicity testing. Conversely, in silico predictive toxicology techniques offer a swift and cost-efficient alternative or supplement to in vivo/in vitro testing for predicting the toxicity of chemical compounds. As a result, in silico toxicology plays a vital role in estimating the safety/toxicity of chemicals, as well as in the drug discovery and development process. Consequently, the capability and applicability of in silico approaches in predicting safety/toxicity continue to increase.

The aim of this Research Topic is to focus on the most recent scientific contributions regarding various aspects of computational approaches used to predict safety/toxicity and prioritize chemicals and drugs in order to minimize adverse effects. Authors are welcome to submit the following article types: General Commentary, Hypothesis and Theory, Methods, Mini Review, Opinion, Original Research, Perspective, and Review, which cover, but are not limited to, the following themes:

• Various in silico techniques, including traditional and machine learning/artificial intelligence-based approaches
• Various safety/toxicity endpoints of chemicals/drugs
• Applications of novel machine learning/artificial intelligence techniques, such as ChatGPT, for computationally assessing toxicity or elucidating toxic mechanisms
• Implementation of novel programming languages, such as "mojo," for computational toxicity
• Novel packages/strategies that can be utilized to predict toxicity
• Other related issues

Keywords: In silico, Predictive Toxicology, Endpoints, Safety/toxicity, Molecular modeling, Machine learning/Artificial intelligence

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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