While machine learning has gained traction in toxicological assessments, the limited data availability requires the quantification of uncertainty of in silico predictions for reliable decision-making. This study addresses the challenge of predicting ...
The pro-inflammatory responses in THP-1-derived macrophages and human bronchial epithelial cells (HBEC3-KT) were examined after exposure to size-fractioned particulate matter (PM) sampled in two road tunnels. All tunnel PM samples induced release and...
Drug-induced liver injury (DILI) toxicity is a condition when drugs have a destructive effect on the liver organ. The prediction of this toxicity becomes crucial in the drug development process to guarantee that drugs are safe from toxicity. Assessme...
Drug-induced autoimmunity (DIA) is a non-IgE immune-related adverse drug reaction that poses substantial challenges in predictive toxicology due to its idiosyncratic nature, complex pathogenesis, and diverse clinical manifestations. To address these ...
The growing prevalence of environmental pollutants has raised concerns about their potential role in thyroid dysfunction and related disorders. Previous research suggests that various chemicals, including plasticizers like acetyl tributyl citrate (AT...
The 9th German Pharm-Tox Summit (GPTS) and the 90th Annual Meeting of the German Society for Experimental and Clinical Pharmacology and Toxicology (DGPT) took place in Munich from March 13-15, 2024. The event brought together over 700 participants fr...
To underpin scientific evaluations of chemical risks, agencies such as the European Food Safety Authority (EFSA) heavily rely on the outcome of systematic reviews, which currently require extensive manual effort. One specific challenge constitutes th...
In the field of microplastics (MPs) toxicity prediction, machine learning (ML) computer simulation techniques are showing great potential. In this study, six ML algorithms were utilized to predict the toxicity of MPs on BEAS-2B cells based on quantit...
Methanol poisoning is a global public health concern, especially prevalent in developing nations. This study focuses on predicting the severity of methanol intoxication using machine learning techniques, aiming to improve early identification and pro...
The attempt to define toxicovigilance can be based on defining its fundamental principles: prevention of infections with toxic substances, collecting information on poisonings, both in terms of their sources and side effects, and confirming poisoning...