Predictive, integrative, and regulatory aspects of AI-driven computational toxicology - Highlights of the German Pharm-Tox Summit (GPTS) 2024.

Autor: Haßmann U; Toxlicon GmbH, Obwaldener Zeile 23, Berlin 12205, Germany. Electronic address: hassmann@toxlicon.com., Amann S; Toxlicon GmbH, Obwaldener Zeile 23, Berlin 12205, Germany., Babayan N; Toxometris.ai Inc., USA., Fankhauser S; Austrian Environment Ministry, Spittelauer Lände 5, Vienna 1090, Austria., Hofmaier T; Österreichische Agentur für Gesundheit und Ernährungssicherheit GmbH, Spargelfeldstraße 191, Wien 1220, Austria., Jakl T; Austrian Environment Ministry, Spittelauer Lände 5, Vienna 1090, Austria., Nendza M; Analytisches Laboratorium, Bahnhofstr. 1, Luhnstedt 24816, Germany., Stopper H; Institute of Pharmacology and Toxicology, University of Würzburg, Versbacher Str. 9, Würzburg 97078, Germany., Stefan SM; Medicinal Chemistry and Systems Pharmacology, Medical Systems Biology Division, Lübeck Institute of Experimental Dermatology (LIED), University Medical Center Schleswig-Holstein (UKSH), University of Lübeck (UzL), Ratzeburger Allee 160, Lübeck 23538, Germany; Department of Biopharmacy, Medical University of Lublin, Chodzki 4a, Lublin 20-093, Poland., Landsiedel R; BASF SE, Experimentelle Toxikologie und Ökologie, Carl-Bosch-Straße, Ludwigshafen am Rhein 67056, Germany.
Jazyk: angličtina
Zdroj: Toxicology [Toxicology] 2024 Dec; Vol. 509, pp. 153975. Date of Electronic Publication: 2024 Oct 18.
DOI: 10.1016/j.tox.2024.153975
Abstrakt: 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 from around the world to discuss cutting-edge developments in the fields of pharmacology and toxicology as well as scientific innovations and novel insights. A key focus of the conference was on the rapidly increasing role of computational toxicology, artificial intelligence (AI), and machine learning (ML) into the field, marking a shift away from traditional methods and allowing the reduction of animal testing as primary tool for toxicological risk assessment. Tools such as Toxometris.ai showcased the potential of AI-based risk assessments for predicting carcinogenicity, offering more ethical and efficient alternatives. Additionally, computer-driven models like computer-aided pattern analysis (C@PA) for drug toxicity prediction were presented, emphasizing the growing role of chem- and bioinformatic applications in computational sciences. Throughout the summit, there was a strong focus on the need for regulatory innovation to support the adoption of these advanced technologies and ensure the safety and sustainability of chemical substances and drugs.
Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2024 Elsevier B.V. All rights reserved.)
Databáze: MEDLINE
Externí odkaz: