生成式人工智能在可持续毒理学中的应用、益处和挑战综述

IF 2.9 Q2 TOXICOLOGY
Furqan Alam , Tahani Saleh Mohammed Alnazzawi , Rashid Mehmood , Ahmed Al-maghthawi
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引用次数: 0

摘要

可持续毒理学对生物物种和环境至关重要,因为它保证了药物、治疗、疫苗和化学物质在生物和环境中的安全性、有效性和法规遵从性。传统的毒理学方法往往缺乏可持续性,因为它们昂贵,耗时,有时不准确。这意味着新药、疫苗和治疗方法的生产延迟,以及对化学物质对环境的不利影响的了解延迟。为了应对这些挑战,医疗保健部门必须利用生成人工智能(GenAI)范式的力量。本文旨在通过使用GenAI促进可持续毒理学发展,帮助了解医疗保健领域如何以多种方式进行革命。本文首先回顾了目前的文献,并确定了可以应用于毒理学的GenAI的可能分类。由GenAI提供的各种毒理学过程的广义和整体可视化是串联提出的。本文讨论了毒理学风险评估和管理,重点介绍了全球机构和组织如何制定政策来规范和规范这些领域的人工智能相关发展,例如GenAI。本文对GenAI在毒理学研究中的优势和挑战进行了探讨。此外,该论文还概述了GenAI如何增强对话ai,这对于高度定制的毒理学解决方案至关重要。本文综述将有助于全面了解GenAI在毒理学领域的影响和未来潜力。所获得的知识可用于创建可持续的GenAI应用程序,以解决毒理学中的各种问题,最终使我们的社会和环境受益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A Review of the Applications, Benefits, and Challenges of Generative AI for Sustainable Toxicology

A Review of the Applications, Benefits, and Challenges of Generative AI for Sustainable Toxicology
Sustainable toxicology is vital for living species and the environment because it guarantees the safety, efficacy, and regulatory compliance of drugs, treatments, vaccines, and chemicals in living organisms and the environment. Conventional toxicological methods often lack sustainability as they are costly, time-consuming, and sometimes inaccurate. It means delays in producing new drugs, vaccines, and treatments and understanding the adverse effects of the chemicals on the environment. To address these challenges, the healthcare sector must leverage the power of the Generative-AI (GenAI) paradigm. This paper aims to help understand how the healthcare field can be revolutionized in multiple ways by using GenAI to facilitate sustainable toxicological developments. This paper first reviews the present literature and identifies the possible classes of GenAI that can be applied to toxicology. A generalized and holistic visualization of various toxicological processes powered by GenAI is presented in tandem. The paper discussed toxicological risk assessment and management, spotlighting how global agencies and organizations are forming policies to standardize and regulate AI-related development, such as GenAI, in these fields. The paper identifies and discusses the advantages and challenges of GenAI in toxicology. Further, the paper outlines how GenAI empowers Conversational-AI, which will be critical for highly tailored toxicological solutions. This review will help to develop a comprehensive understanding of the impacts and future potential of GenAI in the field of toxicology. The knowledge gained can be applied to create sustainable GenAI applications for various problems in toxicology, ultimately benefiting our societies and the environment.
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来源期刊
Current Research in Toxicology
Current Research in Toxicology Environmental Science-Health, Toxicology and Mutagenesis
CiteScore
4.70
自引率
3.00%
发文量
33
审稿时长
82 days
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