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...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-01-01
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| Series: | Current Research in Toxicology |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666027X25000180 |
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| author | Furqan Alam Tahani Saleh Mohammed Alnazzawi Rashid Mehmood Ahmed Al-maghthawi |
| author_facet | Furqan Alam Tahani Saleh Mohammed Alnazzawi Rashid Mehmood Ahmed Al-maghthawi |
| author_sort | Furqan Alam |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-39b8bbf3c1374dd1b202e7ffc5b54428 |
| institution | Kabale University |
| issn | 2666-027X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Current Research in Toxicology |
| spelling | doaj-art-39b8bbf3c1374dd1b202e7ffc5b544282025-08-20T03:24:36ZengElsevierCurrent Research in Toxicology2666-027X2025-01-01810023210.1016/j.crtox.2025.100232A Review of the Applications, Benefits, and Challenges of Generative AI for Sustainable ToxicologyFurqan Alam0Tahani Saleh Mohammed Alnazzawi1Rashid Mehmood2Ahmed Al-maghthawi3Faculty of Computing and Information Technology (FoCIT), Sohar University, Sohar 311, Oman; Corresponding author.Department of Computer Science, College of Computer Science and Engineering, Taibah University, Madinah 41477, Kingdom of Saudi ArabiaFaculty of Computer Science and Information Systems, Islamic University Madinah, Madinah 42351, Kingdom of Saudi ArabiaDepartment of Computer Science, College of Science & Art at Mahayil, King Khalid University, Abha 62529, Kingdom of Saudi ArabiaSustainable 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.http://www.sciencedirect.com/science/article/pii/S2666027X25000180Generative AI (GenAI)Artificial IntelligenceToxicologyDrug DiscoveryConversational-AIToxicity Prediction |
| spellingShingle | Furqan Alam Tahani Saleh Mohammed Alnazzawi Rashid Mehmood Ahmed Al-maghthawi A Review of the Applications, Benefits, and Challenges of Generative AI for Sustainable Toxicology Current Research in Toxicology Generative AI (GenAI) Artificial Intelligence Toxicology Drug Discovery Conversational-AI Toxicity Prediction |
| title | A Review of the Applications, Benefits, and Challenges of Generative AI for Sustainable Toxicology |
| title_full | A Review of the Applications, Benefits, and Challenges of Generative AI for Sustainable Toxicology |
| title_fullStr | A Review of the Applications, Benefits, and Challenges of Generative AI for Sustainable Toxicology |
| title_full_unstemmed | A Review of the Applications, Benefits, and Challenges of Generative AI for Sustainable Toxicology |
| title_short | A Review of the Applications, Benefits, and Challenges of Generative AI for Sustainable Toxicology |
| title_sort | review of the applications benefits and challenges of generative ai for sustainable toxicology |
| topic | Generative AI (GenAI) Artificial Intelligence Toxicology Drug Discovery Conversational-AI Toxicity Prediction |
| url | http://www.sciencedirect.com/science/article/pii/S2666027X25000180 |
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