Toxicogenomics Technology for Predictive Toxicology and Safety Assessment | ||||
| Egyptian Society of Clinical Toxicology Journal | ||||
| Volume 12, Issue 2, December 2024, Page 1-13 PDF (772.17 K) | ||||
| Document Type: Review Article | ||||
| DOI: 10.21608/esctj.2024.305833.1065 | ||||
 View on SCiNiTO | ||||
| Author | ||||
Eman A. A. Abdallah  
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| Forensic Medicine and Toxicology, Faculty of Medicine, Zagazig University, Egypt. | ||||
| Abstract | ||||
| Background: To recognize and measure the worldwide changes in gene expression that are occurring in cells, new methods and technologies have been created as human genetics and genomics. Virtually all areas of biological study in the field of toxicology are being transformed by these new technologies, which are enabling researchers to improve their understanding of the function and control of genes at the systems level. Objective: The aim of toxicogenomics research is to uncover molecular patterns that can be utilized as biomarkers to anticipate toxicity or a person's vulnerability to it, as well as to clarify the molecular mechanisms underlying the expression of toxicity. There are many chemical compounds found in the environment with no toxicity data because the number of chemicals that can be analyzed by current toxicity testing techniques is restricted. Toxicogenomics, which study of the interaction between the genome, proteome, or metabolome and severe biological endpoints brought on by exposure to toxicants, offers a quick way to produce toxicity data for a lot of different substances. Additionally, toxicogenomic investigations can identify susceptibility and exposure biomarkers and provide a more accurate evaluation of the hazardous potential of an untested substance. To uncover and define the molecular processes that result in toxicity, toxicogenomics has evolved. Conclusion: This review focuses on recent studies in toxicogenomics and discusses the promises and future challenges in this field. | ||||
| Keywords | ||||
| Toxicogenomics; Genomics; Proteomic; Metabonomic; Bioinformatics | ||||
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