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首页> 外文期刊>Progress in drug research. >Toxicogenomics applied to predictive and exploratory toxicology for the safety assessment of new chemical entities: a long road with deep potholes.
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Toxicogenomics applied to predictive and exploratory toxicology for the safety assessment of new chemical entities: a long road with deep potholes.

机译:毒物基因组学应用于预测和探索性毒理学,以评估新化学实体的安全性:漫长而深坑的路。

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摘要

Toxicology is the perturbation of metabolism by external factors such as xenobiotics, environmental factors or drugs. As such, toxicology covers a broad range of fields from studies of the whole organism responses to minute biochemical events. Mechanistic toxicogenomics is an attempt to harness genomic tools to understand the physiological basis for a toxic event based on an analysis of transcriptional, translational or metabolomic profiles. These studies are complicated by non-toxic adaptive responses in transcript, protein or metabolite expression levels that have to be distinguished from those that are proximally related to the toxic event. Substantial progress has been made on the identification of biomarkers and the establishment of screens derived from such toxicogenomics studies. The ultimate goal, of course, is predictive toxicogenomics, which is an attempt to infer the likelihood of occurrence of a toxic event with exposure to a new agent based upon comparative responses with large databases of gene, protein or metabolite expression data. Gene expression databases are currently limited by the fact that measurable toxic phenotypes generally precede or at best coincide with the earliest observable changes in transcriptional profiles. Unfortunately, predictive protein databases have been limited by technical difficulties. Metabonomics-based databases, which would probably have the highest predictive value, are limited in turn by the inability to perform high dose studies in humans. This chapter will conclude by reviewing those elements of toxicogenomics that apply specifically to the development of anti-infectives and the potential for accurately modelling the toxicity of future drugs.
机译:毒理学是外来因素(例如异种生物,环境因素或药物)对新陈代谢的干扰。因此,毒理学涵盖了从整个生物体反应到微小生化事件的广泛领域。机械毒理基因组学是一种尝试,通过对转录,翻译或代谢组学谱的分析,利用基因组学工具了解毒性事件的生理基础。这些研究因转录本,蛋白质或代谢产物表达水平的无毒适应性反应而变得复杂,这些反应必须与与毒性事件近端相关的那些区别。在生物标志物的鉴定和从这种毒理基因组学研究衍生的筛选的建立方面已经取得了实质性进展。当然,最终目标是预测毒理基因组学,它是根据具有大量基因,蛋白质或代谢物表达数据数据库的比较响应来推断暴露于新药后发生毒性事件的可能性的尝试。目前,基因表达数据库受到以下事实的限制:可测量的毒性表型通常在转录谱中可观察到的最早变化之前或与之一致。不幸的是,预测性蛋白质数据库受到技术困难的限制。基于代谢组学的数据库可能具有最高的预测价值,但又由于无法在人体中进行高剂量研究而受到限制。本章将通过总结专门适用于抗感染药的毒理基因组学要素以及精确建模未来药物毒性的潜力来结束本章。

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