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Computational toxicology, friend or foe?

机译:计算毒理学,是敌还是友?

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摘要

There is increasing public pressure to reduce animal testing and yet maintain public safety from exposure to chemicals either in the environment we live in, the food that we eat or the drugs that we take to treat illnesses. Computational approaches offer the attraction of being both fast and cheap to run being able to process thousands of chemical structures in a few minutes. As a result these approaches have seen an increase in interest and effort over the last decade most notably in the pharmaceutical industry where costs for new drug development is soaring and the failure rate for safety reasons is high. Many applications and approaches have been published covering a wide variety of different human and environmental health issues. As with all new technology, there is a tendency for these approaches to be hyped up and claims of reliability and performance may be exaggerated. So just how good are these computational methods? This review is intended to provide an overview of the state of the art in computational toxicology and to illustrate where some of the limitations of these approaches exist so that these valuable tools are applied and interpreted correctly.
机译:越来越多的公众压力要求减少动物试验,并保持公共安全,避免在我们所居住的环境,所吃的食物或为治疗疾病而服用的药物中接触化学物质。计算方法提供了既快速又廉价的吸引力,使其能够在几分钟内处理成千上万的化学结构。结果,在过去的十年中,这些方法引起了人们的兴趣和努力的增加,特别是在制药行业中,在该行业中,新药开发的成本飞涨,并且出于安全原因的失败率很高。已经发布了涉及广泛的不同人类和环境健康问题的许多应用程序和方法。与所有新技术一样,这些方法有被大肆宣传的趋势,并且可靠性和性能的主张可能会被夸大。那么这些计算方法到底有多好?这篇综述旨在提供计算机毒理学最新技术的概述,并举例说明这些方法的某些局限性存在于何处,以便正确应用和解释这些有价值的工具。

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