Lilly Research Laboratories, Indianapolis, IN, USA.
AstraZeneca, Drug Safety & Metabolism, Mölndal, Sweden.
Regul Toxicol Pharmacol. 2018 Jul;96:18-29. doi: 10.1016/j.yrtph.2018.04.011. Epub 2018 Apr 19.
Toxicogenomics held great promise as an approach to enable early detection of toxicities induced by xenobiotics; however, there remain questions regarding the impact of the discipline on pharmaceutical nonclinical safety assessment. To understand the current state of toxicogenomics in the sector, an industry group surveyed companies to determine the frequency of toxicogenomics use in in vivo studies at various stages of drug discovery and development and to assess how toxicogenomics use has evolved over time. Survey data were compiled during 2016 from thirteen pharmaceutical companies. Toxicogenomic analyses were infrequently conducted in the development phase and when performed were done to address specific mechanistic questions. Prior to development, toxicogenomics use was more frequent; however, there were significant differences in approaches among companies. Across all phases, gaining mechanistic insight was the most frequent reason cited for pursing toxicogenomics with few companies using toxicogenomics to predict toxicities. These data were consistent with the commentary submitted in response to survey questions asking companies to describe the evolution of their toxicogenomics strategy. Overall, these survey data indicate that toxicogenomics is not widely used as a predictive tool in the pharmaceutical industry but is used regularly by some companies and serves a broader role in mechanistic investigations and as a complement to other technologies.
毒理基因组学作为一种能够早期检测外源物诱导毒性的方法具有很大的应用前景;然而,关于毒理基因组学对药物非临床安全性评估的影响仍存在一些问题。为了了解毒理基因组学在该领域的现状,一个行业组织对多家公司进行了调查,以确定毒理基因组学在药物发现和开发的各个阶段的体内研究中的使用频率,并评估毒理基因组学的使用随时间的演变。调查数据于 2016 年由十三家制药公司汇编。毒理基因组学分析在开发阶段很少进行,当进行时,是为了解决特定的机制问题。在开发之前,毒理基因组学的使用更为频繁;然而,不同公司之间的方法存在显著差异。在所有阶段,获得机制见解是最常被引用的追求毒理基因组学的原因,很少有公司使用毒理基因组学来预测毒性。这些数据与对调查问题的回应中的评论一致,这些评论要求公司描述其毒理基因组学策略的演变。总体而言,这些调查数据表明,毒理基因组学在制药行业中并未广泛用作预测工具,但一些公司经常使用它,并在机制研究中发挥更广泛的作用,作为其他技术的补充。