Lynch Caitlin, Sakamuru Srilatha, Ooka Masato, Huang Ruili, Klumpp-Thomas Carleen, Shinn Paul, Gerhold David, Rossoshek Anna, Michael Sam, Casey Warren, Santillo Michael F, Fitzpatrick Suzanne, Thomas Russell S, Simeonov Anton, Xia Menghang
National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, Maryland, USA; email:
Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina, USA.
Annu Rev Pharmacol Toxicol. 2024 Jan 23;64:191-209. doi: 10.1146/annurev-pharmtox-112122-104310. Epub 2023 Jul 28.
Traditionally, chemical toxicity is determined by in vivo animal studies, which are low throughput, expensive, and sometimes fail to predict compound toxicity in humans. Due to the increasing number of chemicals in use and the high rate of drug candidate failure due to toxicity, it is imperative to develop in vitro, high-throughput screening methods to determine toxicity. The Tox21 program, a unique research consortium of federal public health agencies, was established to address and identify toxicity concerns in a high-throughput, concentration-responsive manner using a battery of in vitro assays. In this article, we review the advancements in high-throughput robotic screening methodology and informatics processes to enable the generation of toxicological data, and their impact on the field; further, we discuss the future of assessing environmental toxicity utilizing efficient and scalable methods that better represent the corresponding biological and toxicodynamic processes in humans.
传统上,化学毒性是通过体内动物研究来确定的,这种方法通量低、成本高,而且有时无法预测化合物对人类的毒性。由于使用的化学物质数量不断增加,以及候选药物因毒性而失败的比例很高,因此开发体外高通量筛选方法来确定毒性势在必行。Tox21计划是一个由联邦公共卫生机构组成的独特研究联盟,旨在通过一系列体外试验,以高通量、浓度响应的方式解决和识别毒性问题。在本文中,我们回顾了高通量机器人筛选方法和信息学过程的进展,这些进展能够生成毒理学数据及其对该领域的影响;此外,我们还讨论了利用高效且可扩展的方法评估环境毒性的未来发展方向,这些方法能更好地反映人类相应的生物学和毒理学过程。