Research press release


Nature Communications

Biological sciences: Predicting chemical toxicity without animal testing


今回、Ruili Huangたちは、殺虫剤、工業用化学品、食品添加物、医薬品などの化合物の毒性を調べる方法の改良を目指すTox21プロジェクトの一環として、1万種以上の化学物質の試験を行った。具体的には、30種の標的(例えば、ヒト細胞の核内受容体や細胞経路)と相互作用する化学物質の濃度を15段階設定して、その活性を調べた。その結果、Huangたちは、5000万データポイントを生成し、化学物質の構造に関するデータを組み合わせて、化合物が動物や人間の健康に及ぼす悪影響を予測するために使用できると考えられる毒性モデルを作り出した。


Predictions of how toxic chemical compounds are to humans can be made using cell-based methods, without the need for animal testing, finds a study published in Nature Communications this week. This research presents cell-based toxicity models which may aid the development of alternatives to traditional animal testing in measuring compound toxicity.

Ruili Huang and colleagues test more than 10,000 chemicals as part of the Tox21 project that seeks to develop better methods of testing the toxicity of compounds such as pesticides, industrial chemicals, food additives and drugs. They test the activity of the chemicals in 15 different concentrations as they interact with 30 targets, such as nuclear receptors or cellular pathways in human cells. The authors thus generate more than 50 million data points, which they combine with data on the structure of the chemicals to create toxicity models that may be used to predict adverse health outcomes of the chemical compounds in animals or humans.

When these results are compared to toxicity data derived from animal testing or as a result of known exposure effects in humans, the authors find that their models are able to predict both human and animal toxicity. Although these results need to be further tested using additional pathways and targets, the authors propose that cell-based methods can be used in toxicological testing, and could help prioritize which compounds to select for more in-depth toxicological testing.

doi: 10.1038/ncomms10425

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