实验动物们的救星

Toxicologists today unveiled a digital chemical safety screening tool that could greatly reduce the need for six common animal tests.

毒理学家今天揭示了一种数字化学安全筛选工具，它可以大大减少对六种常见动物试验的需求。

Those tests account for nearly 60% of the estimated 3 million to 4 million animals used annually in risk testing worldwide.

这些试验占到了如今全世界每年的安全风险测试所使用的三百万到四百万动物的60%。

The computerized tool—built on a massive database of molecular structures and existing safety data—appears to match, and sometimes improve on, the results of animal tests for properties such as skin sensitization and eye irritation, the researchers report in today’s issue of Toxicological Sciences.

这种计算机化的工具—建立在分子结构和现有安全数据的大规模数据库基础上—似乎可以匹敌甚至有时候胜过动物试验的结果，试验一般测试的是比如皮肤敏感性，眼部刺激性，研究员们在今天的《毒理科学》杂志最新一期上发表了结果。

But it also has limitations; for instance, the method can’t reliably evaluate a chemical’s risk of causing cancer.

不过它仍有局限性，比如，这种方法还不能可靠地评估化学致癌风险。

And it’s not clear how open regulatory agencies will be to adopting a nonanimal approach.

而且还不清楚管理机构是否会对采用这种非动物方法持开放态度。

Still, “We’re really excited about the potential of this model,” says toxicologist Nicole Kleinstreuer, deputy director of a center that evaluates alternatives to animal testing at the National Institute of Environmental Health Sciences (NIEHS) in Durham, North Carolina.

不过，“我们还是对这个模型的潜能感到兴奋异常，”毒理学家尼克.科伦斯卓尔说道，他是一个评估动物试验替代方法的中心的副局长，该中心属于北卡罗莱纳州达勒姆市的全国环境卫生学会。

Kleinstreuer, who was not involved in the work, adds that using “big data … to build predictive models is an extremely promising avenue for reducing and replacing animal testing.”

科伦斯卓尔，并未参与此次研究，他补充道“利用大数据...来建立可预测模型是一种非常有前景的方法，可以减少和替换动物试验。”

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