Going All In: A Strategic Investment in In Silico Toxicology
Going All In: A Strategic Investment in In Silico Toxicology
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DOI：
10.1021/acs.chemrestox.9b00497
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发表时间：
2020-04-20
影响因子：
4.1
通讯作者：
Voutchkova-Kostal, Adelina
中科院分区：
文献类型：
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作者：
Kostal, Jakub;Voutchkova-Kostal, Adelina
由于每年都有大量的新化学品进入市场，我们面临着保护人类和环境的巨大挑战，同时最大限度地减少经济上和道德上代价高昂的动物试验。In silico模型有望成为我们所寻求的解决方案，但我们发现自己处于未来开发工作的十字路口，这将确保这些工具的独立适用性和可靠性。为了实现这一目标，需要进行认真的努力，优先考虑实验测试，以支持计算机模型的需求（相对于监管需求）。在本工作的标题中使用经济类比，我们认为谨慎的投资是全力支持硅模型开发，而不是通过保持测试方法的“平衡组合”的现状来赌我们的未来。我们讨论了未来硅毒理学的两条道路——一条基于大数据统计（“大刀”），另一条基于分子相互作用的直接建模（“手术刀”）——并提供了后一种方法更透明的理由，更符合我们对基础知识的追求，如果我们愿意改变我们的毒性测试范式，它就有更大的成功潜力。
As vast numbers of new chemicals are introduced to market annually, we are faced with the grand challenge of protecting humans and the environment while minimizing economically and ethically costly animal testing. In silico models promise to be the solution we seek, but we find ourselves at crossroads of future development efforts that would ensure standalone applicability and reliability of these tools. A conscientious effort that prioritizes experimental testing to support the needs of in silico models (versus regulatory needs) is called for to achieve this goal. Using economic analogy in the title of this work, we argue that a prudent investment is to go all-in to support in silico model development, rather than gamble our future by keeping the status quo of a "balanced portfolio" of testing approaches. We discuss two paths to future in silico toxicology-one based on big-data statistics ("broadsword"), and the other based on direct modeling of molecular interactions ("scalpel")-and offer rationale that the latter approach is more transparent, is better aligned with our quest for fundamental knowledge, and has a greater potential to succeed if we are willing to transform our toxicity-testing paradigm.