尼文·纳雷因:我知道你经常报道航空业,你可能很熟悉航空公司的路线图了,它们展示了各个枢纽城市和目的地之间的联系。在我们的疑问型生物平台上,所有这些数据分析的结果看起来就像3D版的航空路线图。但这些联系并不是城市与城市之间的,而是基因与蛋白质之间。然后我们把重点放在那些大的枢纽上,看看是否出了什么问题。比如如果达拉斯市是在俄克拉荷马州境内,我们都知道肯定有问题,这时人工智能就会把达拉斯推回北德克萨斯州,然后分析生物学中的哪些事件可以让人体重启正常的流程。这就是我们的研究重点,即生物的基本元素,以及能让健康流程重启的基因和蛋白质。
Have you had any success using this platform in a real world situation?
在真实世界中,你利用该平台取得过成功吗?
NN: We are in clinical trials for a drug, BPM 31510, which we developed using the interrogative platform. The results we have seen so far have been very encouraging. The platform predicted that the more metabolic, the better the treatment will work. And that is exactly what we are seeing in patients for certain types of cancer. For example, we tested this on a patient who had bladder cancer. It was a very aggressive cancer, which failed to respond to all other therapies. We then put him on BPM 31510, which targeted the metabolism of the cancer cell, and by week 18, the tumor was completely gone.
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2020-09-15
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