The global search for a COVID-19 vaccine and treatment is on. Researchers are using every resource at their disposal to try and find a breakthrough against the killer virus. That includes artificial intelligence (AI).

全球正在寻找COVID-19疫苗和治疗方法。 研究人员正在利用所有可利用的资源来尝试找到针对杀手级病毒的突破。 其中包括人工智能 (AI)。

The tech has previously shown promise as a tool for drug development, but now researchers are putting it to the ultimate test — finding a drug that treats COVID-19 in record time. A Japanese startup called Elix is leading the charge thanks to deep learning software from Nvidia.

这项技术以前已经显示出有望作为药物开发的工具，但是现在研究人员将其用于最终测试 -找到在创纪录的时间内治疗COVID-19的药物。 得益于Nvidia的深度学习软件，一家名为Elix的日本初创企业领导了该项目。

大海捞针 (Needle in the Haystack)

Finding drug molecules to treat diseases used to be a task that took years. Now, sophisticated AI systems can significantly condense the process. Even so, the number of potential drug-like molecules out there is somewhere in the neighborhood of 1060.

寻找药物分子来治疗疾病曾经是一项耗时数年的任务。 现在，先进的AI系统可以大大简化流程。 即便如此，潜在的类药物分子的数量仍在1060附近。

Shinya Yuki, co-founder and CEO of Tokyo-based startup Elix, puts it in perspective by saying, “Even if you hypothetically checked one molecule per second, it would take longer than the age of the universe to explore the entire chemical space.”

东京初创公司Elix的联合创始人兼首席执行官Shinya Yuki 表示 ：“即使假设每秒检查一个分子，探索整个化学空间的时间也要比宇宙时代更长。 ”

He adds, “AI can efficiently explore huge search spaces to solve difficult problems, whether in drug discovery, materials development or a game like Go.”

他补充说：“人工智能可以有效地探索巨大的搜索空间，以解决难题，无论是在药物发现，材料开发还是在Go之类的游戏中。”

The game that Yuki references became popular in the AI space last year after Google’s AlphaGo algorithm forced Korean Go master Lee Se-dol into retirement, citing the fact that AI is unbeatable. Go has been around for more than 2,500 years and features a virtually unlimited number of moves.

在Google的AlphaGo算法迫使韩国围棋大师Lee Se-dol退役后，Yuki引用的游戏于去年在AI领域流行 ，理由是AI无与伦比。 Go已有2500多年的历史了，其动作几乎不受限制。

In a sense, it’s a lot like looking for one helpful drug molecule in an endless pile of useless ones. That’s why Yuki’s company is using AI to accelerate the process.

从某种意义上讲，这就像在无尽无用的一堆中寻找一种有用的药物分子。 这就是Yuki的公司使用AI加速流程的原因。

Elix uses deep learning to build neural networks that predict the properties of molecules far faster than traditional computer simulations. To speed up the process, the researchers are using molecules that are either in a clinical trial or have FDA approval. They want to find potential candidates that could be repurposed to treat the coronavirus.

Elix使用深度学习来构建神经网络，该神经网络比传统的计算机模拟要快得多地预测分子的特性。 为了加快这一过程，研究人员正在使用处于临床试验中或已获得FDA批准的分子。 他们希望找到可以重新用于治疗冠状病毒的潜在候选药物。

“Speed is critical, and drug-repurposing can help identify candidates with an existing clinical safety record, significantly reducing the time and cost of drug development,” says Yuki.

Yuki说：“速度至关重要，重新调整药物用途可以帮助确定具有现有临床安全记录的候选人，从而大大减少了药物开发的时间和成本。”

取得进展 (Making Progress)

Elix’s efforts are starting to pay off. The startup recently released a paper detailing the various drug molecules that its AI model flagged as potential COVID-19 treatments. Notably, an antiviral drug called remdesivir is on the list.

Elix的努力已开始见效。 这家初创公司最近发表了一篇论文，详细介绍了其AI模型标记为潜在COVID-19治疗的各种药物分子。 值得注意的是，一种名为remdesivir的抗病毒药物已列入名单。

The same drug recently gained FDA emergency use authorization to treat critically-ill coronavirus patients. Although remdesivir doesn’t cure COVID-19, clinical trials showed that it can decrease the time to recovery in some patients.

该药物最近获得了FDA紧急使用许可来治疗重症冠状病毒患者。 尽管瑞德昔韦不能治愈COVID-19，但临床试验表明，它可以减少某些患者的恢复时间。

Per the FDA, “The emergency use authorization allows for remdesivir to be distributed in the U.S. and administered intravenously by health care providers, as appropriate, to treat suspected or laboratory-confirmed COVID-19 in adults and children hospitalized with severe disease.”

根据FDA的规定 ，“紧急使用授权允许将remdesivir在美国分发，并由医疗保健提供者酌情静脉注射，以治疗可疑或经实验室确认的COVID-19，用于成年人和患有严重疾病的儿童。”

The fact that remdesivir is on the list generated by Elix’s AI is good news. For one, it somewhat confirms the results of earlier clinical trials and suggests that the drug might be effective. More importantly, however, it proves that the algorithm is on the right track. Since it flagged remdesivir, which is showing promising results, other drugs on the list might be effective as well.

remdesivir在由Elix的AI生成的列表中的事实是个好消息。 首先，它在某种程度上证实了早期临床试验的结果，并表明该药物可能有效。 然而，更重要的是，它证明了算法是正确的。 由于它标记了显示出有希望的结果的瑞德昔韦，因此清单上的其他药物也可能有效。

尖端技术 (Cutting Edge Tech)

The process which Elix uses to narrow down its drug selection is complex. It includes several layers of neural networks and predictive AI models. The first layer analyzes a database of drug molecules and determines which ones have the physical or chemical properties to treat COVID-19.

Elix用于缩小药物选择范围的过程很复杂。 它包括多层神经网络和预测AI模型。 第一层分析药物分子的数据库，并确定哪些分子具有治疗COVID-19的物理或化学特性。

Meanwhile, generative models start from scratch to create new molecular structures that might be promising. The issue with this, however, is that not all of the structures are found in nature. As such, a third neural network is needed. It is a retrosynthesis model that helps researchers determine if it’s even possible to synthesize the generated molecules.

同时，生成模型从头开始创建可能有希望的新分子结构。 然而，与此有关的问题是，并非所有结构都在自然界中发现。 这样，需要第三神经网络。 这是一个逆合成模型，可以帮助研究人员确定是否有可能合成生成的分子。

To accomplish this feat, Yuki and his team utilize multiple Nvidia DGX Station systems. These GPU-powered AI workstations allow neural networks to train up to six times faster than using a single GPU. That acceleration is vital to making the generative models a practical part of the research. Otherwise, it would take weeks for them to reach the lowest error rate possible.

为了实现这一壮举，Yuki和他的团队利用了多个Nvidia DGX Station系统。 这些GPU驱动的AI工作站使神经网络的训练速度比使用单个GPU快六倍。 加速对于使生成模型成为研究的实际部分至关重要。 否则，将需要数周的时间才能达到最低的错误率。

Each DGX station features four of Nvidia’s V100 Tensor Core GPUs. This allows the Elix team to run multiple experiments simultaneously and use larger AI models. It’s worth noting that Elix is a member of Nvidia Inception, a program that helps startups reach their market faster.

每个DGX工作站均配备四个Nvidia的V100 Tensor Core GPU。 这使Elix团队可以同时运行多个实验并使用更大的AI模型。 值得注意的是，Elix是Nvidia Inception的成员，该计划可帮助初创企业更快地进入其市场。

许多应用 (Many Applications)

Although it is currently focusing on identifying COVID-19 drugs, Elix isn’t shy about using AI. The startup also harnesses the technology’s power across several other applications, including molecular design for material informatics. Its client list includes noteworthy companies like Bridgestone and Riken.

尽管目前Elix致力于识别COVID-19药物，但Elix并不害羞于使用AI。 该初创公司还利用该技术在其他几个应用中的力量，包括用于材料信息学的分子设计。 它的客户包括像普利司通和理肯这样的著名公司。

Elix used a similar process to develop a new molecule for the global chemical company Nippon Shokubai. Together, the duo created a molecule that helps blend ink without posing a high risk for skin irritation.

Elix用类似的方法为全球化学公司Nippon Shokubai开发了一种新分子。 两人共同创造了一种分子，可帮助混合墨水，而不会引起皮肤刺激的高风险。

Meanwhile, Elix also develops computer vision models for self-driving car applications.

同时，Elix还开发了用于自动驾驶汽车应用的计算机视觉模型。

只是开始 (Just the Beginning)

As mentioned, drug research is an extremely inefficient task when done manually. That makes it a golden application for artificial intelligence. This isn’t the first time that it has been used.

如前所述，药物研究如果手动完成，则效率极低。 这使其成为人工智能的黄金应用。 这不是第一次使用它。

Last July, an Australian AI system developed the first computer-generated human drug. It was an add-on that aims to boost the efficiency of traditional flu vaccines.

去年7月，澳大利亚的AI系统开发了第一种计算机生成的人类药物 。 这是一个旨在提高传统流感疫苗效率的附件。

Meanwhile, a newly developed AI drug known as DSP-1181 entered the human trial phase earlier this year. The drug, discovered by Exscientia, is being developed to treat obsessive-compulsive disorder (OCD). At the time, the team behind the drug said, “This year was the first to have an AI-designed drug but by the end of the decade all new drugs could potentially be created by AI.”

同时，一种名为DSP-1181的新开发的AI药物已于今年年初进入人体试验阶段 。 Exscientia发现的这种药物正在研发中，用于治疗强迫症(OCD)。 当时，该药物背后的团队说：“今年是第一款采用AI设计的药物，但到本世纪末，所有新药物都可能由AI产生。”

Thanks to AI-focused applications like Elix’s, humanity could be closer than ever to finding a viable treatment for COVID-19. With little time to waste, artificial intelligence is a valuable ally in the fight against the virus.

多亏了像Elix's这样的以AI为重点的应用，人类才能比以往更接近找到可行的COVID-19疗法。 很少浪费时间，人工智能是对抗病毒的宝贵盟友。

Originally published at https://www.theburnin.com on July 10, 2020.

最初于 2020年7月10日 发布在 https://www.theburnin.com 。