My family loves to do jigsaw puzzles. It’s one of our favorite activities to do together, especially when we’re on vacation. There is something so satisfying about everyone working as a team to put down piece after piece until finally the whole thing is done.
我的家人喜欢做拼图游戏。这是我们最喜欢一起做的活动之一，尤其是在度假时。当我们全家像一个团队一样，把一块接一块的图片拼起来，直到最后完成整幅拼图，这会让我们感到非常满足。
In a lot of ways, the fight against Alzheimer’s disease reminds me of doing a puzzle. Your goal is to see the whole picture, so that you can understand the disease well enough to better diagnose and treat it. But in order to see the complete picture, you need to figure out how all of the pieces fit together.
在许多方面，与阿尔茨海默病的斗争会让我想起拼图。你的目标是看到整个画面，从而可以充分理解这种疾病，以便更好地诊断和治疗它。但为了看到完整的画面，你需要弄清楚所有碎片该如何组合在一起。
Right now, all over the world, researchers are collecting data about Alzheimer’s disease. Some of these scientists are working on drug trials aimed at finding a way to stop the disease’s progression. Others are studying how our brain works, or how it changes as we age. In each case, they’re learning new things about the disease.
目前，全世界的研究人员正在收集有关阿尔茨海默病的数据。其中一些科学家正在进行药物试验，旨在找到一种方法来阻止疾病的发展。其他科学家正在研究我们的大脑是如何工作的，或者随着年龄的增长它会如何变化。在各个情况下，他们都在学习与该疾病有关的新知识。
But until recently, Alzheimer’s researchers often had to jump through a lot of hoops to share their data—to see if and how the puzzle pieces fit together. There are a few reasons for this. For one thing, there is a lot of confusion about what information you can and can’t share because of patient privacy. Often there weren’t easily available tools and technologies to facilitate broad data-sharing and access. In addition, pharmaceutical companies invest a lot of money into clinical trials, and often they aren’t eager for their competitors to benefit from that investment, especially when the programs are still ongoing.
但直到最近，阿尔茨海默病的研究人员常常不得不克服很多障碍才能分享数据——他们分享数据是为了解这些拼图碎片是否及如何可以拼一起。障碍的出现有几个原因。一方面，出于对患者隐私的保护，研究人员会对哪些信息可以分享、哪些不可以分享感到困惑。通常，研究人员没有容易获取的工具和技术，用来促进他们之间广泛的数据共享和使用。此外，制药公司在临床试验中投入了大量资金，通常他们并不想让竞争对手从自己的投资中受益，特别是当他们的项目仍在进行时。
Unfortunately, this siloed approach to research data hasn’t yielded great results. We have only made incremental progress in therapeutics since the late 1990s. There’s a lot that we still don’t know about Alzheimer’s, including what part of the brain breaks down first and how or when you should intervene. But I’m hopeful that will change soon thanks in part to the Alzheimer’s Disease Data Initiative, or ADDI.
不幸的是，这种独立处理研究数据的方法并没有产生很好的成果。自1990年代末以来，我们在治疗方面仅取得了渐进式的进展。关于阿尔茨海默病，我们还有很多未知的地方，包括大脑的哪个部分首先会出问题，以及应该如何干预或何时干预。但我希望这种情况很快将有所改变，这在一定程度上要归功于阿尔茨海默病数据行动，简称ADDI。
I worked with a coalition of partners to create ADDI, because we believe that more data sharing will accelerate progress towards an Alzheimer’s breakthrough. To make this happen, ADDI created the Alzheimer’s Disease workbench.
我与一群合作伙伴共同创建了ADDI，因为我们相信更多的数据共享将加快阿尔茨海默病研究取得突破的进程。为了实现这一目标，ADDI创建了阿尔茨海默病工作平台。
This workbench hosts an open, global, and easy-to-use set of tools and resources. The goal is to simplify how researchers and data scientists around the world work together and share data, code, and knowledge in order to make advances in the field.
该平台具有一组开放的、全球的和易于使用的工具和资源，目的是简化世界各地研究人员和数据科学家合作的过程，便于他们分享数据、代码和知识，从而在该领域取得进展。
Instead of having to navigate dozens of individual databases, scientists will be able to access and upload information to a patient database from around the world. The workbench also facilitates access to datasets from failed drug trials, since many pharmaceutical companies have decided that the benefits of sharing their data outweigh the risks. And all the data is in compliance with privacy laws, so researchers don’t have to worry about compromising anyone’s personal information.
不再需要浏览几十个单独的数据库，科学家将能访问及上传信息到一个全球性的患者数据库。该平台还为访问失败药物试验的数据提供了便利，这是由于许多制药公司认为，共享这些数据的好处大过可能的风险。而且这里所有的数据均符合隐私法律，因此研究人员不必担心这么做会危及任何人的个人信息安全。
I’m optimistic that this will make a real difference in Alzheimer’s research, because there are many examples where we’ve made progress on diseases after bringing together large amounts of data. One is malnutrition. Several years ago, our foundation launched an initiative to pool information about childhood growth to try to see when exactly a child who ends up stunted starts falling behind.
我乐观地认为，这将给阿尔茨海默病研究带来真正的改变，因为很多例子表明，我们在将大量数据整合到一起后，就能在疾病领域取得进展。其中的一个例子是营养不良。几年前，我们的基金会发起了一个项目，通过收集有关儿童成长的信息，来了解发育不良的孩子到底是从什么时候开始落后的。
That information produced some fascinating insights. For example, we learned that, in South Asia, weather cycles play a huge role in whether a child recovers from a period where he or she doesn’t get enough to eat. If you’re born during monsoon season—when food can be harder to come by—you still have a decent shot at getting back on a normal growth curve eventually. But if your mother was in her third trimester during monsoon season, you’re much less likely to get back on track. This insight has implications for how we address malnutrition in that region, and we would have never discovered it without pooling lots of different data sources.
这些信息催生了一些非常有趣的发现。例如，我们了解到在南亚，气候周期扮演了一个重要角色，决定着一个孩子能否从食不果腹的一段时期恢复过来。如果你出生在季风季节（在这段时期比较难以获得食物），你仍然有很大希望最终回到正常的生长曲线。但如果你的母亲在季风季节正处于妊娠第三期，那么你回归正轨的可能性就会大大降低。这一发现给我们如何解决该地区的营养不良问题提供了启示。如果没有汇集大量不同来源的数据，我们将永远不会有这一发现。
The Alzheimer’s workbench will finally be available to scientists this month after a year and a half in development. (If you work in data science or Alzheimer’s research, or are just a curious researcher, you can explore the AD Workbench by clicking “Read More” at the bottom of this post.) But even though the workbench is only now becoming broadly available, we’re already seeing huge benefits from it—just not on the disease we expected.
经过一年半的开发，阿尔茨海默病工作平台终于将在本月向科学家开放。（如果你从事数据科学或阿尔茨海默病研究，或者只是一个对此好奇的研究人员，你可以点击文末“阅读原文”了解详情。）虽然这个平台现在才开始供广泛使用，但我们已经从中看到了巨大的收益——只是并非关于我们预期中的疾病。
In the early days of the COVID-19 pandemic, our foundation decided to use the Alzheimer’s workbench framework to create a platform for sharing information on the novel coronavirus. This platform is letting scientists from all around the world collaborate to understand more about the virus and its impacts. Each insight we gain about the virus moves us closer to the end of the pandemic, just as each insight about Alzheimer’s moves us closer to a breakthrough.
在新冠肺炎大流行的初期，我们的基金会决定使用阿尔茨海默病工作平台的框架来创建另一个平台，用来共享有关新冠肺炎病毒的信息。这个平台正让世界各地的科学家通过合作更多地了解新冠病毒及其影响。我们对病毒的每一项发现，都使我们离终结大流行更近了一步，就像对阿尔茨海默病的每一项发现，都会使我们离突破更近一步一样。
I want to be clear: data alone is not going to find the miracle treatment or the diagnostic we need to stop Alzheimer’s (or COVID-19). But what it can do is let us test hypotheses and point us in the right direction.
我想明确一点：仅凭数据，我们无法找到阻止阿尔茨海默病（或新冠肺炎）所需的奇迹疗法或诊断工具。但是数据可以让我们验证假设，并为我们指明正确的方向。
Nearly forty million people around the world have Alzheimer’s or dementia today. We have no way to stop or even slow the disease at this point. I lost my dad to Alzheimer’s two months ago, and I wouldn’t wish that experience on anyone. My hope is that the data sharing facilitated by ADDI will move us closer to a world where no one has to watch someone they love suffer from this awful disease.
如今，全球有近四千万人患有阿尔茨海默病或痴呆症。我们还没有办法阻止甚至减缓这种疾病的发展。两个月前，我的父亲因阿尔茨海默病去世，我不愿任何人有这样的经历。我希望ADDI带来的数据共享，将推动我们朝一个更好的世界迈进，在那里没有人只能眼巴巴地看着自己所爱的人遭受这一可怕疾病的痛苦。
继续阅读
阅读原文