數(shù)據(jù)共享有助于加快攻克老年癡呆癥
不久前，社交新聞網(wǎng)站Reddit的一名用戶上傳了一張令人難忘的照片，那是她母親被診斷出患有“阿爾茲海默癥”(Alzheimer’s，俗稱“老年癡呆癥”——譯者注)后，用毛線織的方格圖案的照片。剛開始的圖案都很整齊，越到后來，針腳越亂，到最后方格已經(jīng)不成其為方格了，徹底亂成了一團。
The picture perfectly captures how Alzheimer’s destroys the brain. The disease robs people of their ability to function. My family and I have seen first-hand how devastating this process is, and we’re not alone.
這張照片很好地體現(xiàn)了老年癡呆癥是如何摧毀大腦的。這種疾病能致使患者喪失身體機能。我和家人親眼目睹了這個過程的破壞力有多大，而很多人跟我們有相同的經(jīng)歷。
In the UK, Alzheimer’s is the only disease in the top 10 causes of death without any meaningful treatments that becomes more prevalent each year. Unless we find a breakthrough in treatment, its cost — both emotional and financial — will explode.
在英國前十大致死疾病中，老年癡呆癥是唯一完全沒有任何有效療法的。年復(fù)一年，此病變得日益流行。除非我們在療法上取得重大突破，該病的成本——不管是在情感上還是在經(jīng)濟上——將爆炸性增長。
Despite this daunting state of affairs, I’m optimistic that we can substantially reduce the impact of Alzheimer’s. There are a number of areas where we can make significant progress.
盡管局面如此嚴重，我還是樂觀地認為我們能夠顯著減輕該病的影響。在很多領(lǐng)域我們都有可能取得重大進展。
To start, we could enable faster progress on all fronts of the Alzheimer’s fight by facilitating more data-sharing. Scientists all around the world are working hard to generate new discoveries every day. The data they’re collecting in the process are a tremendously powerful tool that can be harnessed better to understand and reduce the impact of the disease.
首先，通過推動人們更多地共享數(shù)據(jù)，我們可以在對抗老年癡呆癥這場戰(zhàn)斗的各個方面更快地取得進展。世界各地的科學(xué)家每天都在殫精竭力地試圖找到新的發(fā)現(xiàn)。他們在這個過程中收集的數(shù)據(jù)是一件非常有用的工具，可以更好地加以利用，以了解并減輕這種疾病的影響。
Much of the research being done is publicly funded. While I recognise there is a lot of money to be made from discovering an effective Alzheimer’s treatment, the benefits the entire field will reap from combining data sets outweigh the competitive advantages that come from keeping information siloed.
目前正在開展的很大一部分研究都是由公共部門資助的。我承認，發(fā)現(xiàn)一種對抗老年癡呆癥的有效療法能賺很多錢，但將數(shù)據(jù)匯總起來給整個領(lǐng)域帶來的收益，將遠超獨守信息所能帶來的競爭優(yōu)勢。
For one thing, compiling these data might show us how the disease progresses. When you take a newborn to the doctor, you can see how their height and weight measure against a typical growth curve. Combining data sets could allow us to create a similar curve for our brain’s health as it ages, helping us understand how Alzheimer’s deviates from normal ageing, and track how the brain changes. We could also see how these changes may differ based on gender, ethnicity, lifestyle or genetics.
一來，通過匯總數(shù)據(jù)，或許可以讓我們看出該病是如何發(fā)展的。當(dāng)你帶一個新生兒去看醫(yī)生時，你可以看到嬰兒的身高體重與典型成長曲線對比的情況。將數(shù)據(jù)匯集起來，我們或許可以構(gòu)建一條類似的顯示大腦健康狀況隨年紀增大而變化的曲線，從而有助于我們理解老年癡呆癥是如何偏離正常老化軌跡的，并追蹤大腦變化情況。我們也可以看到，不同的性別、種族、生活方式或基因，大腦的這些變化會有什么不同。
Here’s another benefit: by analysing data from large populations, we will probably be able to identify patients at risk earlier. Families and doctors often wait until memory problems appear before diagnosing someone, but the disease begins much earlier. A comprehensive look at brain scans, genetics, medical records and memory testing results would enable doctors to calculate your Alzheimer’s “risk score” and identify when you should be tested further.
還有一個好處是，通過分析來自大量人口的數(shù)據(jù)，我們也許能夠更早地發(fā)現(xiàn)有罹患此病風(fēng)險的潛在患者。家屬和醫(yī)生經(jīng)常等到患者出現(xiàn)記憶問題才能做出診斷，其實疾病的發(fā)生要早得多。綜合分析腦部掃描圖像、基因、病歷和記憶測試結(jié)果，醫(yī)生能夠就你罹患老年癡呆癥的風(fēng)險打一個分數(shù)，判斷你什么時候應(yīng)該去做進一步的檢測。
Large data sets will also make it easier to identify new targets for treatment. While most research to date has focused on two proteins that cause tangles and plaques in the brain, there are thousands of potential ways we could target Alzheimer’s. I recently invested in a UK-based organisation working on unique approaches to stopping the disease, and there is lots of excellent science being conducted on a small scale. A comprehensive look at the results coming out of these past studies could help spot attractive drug candidates and promising new approaches.
龐大數(shù)據(jù)集也更加便于識別新的治療目標。盡管迄今大多數(shù)研究聚焦于導(dǎo)致大腦出現(xiàn)斑塊和纏結(jié)的兩種蛋白質(zhì)，但針對老年癡呆癥我們有幾千種潛在方法可以嘗試。我最近投資了英國一家研究以獨特方法抑制該病的機構(gòu)，小范圍進行的出色科研活動也很多。綜合考察這些以往研究的結(jié)果，可能有助于找出有吸引力的潛在合適的藥物和有前景的新療法。
The clinical trial process is another area that will benefit from data. It’s difficult to find enough eligible patients willing to participate. If scientists could predict exactly how many participants are needed to gauge the efficacy of a new drug, they could conduct smaller but just as effective studies. This would speed up the process and help get new therapies to market sooner.
臨床試驗是另一個可從數(shù)據(jù)中受益的領(lǐng)域。研究者很難找到足夠多的愿意參與試驗的合適患者。如果科學(xué)家們能夠準確地預(yù)測出需要多少患者才能評估一種新藥的功效，那么他們就可以進行規(guī)模更小但同樣有效的研究。這將加快研究進程，有助于把新療法加快推向市場。
Data have already transformed our lives for the better in so many ways, from spotting a fraudulent purchase on your credit card to adjusting traffic lights so that you spend less time sitting in traffic. I can’t wait to see what new discoveries will be made in the fight against Alzheimer’s thanks to the power of data.
在很多方面，數(shù)據(jù)都使我們的生活變得更美好——從發(fā)現(xiàn)冒用信用卡進行欺詐性購物的行為，到調(diào)整交通信號燈以減少等待時間。我迫不及待地想看到數(shù)據(jù)能夠幫助我們在對抗老年癡呆癥方面取得什么新發(fā)現(xiàn)。
The writer is co-chair of the Bill & Melinda Gates Foundation
本文作者為比爾和梅林達•蓋茨基金會(Bill and Melinda Gates Foundation)聯(lián)合主席
