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1. 幫助指導(dǎo)使用已通過的癌癥藥物

雖然臨床試驗為醫(yī)生們提供了許多藥物如何發(fā)揮作用的有用信息，但是大概只有2%的癌癥患者參與了臨床試驗。 事實上，每天都有成千上萬的患者接受診斷和治療。這意味著其實我們可以從中獲得大量的重要數(shù)據(jù),來幫助醫(yī)生與病人在面對不同治療方案及其可能的結(jié)果時做出更好的選擇。

美國臨床腫瘤學(xué)會ASCO發(fā)起建立一個數(shù)據(jù)庫:CancerLinQ,旨在獲取這些數(shù)據(jù)。它能將數(shù)據(jù)提供給醫(yī)生們, 為他們提供實時的治療建議。美國基因泰克公司（Genentech）的科學(xué)家和醫(yī)生們都對能幫助ASCO開發(fā)一個完善的CancerLinQ系統(tǒng)感到興奮。

2. 決定每位患者的預(yù)后治療

了解患者的預(yù)后，可以幫助醫(yī)療團隊決定對患者癌癥的治療強度，以及在腫瘤消失后需采取的措施。大數(shù)據(jù)正在借助分析從大量不同患者搜集過來的海量信息，來預(yù)測長期結(jié)果。例如，醫(yī)生可以使用這些信息來決定哪些患者應(yīng)該接受進一步治療，哪些患者，由于他們的癌癥不太可能復(fù)發(fā)而避免不必要的治療。

3. 幫助藥物開發(fā)發(fā)掘潛在的新靶點

對大量腫瘤DNA進行測序可以幫助研究人員了解一些與癌癥相關(guān)的基因變化?？茖W(xué)家利用這一點幫助測試潛在的新藥物，這些藥物能靶定到某些與腫瘤生長相關(guān)的基因變化或驅(qū)動因子。大數(shù)據(jù)可以從臨床前試驗中獲得，并用來幫助藥物或藥物組合的選擇，以放到人類臨床試驗的研究中。

4. 解決大的公共衛(wèi)生問題

流行病學(xué)研究包括癌癥在內(nèi)的人類疾病的起因及模式。在大數(shù)據(jù)時代之前，人們發(fā)現(xiàn)吸煙是導(dǎo)致絕大多數(shù)肺癌的因素?，F(xiàn)在，大數(shù)據(jù)可以幫助解決癌癥研究中更大的問題。新時代的流行病學(xué)借助于海量的住院記錄及基因組數(shù)據(jù)，深入研究不同人群中的不同癌癥。

5. 允許病人直接參與進來

癌癥患者現(xiàn)在可以通過提供基因，醫(yī)療記錄及治療效果等數(shù)據(jù)，直接參與癌癥研究。這些信息用于建立大型的研究數(shù)據(jù)庫。

英語原文：

5 things Big Data CAN do in cancer research

1. Help Guide the Use of Approved Cancer Medicines

While clinical trials provide valuable information to doctors on how medicines may work, only about 2% of people with cancer participate in clinical trials. However, thousands of people are diagnosed and treated every day, which means there is a huge amount of important data that could be obtained to help doctors and patients make better decisions about treatment options and potential outcomes.

ASCO has started an initiative, CancerLinQ, to try to capture some of these data. CancerLinQ is a system that connects doctors with data, helping to inform decisions about treatments in real time. Scientists and doctors at Genentech are excited to help ASCO develop the full CancerLinQ system.

2. Determine an Individual Patient’s Prognosis

Knowing a patient’s prognosis allows medical teams to decide how aggressively to treat each cancer and what steps to take after a tumor is gone. By analyzing information from incredibly large and diverse groups of patients, big data is helping to predict long-term outcomes. For example, doctors can use this information to determine who should receive additional treatment and who might avoid it because their cancer is unlikely to recur.

3. Help Discover Potential New Targets for Drug Discovery

The ability to sequence the DNA of large numbers of tumors has allowed researchers to understand the genetic changes underlying certain cancers. Scientists can use this information to help test potential new medicines that might target some of these genetic changes or drivers of cancer growth. Big data sets from preclinical studies are being used to help predict which medicines or combinations of medicines might be good candidates to move forward into clinical trials in humans.

4. Answer Big Public Health Questions

Epidemiologists study the causes and patterns of human diseases including cancer. In the era before big data, they discovered that smoking causes the vast majority of lung cancer cases. Now big data is allowing them to answer even bigger questions in cancer research. This new era of epidemiology takes advantage of the availability of large collections of hospital records and genomic data, leading to new insights into diverse cancers in diverse populations.

5. Allow Individuals to Get Involved

People with cancer can now play a direct role in research by contributing genetic data and information about their health and how treatments have affected them to large databases used for research.

via：大數(shù)據(jù)文摘（公眾號：BigDataDigest）校檢：兔八哥