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功能基因組學(xué)能否破解新藥研制失敗率難題

功能基因組學(xué)能否破解新藥研制失敗率難題

方繪香(Erika Fry) 2019年04月14日
在這個(gè)科技發(fā)展突飛猛進(jìn)的年代,新藥失敗率依然高居不下,但功能基因組學(xué)卻有可能打破這個(gè)情況。

新藥發(fā)現(xiàn)是一個(gè)極其燒錢、低效的流程。候選藥在經(jīng)歷了高成本、多年期臨床試驗(yàn)流程之后,有90%最終都與市場無緣。90%的失敗率會拖累醫(yī)療產(chǎn)業(yè)的發(fā)展,同時(shí)也成為了大型公司為其天價(jià)藥辯解的托詞。事實(shí)證明,即便是在這個(gè)科技發(fā)展突飛猛進(jìn)的年代,上述失敗率卻絲毫沒有松動(dòng)的跡象。

讓我們想一下:自從美國前總統(tǒng)比爾·克林頓宣布完成首個(gè)人類基因組測繪之后已經(jīng)過了近20年的時(shí)間??肆诸D曾經(jīng)說過,“這是科學(xué)與理性領(lǐng)域一個(gè)劃時(shí)代的勝利”,能夠帶來“大量新治療方案”,而且“可以通過攻擊疾病的基因來治療阿爾茨海默癥、帕金森綜合征、糖尿病和癌癥等疾病?!?/p>

雖然這些美好的目標(biāo)依然只是正在進(jìn)行的工作,但英國制藥巨頭葛蘭素史克的研發(fā)負(fù)責(zé)人哈爾·巴倫認(rèn)為,該行業(yè)可能終于即將迎來具有實(shí)際意義而且卓有成效的基因革命。巴倫是一位心臟病學(xué)家,曾經(jīng)在基因泰克和Alphabet的長生實(shí)驗(yàn)室Calico擔(dān)任過領(lǐng)導(dǎo)職務(wù),雖然他不大愿意做出這類籠統(tǒng)的聲明,但他在《財(cái)富》雜志上周于圣迭戈舉行的健康頭腦風(fēng)暴會議上說,當(dāng)前的形勢“給我一種不同的感受”。

他解釋說,作為一項(xiàng)基礎(chǔ)性工作,過去的基因組測序所提供的“構(gòu)造性”洞見十分有限??茖W(xué)家可以破解DNA,并發(fā)現(xiàn)堿基對鏈中的變異,但測序難以解釋隨之而來的生物學(xué)現(xiàn)象,也就是這些變異如何影響基因發(fā)揮作用的方式(以及后續(xù)會給攜帶這些基因的人群帶來什么影響)。

他對當(dāng)前形勢十分樂觀的原因在于新出現(xiàn)的一些技術(shù),即更加廉價(jià)的高通量DNA測序和深度學(xué)習(xí)。這些技術(shù)近期的同時(shí)興起也讓葛蘭素史克這類大型制藥公司能夠開展功能基因組學(xué)的研究。他解釋說,功能基因組學(xué)可以幫助建立基因變化與功能之間的聯(lián)系,解決近些年來出現(xiàn)的種種基因謎團(tuán)(例如,為什么在出現(xiàn)特定變異的所有個(gè)體中,有30%患上了帕金森綜合征,但其他人卻沒有),并確立藥物靶標(biāo)。巴倫說,有數(shù)據(jù)顯示,如果藥物靶標(biāo)能夠得到基因驗(yàn)證,那么新藥開發(fā)的成功率有可能會翻倍。

少數(shù)基因數(shù)據(jù)庫,從英國的Biobank到23andMe的自愿客戶基因池(葛蘭素史克去年夏天與這家基因檢測公司達(dá)成了一項(xiàng)協(xié)議),提升了驗(yàn)證工作可行性。就深度學(xué)習(xí)而言,我們可以利用其能力分析人類生物構(gòu)成方面“異常復(fù)雜”的多領(lǐng)域海量數(shù)據(jù)集。

這位研究負(fù)責(zé)人表示,功能基因組學(xué)還處于初期,葛蘭素史克的項(xiàng)目也不過是剛剛起步,但他計(jì)劃迅速向前推進(jìn)。巴倫說:“我們希望成為業(yè)界的領(lǐng)軍者?!保ㄘ?cái)富中文網(wǎng))

譯者:馮豐

審校:夏林

Drug discovery is a notoriously expensive and inefficient endeavor. Nine of 10 drug candidates that go through the cost-intensive, years-long clinical trial process never make it to market. That 90% failure rate—a drag on medical progress and a factor often cited by pharmaceutical companies to justify sky-high drug prices—has proven frustratingly sticky even in an era of breakneck scientific and technological advancements.

Consider: it’s been nearly two decades since President Bill Clinton announced the completion of the first-ever survey of the human genome, “an epic-making triumph of science and reason” that Clinton said would bring “immense, new power to heal” and “cure diseases like Alzheimer’s, Parkinson’s, diabetes, and cancer by attacking their genetic roots.”

Those lofty goals are still very much a work in progress, but Hal Barron, the head of R&D for the U.K.-based pharmaceutical giant GSK, thinks the industry may at last be on the cusp of a meaningful and productive genetic revolution. Though Barron, a cardiologist who previously held leadership roles at Genentech and Alphabet’s immortality lab Calico, hesitates to make such sweeping claims, he said at Fortune’s Brainstorm Health conference in San Diego last week that this moment “feels different.”

The genome sequencing efforts of the past, while foundational, offered limited “structural” insight he explained. Scientists could decode the DNA and identify mutations in a chain of base pairs, but the sequencing did little to explain the resulting biology—or how those mutations affect the way genes function (and in turn, impact the humans who hold them).

He’s optimistic about the current moment because of a handful of technologies—namely cheaper, high-throughput DNA sequencing and deep learning—have recently and simultaneously made the study of functional genomics feasible for big pharma companies like GSK. Functional genomics, he explained, can help link the genetic variant to function, solve the genetic mysteries that have piled up in recent years (why 30% of individuals with a certain mutation get Parkinson’s Disease, but the other 70% does not, for example) and pinpoint drug targets. Barron says data shows drug development is twice as likely to succeed when the drug target is genetically validated.

A handful of genetic databases, from the UK Biobank to 23andMe’s consenting customer pool (GSK did a deal with the genetic testing company last summer), have made the validation work more possible. As has deep learning, with its power to analyze the massive, multidimensional, “wildly complicated” data sets that make up human biology said Barron.

The research chief said it’s early days for functional genomics and that GSK’s program is in its infancy, but he plans to move quickly. Said Barron: “We’re hoping to be the leaders.”

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