功能基因组学能否破解新药研制失败率难题

新药发现是一个极其烧钱、低效的流程。候选药在经历了高成本、多年期临床试验流程之后，有90%最终都与市场无缘。90%的失败率会拖累医疗产业的发展，同时也成为了大型公司为其天价药辩解的托词。事实证明，即便是在这个科技发展突飞猛进的年代，上述失败率却丝毫没有松动的迹象。

让我们想一下：自从美国前总统比尔·克林顿宣布完成首个人类基因组测绘之后已经过了近20年的时间。克林顿曾经说过，“这是科学与理性领域一个划时代的胜利”，能够带来“大量新治疗方案”，而且“可以通过攻击疾病的基因来治疗阿尔茨海默症、帕金森综合征、糖尿病和癌症等疾病。”

虽然这些美好的目标依然只是正在进行的工作，但英国制药巨头葛兰素史克的研发负责人哈尔·巴伦认为，该行业可能终于即将迎来具有实际意义而且卓有成效的基因革命。巴伦是一位心脏病学家，曾经在基因泰克和Alphabet的长生实验室Calico担任过领导职务，虽然他不大愿意做出这类笼统的声明，但他在《财富》杂志上周于圣迭戈举行的健康头脑风暴会议上说，当前的形势“给我一种不同的感受”。

他解释说，作为一项基础性工作，过去的基因组测序所提供的“构造性”洞见十分有限。科学家可以破解DNA，并发现碱基对链中的变异，但测序难以解释随之而来的生物学现象，也就是这些变异如何影响基因发挥作用的方式（以及后续会给携带这些基因的人群带来什么影响）。

他对当前形势十分乐观的原因在于新出现的一些技术，即更加廉价的高通量DNA测序和深度学习。这些技术近期的同时兴起也让葛兰素史克这类大型制药公司能够开展功能基因组学的研究。他解释说，功能基因组学可以帮助建立基因变化与功能之间的联系，解决近些年来出现的种种基因谜团（例如，为什么在出现特定变异的所有个体中，有30%患上了帕金森综合征，但其他人却没有），并确立药物靶标。巴伦说，有数据显示，如果药物靶标能够得到基因验证，那么新药开发的成功率有可能会翻倍。

少数基因数据库，从英国的Biobank到23andMe的自愿客户基因池（葛兰素史克去年夏天与这家基因检测公司达成了一项协议），提升了验证工作可行性。就深度学习而言，我们可以利用其能力分析人类生物构成方面“异常复杂”的多领域海量数据集。

这位研究负责人表示，功能基因组学还处于初期，葛兰素史克的项目也不过是刚刚起步，但他计划迅速向前推进。巴伦说：“我们希望成为业界的领军者。”（财富中文网）

译者：冯丰

审校：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.”