财富杂志 AI如何让老药新用?(1)（在线收听）

In the elegant quiet of the café at the Church of Sweden, a narrow Gothic-style building in Midtown Manhattan,

位于曼哈顿中城区的瑞典教会是一个狭窄的哥特式建筑，在教会内的咖啡馆里，

Daniel Cohen is taking a break from explaining genetics.

丹尼尔·科恩暂时从解释遗传学中脱身休息一会儿。

He moves toward the creaky piano positioned near the front door, sits down, and plays a flowing, flawless rendition of "Over the Rainbow."

他朝着前门旁边的那架旧钢琴走去，坐下，并弹奏了一首流畅完整的《Over the Rainbow》。

If human biology is the scientific equivalent of a complicated score, Cohen has learned how to navigate it like a virtuoso.

如果人体生物学在科学上相当于一个复杂的分数，那么科恩已经学会了如何像一个艺术大师那样驾驭它。

Cohen was the driving force behind Généthon, the French laboratory that in December 1993 produced the first-ever "map" of the human genome.

科恩是法国实验室Genethon的中坚力量，该实验室于1993年12月绘制了第一张人类基因组“图谱”。

He essentially introduced Big Data and automation to the study of genomics,

他将大数据和自动化引入遗传学的研究中，

as he and his team demonstrated for the first time that it was possible to use super-fast computing to speed up the processing of DNA samples.

因为他和他的团队首次证明，使用超高速运算来加速DNA样本的处理是有可能的。

Scientists worldwide have built on Cohen's insights, and Cohen himself, an MD with a Ph.D. in immunology,

全世界的科学家都以科恩的见解为基础，而拥有医学博士学位和免疫学博士学位的科恩本人，

has gone on to success as a researcher and pharma executive. But a quarter-century later,

则成功成为了一名研究人员兼制药公司高管。但25年后，

genomics has yielded few of the kinds of paradigm-changing medical breakthroughs that many of its early innovators hoped for.

遗传学几乎没有取得许多早期创新者所期待的那种变革式的医学突破。

Today, as chief executive and founder of Paris-based drug startup Pharnext, Cohen is striving to understand why that rainbow hasn't led to a pot of gold.

如今，作为一家总部位于巴黎的药物初创公司Pharnext的CEO兼创立者，科恩正力求弄清楚，为什么那道彩虹没有带来一罐金子。

"Any protein in the body has many different functions, not only one," he says,

“身体中的任何一个蛋白质都有不止一种功能，而是有很多不同的功能”

returning from the piano to talk with me, "just as you are a person who has many functions in the population, not just one."

他从钢琴旁走过来跟我说，“就像是你在社会中不仅只有一种职责，而是有很多职责。”

The phenomenon Cohen is describing is "pleiotropy," the capacity of a single gene to have multiple, seemingly unrelated effects.

科恩描述的这一现象是“基因多效性”，一个基因具有多个看似无关影响的能力。

It is one of the complexities of disease that has repeatedly frustrated medical researchers in their quest for therapies for the most stubborn illnesses.

这是疾病的复杂性之一，它一再让寻求最顽固疾病治疗方法的医学研究人员感到沮丧。

Cohen not only appreciates pleiotropy's significance: He believes that Pharnext and other drugmakers may soon exploit it—

科恩不仅仅是重视基因多效性的重要性：他相信Pharnext和其他制药公司或许很快就能利用它——

with a powerful boost from artificial intelligence. By embracing the body's complexity,

在人工智能的强大推动力下。理解身体的复杂性，

and by using A.I. to more methodically analyze and map the way the chain reactions of disease sweep through the body,

并利用AI系统地分析和绘制疾病横扫身体的连锁反应方式，

he hopes to develop combinations of drugs tuned to attack a plethora of medical conditions.

他希望通过此来开发出治疗多种疾病药物组合。

Cohen and his team are also applying A.I. to search for therapies that leverage "repurposing"—

科恩和他的团队也正在应用AI寻找可以进行“再利用”的治疗方法——

combining existing drugs in ways that give them therapeutic powers that each lacks in isolation.

将现有药物进行结合，并赋予它们各自所缺乏的治疗能力。

Their long-term goal is a drug pipeline that is far more efficient than Big Pharma's notoriously slow R&D departments—streamlined by machine learning.

他们的长期目标是一个比大型制药公司中以缓慢著称的研发部门更加高效的药品管道——通过机器学习来提高效率。

Cohen's sleepy gaze widens with enthusiasm when he describes how it's all coming along. "Très bien," he says. “Très économique.”

当科恩描述这一切是如何进行的时，他睡眼惺忪的目光充满了热情。“很好，”他说。“非常经济实惠。”

Running in the same race as Pharnext are companies ranging from giants like Google and IBM to startups such as Insilico Medicine,

与Pharnext同场竞技的是各大公司，如谷歌和IBM这样的巨头，以及像Insilico Medicine、Recursion Pharmaceuticals以及

Recursion Pharmaceuticals, and BenevolentAI. All are deeply invested in the tools of A.I.,

BenevolentAI，这样的初创公司。他们都在AI工具上投资巨大，

using them to analyze millions of examples of drug and patient data and tease out patterns of significance.

利用它们来分析数以百万计的药物和病人数据的例子，并梳理出重要的模式。

But Pharnext, founded in 2007, predates most of those competitors by several years—

但成立于2007年的Pharnext，比大多数竞争对手都早了几年——

and has a longer head start when one factors in Cohen's decades of earlier research in genomics and pleiotropy.

而且拥有更长的领先优势，因为科恩对基因组学和基因多效性进行了几十年的前期研究。

And perhaps most important, Pharnext's application of A.I. to medical problems over the course of more than a decade

或许最重要的是，在过去十多年的时间里，Pharnext一直将AI应用于医疗问题，

has finally reached a critical inflection point.

现在终于达到了一个关键的转折点。