TED2019
Leila Pirhaji: The medical potential of AI and metabolites
Leila Pirhaji: AI 和代谢产物的医学潜能
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许多疾病由代谢物引起，这些代谢物是体内的一些小分子，例如脂肪、葡萄糖和胆固醇，但我们并不确切知道它们是什么，也不知道它们如何起作用。生物技术企业家和 TED 研究员 Leila Pirhaji 分享了她的计划，即建立一个基于 AI 的网络来表征代谢物模式，以更好地了解疾病的发展方式，并发现更有效的治疗方法。
Leila Pirhaji - Biotech entrepreneur
Leila Pirhaji uses artificial intelligence for drug discovery and the treatment of metabolic diseases. Full bio
Leila Pirhaji uses artificial intelligence for drug discovery and the treatment of metabolic diseases. Full bio
Double-click the English transcript below to play the video.
00:13
In 2003,
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在 2003 年，
00:15
when we sequenced the human genome,
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当我们测序人类基因组时，
我们以为会找到
治疗多种疾病的答案。
治疗多种疾病的答案。
00:18
we thought we would have the answer
to treat many diseases.
to treat many diseases.
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00:22
But the reality is far from that,
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但是实际情况远非如此，
00:26
because in addition to our genes,
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因为除了我们的基因，
00:28
our environment and lifestyle
could have a significant role
could have a significant role
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我们的生存环境和生活方式
也可能导致多种重大疾病。
00:33
in developing many major diseases.
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例如，影响全球
00:35
One example is fatty liver disease,
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超过 20％ 人口的脂肪肝，
00:39
which is affecting over 20 percent
of the population globally,
of the population globally,
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00:43
and it has no treatment
and leads to liver cancer
and leads to liver cancer
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没有任何有效的治疗方法，
而且最终可发展为肝癌
而且最终可发展为肝癌
或肝衰竭。
00:46
or liver failure.
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00:49
So sequencing DNA alone
doesn't give us enough information
doesn't give us enough information
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因此，单纯的 DNA 测序
无法提供足够信息，
无法提供足够信息，
帮助我们寻找有效治疗方法。
00:54
to find effective therapeutics.
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好消息是，我们体内
还有许多其他分子。
还有许多其他分子。
00:56
On the bright side, there are
many other molecules in our body.
many other molecules in our body.
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01:00
In fact, there are
over 100,000 metabolites.
over 100,000 metabolites.
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实际上，有超过 10 万多种代谢物。
01:04
Metabolites are any molecule
that is supersmall in their size.
that is supersmall in their size.
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代谢物是体积很小的分子，
01:09
Known examples are glucose,
fructose, fats, cholesterol --
fructose, fats, cholesterol --
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像我们常听说的：
葡萄糖、果糖、脂肪、胆固醇等。
01:14
things we hear all the time.
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01:16
Metabolites are involved
in our metabolism.
in our metabolism.
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代谢物参与我们的新陈代谢，
01:20
They are also downstream of DNA,
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它们在 DNA 的下游，
01:24
so they carry information
from both our genes as well as lifestyle.
from both our genes as well as lifestyle.
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因此，它们携带着来自基因
和我们生活方式的信息。
和我们生活方式的信息。
01:29
Understanding metabolites is essential
to find treatments for many diseases.
to find treatments for many diseases.
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了解代谢物对寻找许多疾病的
治疗方法至关重要。
治疗方法至关重要。
01:34
I've always wanted to treat patients.
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我一直想治病救人，
01:37
Despite that, 15 years ago,
I left medical school,
I left medical school,
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但尽管如此，在十五年前，
我因为喜欢数学
我因为喜欢数学
01:41
as I missed mathematics.
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而离开了医学院。
01:45
Soon after, I found the coolest thing:
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不久之后，我发现了最酷的东西：
01:48
I can use mathematics to study medicine.
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我可以使用数学来研究医学。
01:53
Since then, I've been developing
algorithms to analyze biological data.
algorithms to analyze biological data.
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从那时起，我一直在开发
用于分析生物学数据的算法。
用于分析生物学数据的算法。
01:59
So, it sounded easy:
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这听起来很简单：
我们先收集体内所有代谢物，
02:01
let's collect data from all
the metabolites in our body,
the metabolites in our body,
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然后，开发数学模型
描述疾病中的代谢物变化，
描述疾病中的代谢物变化，
02:05
develop mathematical models to describe
how they are changed in a disease
how they are changed in a disease
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并通过干预这些变化来进行治疗。
02:10
and intervene in those
changes to treat them.
changes to treat them.
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02:14
Then I realized why no one
has done this before:
has done this before:
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然后，我终于明白
以前为何没人做这件事了：
以前为何没人做这件事了：
02:19
it's extremely difficult.
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这真是太困难了。
（笑声）
02:20
(Laughter)
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02:22
There are many metabolites in our body.
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我们体内有许多代谢产物，
02:24
Each one is different from the other one.
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种类繁多。
对于某些代谢物，我们可以使用
02:27
For some metabolites,
we can measure their molecular mass
we can measure their molecular mass
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质谱仪来检测其分子量。
02:31
using mass spectrometry instruments.
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02:33
But because there could be, like,
10 molecules with the exact same mass,
10 molecules with the exact same mass,
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而质量完全相同的分子
可能有 10 种之多，
可能有 10 种之多，
我们分不清谁是谁，
02:38
we don't know exactly what they are,
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02:39
and if you want to clearly
identify all of them,
identify all of them,
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如果想识别所有这些分子，
02:42
you have to do more experiments,
which could take decades
which could take decades
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则必须进行更多实验，
这可能需要几十年、
这可能需要几十年、
数十亿美元。
02:45
and billions of dollars.
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02:48
So we developed an artificial
intelligence, or AI, platform, to do that.
intelligence, or AI, platform, to do that.
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为了做这件事，我们开发了
人工智能（AI）平台，
人工智能（AI）平台，
我们利用生物数据的增长，
02:53
We leveraged the growth of biological data
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02:56
and built a database of any existing
information about metabolites
information about metabolites
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建立了一个数据库，
包含代谢物现有信息
包含代谢物现有信息
03:01
and their interactions
with other molecules.
with other molecules.
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及与其它分子的相互作用的数据。
我们将所有这些数据
组合成了一个大型网络，
组合成了一个大型网络，
03:04
We combined all this data
as a meganetwork.
as a meganetwork.
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然后，在患者的组织或血液中，
03:07
Then, from tissues or blood of patients,
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测量代谢物的质量，
03:11
we measure masses of metabolites
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并寻找因疾病
而产生变化的代谢物的质量。
而产生变化的代谢物的质量。
03:13
and find the masses
that are changed in a disease.
that are changed in a disease.
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03:17
But, as I mentioned earlier,
we don't know exactly what they are.
we don't know exactly what they are.
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但是，正如我之前提到的，
我们并不知道是什么代谢物。
我们并不知道是什么代谢物。
03:20
A molecular mass of 180 could be
either the glucose, galactose or fructose.
either the glucose, galactose or fructose.
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分子量为 180 的代谢物
可以是葡萄糖、半乳糖或果糖，
可以是葡萄糖、半乳糖或果糖，
在我们体内，它们的质量完全相同，
03:25
They all have the exact same mass
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03:27
but different functions in our body.
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但功能不同。
03:29
Our AI algorithm considered
all these ambiguities.
all these ambiguities.
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我们的 AI 算法
考虑了所有这些可能。
考虑了所有这些可能。
03:33
It then mined that meganetwork
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然后，会挖掘那个巨型网络的数据，
03:36
to find how those metabolic masses
are connected to each other
are connected to each other
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以发现那些代谢物
如何相互关联而导致疾病。
03:40
that result in disease.
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03:42
And because of the way they are connected,
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根据它们的关联方式，
03:44
then we are able to infer
what each metabolite mass is,
what each metabolite mass is,
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我们就能推断出
每个代谢物的质量，
每个代谢物的质量，
03:49
like that 180 could be glucose here,
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如 180 分子量的
可能是葡萄糖，
可能是葡萄糖，
03:52
and, more importantly, to discover
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更重要的是，
发现葡萄糖和其他代谢物的变化
03:54
how changes in glucose
and other metabolites
and other metabolites
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如何导致疾病。
03:57
lead to a disease.
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03:59
This novel understanding
of disease mechanisms
of disease mechanisms
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对疾病机制的这种新颖理解，
04:02
then enable us to discover
effective therapeutics to target that.
effective therapeutics to target that.
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使我们能够发现
针对该疾病的有效疗法。
针对该疾病的有效疗法。
04:07
So we formed a start-up company
to bring this technology to the market
to bring this technology to the market
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凭借该技术，我们成立了
一家初创公司，
一家初创公司，
将该技术推向市场，
进而影响人们的生活。
进而影响人们的生活。
04:11
and impact people's lives.
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04:13
Now my team and I at ReviveMed
are working to discover
are working to discover
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现在，我们的 ReviveMed 团队
正努力寻找主要代谢疾病的疗法，
04:17
therapeutics for major diseases
that metabolites are key drivers for,
that metabolites are key drivers for,
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例如脂肪肝，
04:22
like fatty liver disease,
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因为它由脂肪堆积造成，
04:24
because it is caused
by accumulation of fats,
by accumulation of fats,
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04:27
which are types
of metabolites in the liver.
of metabolites in the liver.
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而脂肪是肝脏中的代谢物。
04:29
As I mentioned earlier,
it's a huge epidemic with no treatment.
it's a huge epidemic with no treatment.
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如前所述，这种大型流行病
尚无有效疗法。
尚无有效疗法。
04:33
And fatty liver disease
is just one example.
is just one example.
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脂肪肝只是其中一个例子，
展望未来，我们将研究其它几百种
04:36
Moving forward, we are going to tackle
hundreds of other diseases
hundreds of other diseases
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尚无有效疗法的疾病。
04:40
with no treatment.
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通过收集更多代谢物的数据，
04:42
And by collecting more and more
data about metabolites
data about metabolites
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了解代谢物的变化
04:46
and understanding
how changes in metabolites
how changes in metabolites
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如何导致疾病发展，
04:50
leads to developing diseases,
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04:52
our algorithms will get
smarter and smarter
smarter and smarter
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我们的算法会逐步完善，
04:56
to discover the right therapeutics
for the right patients.
for the right patients.
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为某些患者找到合适的疗法。
而且，我们将更加接近我们的愿景：
05:00
And we will get closer to reach our vision
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用程序代码拯救生命。
05:04
of saving lives with every line of code.
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谢谢。
05:08
Thank you.
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（掌声）
05:09
(Applause)
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ABOUT THE SPEAKER
Leila Pirhaji - Biotech entrepreneurLeila Pirhaji uses artificial intelligence for drug discovery and the treatment of metabolic diseases.
Why you should listen
Leila Pirhaji is the founder of ReviveMed, an AI platform that can quickly and inexpensively characterize large numbers of metabolites (small molecules like glucose or cholesterol) from the blood, urine and tissues of patients. This allows for the detection of molecular mechanisms that lead to disease and the discovery of drugs that target these disease mechanisms.
Leila Pirhaji | Speaker | TED.com