
Peter Thiel Explains Biotech Investing Rationale: Get Rid of Randomness - adenadel
http://www.technologyreview.com/news/541226/peter-thiel-explains-biotech-investing-rationale-get-rid-of-randomness/
======
Fede_V
There is another incredibly interesting meta-discussion implicit in that
article. How does someone very intelligent like Peter Thiel make investment
decisions in an area where he lacks a huge amount of background knowledge?

He can obviously evaluate the team, he can ask experts he trusts to give him
their opinion about the value of the approach, but... biotech start ups, far
more than software start ups, live or die by the strength of their technology.
Transplants have far fewer false positives than working with cell lines
(especially HeLa!) - but they are also several orders of magnitude more
expensive. Is the trade off between decreasing false positives versus increase
in experiment costs worth it? That company obviously think so, but it's not a
no brainer, and it's very difficult to seriously evaluate. Mice models are
very expensive - and they are better than HeLa, but they aren't foolproof. In
cancer biology, there's a continuum between how expensive a technique is, and
how much it recapitulates the actual biology of the disease. The sweet spot
also varies hugely from disease to disease.

Another point which I find fascinating, is that more or less everyone who has
worked on cancer biology knows that HeLa are not really a realistic model...
yet people keep using them, why? Because a lot of researchers are interested
in publishing papers in prestigious journals, not discovering robust findings.
A pharma company instead has a lot more incentive in getting things right -
because a splashy result that gets falsified at phase 1 is an incredibly
expensive failure, while it's still a Nature paper for a professor. I don't
think that academia should exist to serve pharma companies, but the problem of
false positives is very real, and all the incentives around the
publishing/grant system make it much worse. We should be rewarding researchers
that get moderate but robust results that hold up under scrutiny, not people
who make incredibly splashy discoveries that later turn out to be incredibly
narrow and difficult to reproduce.

~~~
cryoshon
There are no completely accurate tumor models. The best a tumor model can do
for a group is provide a standardized disease progression to test against.

This is why in mouse tumor models there are a lot of highly aggressive tumor
models that are meant to rapidly kill the host-- if you can show even a 5%
reduction in tumor size or 5% longer life of the mouse, it's impressive.

------
a_bonobo
I'm not the biggest fan of Thiel's thinking, but this line shows that the two
founders did their job very well:

>They convinced me there is a surprising amount that has gone wrong with the
cancer cell lines people have been studying

This sounds that they managed to explain to him how much is going wrong with
HeLa cells (I assume he's talking about HeLa - these are the most widely
used).

They're so sturdy that they contaminate everything to the point that some
well-known, well-used cancer cell lines turn out to be nothing but HeLa
contamination [1]. There's ethical problems as the original cells were taken
from Henrietta Lacks without her consent (this is slowly being rectified, have
a look at "The Immortal Life Of Henrietta Lacks"). HeLa cells have mutated so
much in culture that they have little in common with human cells [2]. I wonder
which "human cancer" cells they graft into mice.

All together, this sounds like the founders did their homework on science
communication. To scientists this highlights the importance of communication -
it's not "just" useful for talking to "the public about the importance of your
work", it can make you some serious money!

[1] [http://retractionwatch.com/2013/03/11/more-hela-problems-
for...](http://retractionwatch.com/2013/03/11/more-hela-problems-for-decades-
a-widely-used-bladder-cancer-line-hasnt-been-what-scientists-thought/)

[2] [http://blogs.biomedcentral.com/on-
biology/2013/09/17/debatin...](http://blogs.biomedcentral.com/on-
biology/2013/09/17/debating-the-hela-cell-controversy-karyotype-defined-cell-
line-identity-and-the-privacy-of-patients-2/)

~~~
eggie
The fact that they managed to convince Mr. Thiel that they have a unique
approach indicates as much about his lack of education in biology as it does
their ability to communicate.

The problems with modeling human disease using "found" cancer cell lines (of
which HeLa is just one of hundreds) have been widely-understood for well more
than a decade. These cells have absurd, fragmented genomes with bizarre and
variable chromosomal copy numbers. They have lived in culture for sometimes
many decades, under strange evolutionary pressures. They provide models in
which we can explore human-like cells and regulatory pathways, but it is well-
acknowledged in the field that these are not sufficient to model a generic
form of cancer, much less a particular patient's cancer.

Thiel is approaching biotech with the same blindness with which older
investors approached investment in datatech during the dot-com bubble. There
is no more reason to believe that this startup will corner the market on
xenograft-based research into cancer therapeutics than there was to believe
that pets.com would become the be-all and end-all of everything pet related
online. But this comes back to your point, that the founders have done a
fantastic job of communication. I hope they are communicating the truth, and
not just their dream. It will be a big fall if it is the latter.

~~~
a_bonobo
As the article is a bit short on details we can only grasp at what they
exactly do different - maybe they're not doing anything unique, maybe he's
just impressed with how they're using "known" methods to minimize
risks/randomness.

I really can't tell from the text what kind of cells they use and how random
these are, or how novel their method is (if it is even novel).

------
srunni
> technology is trying to overcome the randomness that is nature

This is a major reason why consumer electronics and information technology
have enabled so many more rapidly scalable businesses in recent decades than
other industries (hence "We wanted flying cars, instead we got 140
characters").

The technology industry is uniquely founded on physical phenomena that are
deterministic, even at high speed or recursive complexity (CPUs, storage,
networking, displays, peripherals, etc). Therefore, if you can think of
something in a mathematical fashion, you know that it can be built. This
essentially eliminates technical feasibility risk - rather than worrying about
_whether_ a product can be built, you can focus on _what_ should be built and
_why_.

~~~
zorked
Well, CPUs don't grow on trees. We got to the point of predictability through
the same rocky, unpredictable process of eliminating randomness (a.k.a.
science).

~~~
srunni
I don't mean the fabrication of those components, I mean their operation.

In living organisms, eliminating randomness in their operation would change
their intended behavior in several ways - randomness is a feature, not a bug,
in living organisms.

------
fabian2k
Even with using xenografts instead of cell lines there's plenty of stuff that
can go wrong. Animal models are maybe closer to humans than cell lines, but
they're still far from perfect.

Derek Lowe posted about this a few days ago on his In The Pipeline blog:

 _But their rationale is that trying to culture CSCs in vitro runs the risk of
having them change character too much, making any assays using them
unreliable. My guess is that they’re right about that, but my worry is that
xenograft tumors themselves are already unreliable enough to cause trouble
(and I have no idea of what happens to them after you “passage” them through
multiple animals). Xenograft models are, of course, well known in oncology
drug discovery, but one of the things that’s well known about them is that
they’re the pure example of “necessary but nowhere near sufficient”._

[http://blogs.sciencemag.org/pipeline/archives/2015/09/09/cha...](http://blogs.sciencemag.org/pipeline/archives/2015/09/09/chasing-
cancer-stem-cells)

------
giltleaf
>the randomness that I think of as the evil part of nature.

This is a perfect example of why Thiel's thinking is so unappealing to me.
First of all, nature is not random, but there is a lack of understanding of
the true implications of cause and effect of what goes on at a biological (and
ecological) level that it may appear that way to people so captivated by the
binary control of the programming world.

But, even if it were random, I don't think that's evil in the least. It's
unpredictable, yes, but so are the implications of many of the technologies
that Thiel embraces. That does not make those technologies inherently evil,
just as "randomness" is not an evil part of nature.

I am afraid of the sterile world that Thiel seems to want.

Additionally, I'd like to point out this bit from a below comment where the
poster responded to several article excerpts, including: "I think of aging and
maybe just mortality as random things that go wrong. The older you get, the
more random things happen, the more breaks. If it’s not cancer, you could get
hit by an asteroid. So on some level, technology is trying to overcome the
randomness that is nature. That is a question on the level of a company. Can
you get rid of randomness in building a company? But the philosophical version
of the question is whether we can get rid of randomness in its entirety and
overcome the randomness that I think of as the evil part of nature." Nature
isn't random! Nature is complex, cryptic, self-referential, and chaotic, but
it's deterministic at the level of biology. "Random things happening" is not a
proper understanding of age-related decline; aging is the long-term
compounding interest of metabolic byproducts. It really stuns me that Thiel's
understanding of these things is so apathetic to reality.

------
defenestration
I find this a very inspiring line of thought for two reasons. 1)
Philosophical. What if we could get rid of randomness in our lives? Can we do
'end-to-end' assembly with our health, owning all stages of the process, like
Elon Musk does with Tesla Cars? And in the end, will this give you more
happiness or more stress? 2) Business. Getting rid of randomness is important
for the growth of our startup. This interview gets me thinking: what
randomness can we cut out of our business?

~~~
HiYaBarbie
If you take the idea of "getting rid of randomness" to its logical conclusion,
it boils down to _making_ the world deterministic.

Does it make sense to pursue impossible goals? If not, does it make sense to
philosophize about pursuing impossible goals?

~~~
eli_gottlieb
It's basically just thermodynamics: if you're willing to spend enough energy,
you can optimize the state an arbitrarily large system as you please.

Of course, the key words there are _enough energy_. It sounds like Thiel might
be forgetting to account for what we want to optimize and how much effort
we're willing to spend on it.

~~~
HiYaBarbie
> _if you 're willing to spend enough energy, you can optimize the state an
> arbitrarily large system as you please_

Define "optimize" and "system"?

~~~
eli_gottlieb
"System" \-- any bloody thing you care about, any collection of mass and
energy.

"Optimize" \-- to constrain the system to within a subset of its state-space.
Or in other words, to make only some things happen rather than all other
possible things.

Generally, as long as something is physically possible, you can spend some
amount of energy to make it reasonably probable or unreasonably improbable.
This may just be far more energy than you happen to have, or care to spend.

~~~
HiYaBarbie
So how does the 'optimization' work? :)

I have no clue about physics, so I'm just curious.

~~~
eli_gottlieb
It doesn't. It's really a deliberately vague term referring to any physical
action designed to put the system in one state rather than another. A
thermodynamically non-reversible action, you could say.

~~~
HiYaBarbie
Alright. Well, we're talking about something that might be theoretically
possible, but is impossible in practice. I don't think it matters.

------
bayesianhorse
Biotech companies don't risk so much randomness because they like it that way.
It's because without most of the randomness there is no possibility of
breakthroughs.

Still, optimizing experiment design through a balancing of bayesian
statistics, simulation and cost optimization may result in savings or less
capital risk.

------
cryoshon
Uhh, I think Thiel doesn't understand what is going on here. I am going to
respond to a few excerpts.

"The question is, can you change those probabilities into different numbers?
The reason we invested in Stemcentrx at a valuation that would have been
higher than many other biotechs we looked at is that we felt the whole company
was designed to get these probabilities as close to one as possible at every
step, to get rid of as much of this randomness or contingency as possible.
That is something that we found deeply reassuring."

Broadly speaking there are two strategies for drug research: shotgun, and
sniper rifle. If we're being honest, shotgun is the dominant method
specifically because 10 chances is far safer than 1 "really good" shot that
may or may not produce a really good drug. The one shot wonder shops usually
fail early stage when they can't produce a chain of positive data from one
funding round to the next. Biotech startups are longshots-- I would say that
they are probably even longer shots than a software shop specifically because
there can be unknown physical constraints of biology that can silently ruin an
otherwise great idea, leaving other people to make the exact same mistake
repeatedly after you're gone. Reducing inconsistency of your results is a core
of the scientific method, practiced everywhere, but doing so effectively is
hard when you don't have full understanding of any one component you work
with. It isn't random behavior, it's just not fully understood behavior.

"One of the very unusual things they do is graft human cancer into the mice.
It’s a somewhat more expensive way to do this than studying cancer in cell
culture. It’s a somewhat harder structure to build. But drugs tested this way
are much more likely to work in humans. They convinced me there is a
surprising amount that has gone wrong with the cancer cell lines people have
been studying. "

Literally everyone who is serious about making oncology drugs does this
technique. It's a staple. I guess it's "unusual" if you aren't accustomed to
the methods of biotechnology, but rest assured, this trick has been well-known
for quite a while-- it is not a magic bullet, but it's better than
alternatives. Cancer cell lines are known to be poor models in a number of
dimensions, which is great because we can anticipate their shortcomings. Mouse
models also have shortcomings that are somewhat well understood, but don't
confuse this for a slam dunk. There are still many (most?) cases in which
drugs developed from mice won't transfer to humans.

"But if biotech companies tend to invest money in ways that are pseudo random,
then a lot of it must get wasted. You end up doing things where you say, “I am
not sure it’s going to work.” Well, that sounds like a wasteful thing to do.
The standard excuse that biotech companies have is that, “We don’t know if
it’s going to work, so we have to do it this way.” That has to be
inefficient."

Is this guy serious? You're never sure if it's going to work in the
laboratory! Research is mostly "try something new, then try another new thing
when that fails." It's "wasteful" because it's guided trial and error, and you
don't have full totalitarian control over any of the variables. If you think
you are investing in a new biotech company (or old, really) that has escaped
this paradigm, I have a series of pyramids to sell you.

"This idea was very much in my mind by the time we invested in Stemcentrx in
2012. They had an annoyingly complicated problem, all these pieces you have to
bring together, and they said, “We are just going to do it ourselves.” That is
a mind-set that I very deeply share. I don’t want to name names, but there are
other companies where, in some ways, this was the key thing that failed."

All biotech problems are annoyingly complicated, and the prerequisites for
trying to solve problems are also annoyingly complicated. There are some
extremely well funded companies that can do everything in house, but it's the
wrong way to go about a startup-- even a lot of the larger biotechs contract
stuff extensively. Why have problems with simple things that should work when
you could contract them out and not worry? You can always bring that
capability online in parallel in your own company at a later stage when you
have more breathing room. It's a huge hassle to buy equipment, hire and train
your own people to perform a task that someone else can do better and cheaper.

"The big picture is the question of whether biological science can be
transformed into an information science. Can something that seems chaotic,
fractal, and generally random be transformed into something more deterministic
and more controlled?

"I think of aging and maybe just mortality as random things that go wrong. The
older you get, the more random things happen, the more breaks. If it’s not
cancer, you could get hit by an asteroid. So on some level, technology is
trying to overcome the randomness that is nature. That is a question on the
level of a company. Can you get rid of randomness in building a company? But
the philosophical version of the question is whether we can get rid of
randomness in its entirety and overcome the randomness that I think of as the
evil part of nature."

Nature isn't random! Nature is complex, cryptic, self-referential, and
chaotic, but it's deterministic at the level of biology. "Random things
happening" is not a proper understanding of age-related decline; aging is the
long-term compounding interest of metabolic byproducts. It really stuns me
that Thiel's understanding of these things is so apathetic to reality.

~~~
srunni
> You're never sure if it's going to work in the laboratory! Research is
> mostly "try something new, then try another new thing when that fails." It's
> "wasteful" because it's guided trial and error, and you don't have full
> totalitarian control over any of the variables. If you think you are
> investing in a new biotech company (or old, really) that has escaped this
> paradigm, I have a series of pyramids to sell you.

This is an application of Thiel's philosophy of making contrarian bets. From
his perspective, if you weren't incredulous about Stemcentrx in the way you
are, then he would have made the mistake of investing in something
incremental. Whether his contrarian bet turns out to be correct is something
that remains to be seen.

> Nature isn't random! Nature is complex, cryptic, self-referential, and
> chaotic, but it's deterministic at the level of biology.

I don't think this is exactly true. For example:
[https://en.wikipedia.org/wiki/Cellular_noise](https://en.wikipedia.org/wiki/Cellular_noise)

There are certainly many seemingly random aspects of biology that are actually
just a lack of understanding at the moment, but that doesn't mean there is no
fundamentally random behavior in biological systems.

~~~
toufka
The concept you're looking for is Stocastic [1]. The distinction between being
'stocastic' and 'random' is one of 'unpredictable & determined' vs '
unpredictable & undetermined'. Cell biology deals with (and utilizes) a few
stocastic processes, but that doesn't make those processes random. An
interesting test to differentiate the two (at least in biology) is what
happens when you run the simulation backwards - if the occurrence of an event
is still unpredictable in reverse, then it's 'random', if every causal
incident can be traced, it would generally be considered stochastic.

[1]
[https://en.wikipedia.org/wiki/Stochastic](https://en.wikipedia.org/wiki/Stochastic)

(edit to fix wording)

~~~
srunni
> The distinction between being 'stocastic' and 'random' is one of
> 'predictability & determined' vs 'undetermined'.

The first sentence on the page you linked to suggests otherwise:

> The term stochastic occurs...to describe events or systems that are
> _unpredictable_

~~~
toufka
Sorry, that was not a well-written wording. The intention was to demonstrate
the concept of 'predictability' not whether it was actually predictable.
Edited and fixed now.

~~~
srunni
> The distinction between being 'stocastic' and 'random' is one of
> 'unpredictable & determined' vs ' unpredictable & undetermined'

Also from that page you linked:

> a purely stochastic system is one whose state is randomly determined...it
> can be classified as non-deterministic (i.e., "random")

Also: [http://math.stackexchange.com/questions/114373/whats-the-
dif...](http://math.stackexchange.com/questions/114373/whats-the-difference-
between-stochastic-and-random)

> A variable is 'random'. A process is 'stochastic'. Apart from this
> difference the two words are synonyms

~~~
toufka
Huh. It seems different scientific fields use the word 'stochastic' in very
different ways.

The commenter, 'bgins' makes the point, "Random has many connotations (like
entropy), not at all equivalent, and is a more generic term usable outside
mathematics. Stochastic means nondeterministic or unpredictable. Random
generally means unrecognizable, not adhering to a pattern. A random variable
is also called a stochastic variable."

And user, 'Einnocent,' "Likewise, I've noticed that network theory tends to
refer to traffic as being stochastic. Such traffic, from the point of view of
a router, would be considered random, but of course each packet was
deterministically produced."

In the biochemical field (of which I'm familiar, though ignorant of the
others), I doubt anyone would say that gene expression is 'random', rather it
is 'stochastic', and their intention in choosing those words distinctly would
indicate that there are not just probabilistic, but physical limits to the
expression of a gene that constrain its probability space. And further, there
are generally deterministic (if unpredictable (though not entirely
independent) from to state) mechanisms which ultimately lead to gene
expression. Were I to say that the expression of gene A is 'random,' then it
would seem to imply that there is some minute chance that the result is a
billion copies of the gene, when physically, it might be impossible for the
cell to exist with that many proteins in it - or that the state of gene
expression at time t0 is entirely independent of expression at time t1, which
is also untrue. Both of these interpretations of biological processes are
misleading and wrong, though they are what is conjured when it is said that,
"gene expression is random." All the while, the number of copies is actually
dependent on knowable, measurable, if highly-noisy processes - what I've know
to be termed 'stochastic'.

~~~
srunni
> Were I to say that the expression of gene A is 'random,' then it would seem
> to imply that there is some minute chance that the result is a billion
> copies of the gene

Not at all (in mathematical terms, anyway). You can certainly define the
probability distribution of a random variable such that only certain values
are possible. This is known as its support:
[https://en.wikipedia.org/wiki/Support_(measure_theory)](https://en.wikipedia.org/wiki/Support_\(measure_theory\))

