Subject: Lilly: Why Singapore Is Right for Systems Biology
From: "Systems Biology"<[email-masked]>
To: [email-masked]
Date: Wed, 18 Apr 2007 11:24:59 -0700

SYSTEMS BIOLOGY - Tools, Strategies, and Companies Driving Integrative Biology        

*Lilly: Why Singapore Is Right for Systems Biology*
 _By John Russell _  

_Eli Lilly recently announced a $150-million, five-year expansion of
its systems biology center in Singapore, being developed in
partnership with the Singapore Economic Development Board. No doubt
having such a generous partner influenced Lilly's decision. But
William Chin, Lilly's vice president of discovery, says the
Indianapolis, Ind.-based big pharma sees Singapore as a talent-rich
location ready to take the next step in drug discovery; Singapore is
also a natural gateway to the region's large and promising markets. He
talked with_ SBNL _editor John Russell about why Lilly thinks
Singapore is right for systems biology (SB) and what the company hopes
to achieve._  

*SBNL: Let's turn to the Singapore facility and the $150-million
investment Lilly has announced. What's the background?* 

*Chin:* We went into Singapore because we had previous experience in
this island country. We established a Phase I clinical trial unit in
collaboration with National University of Singapore in 1996, and that
unit really has focused largely on Phase I trials. In fact, we have
done perhaps over 100 such trials there. So when we were thinking
about how we were going to augment our focus on systems biology, how
we were going to augment our strengths in informatics and in
computational sciences, it was already in our thinking. 

It may not seem like an obvious place because, well, why wouldn't we
do it in Boston or in San Diego? Singapore came up as a possibility
because of the following two things. One is the understanding that
there is a lot of talent in the Pacific Rim, in which we also include
south Asia, and wouldn't it be very interesting and important to be
able to capture the talent in areas that are not traditional -- like
pure mathematicians or physicists or engineers -- and use Singapore as
sort of an integrator of this kind of talent? 

The other [factor] was, could we take this and somehow interact with
our Phase I client? So remember, our big challenge is translational
medicine, and you've heard a lot about that, and how do you take the
information that we would gain through understanding systems better to
be able to translate better. We always had a hope that we might be
able to bridge the two. We were very pleased with the results of the
[organizational] experiment because we didn't know, for instance, how
easy it was it to interact 11, 12 time zones away. 

*SBNL: Right.* 

*Chin:* Initially, I have to tell you, it wasn't easy because I
remember having meetings sitting doing a teleconference at 10 o'clock
in the evening here in Indy to communicate appropriately there in
Singapore. It took a lot of energy. I always said that if there were a
great breakthrough, the great breakthrough to me would be not all the
electronics and electrons moving, but if somebody can figure out how
to break down the time zone problem. 

*SBNL: When encountering that communication challenge, did you take
any special effort such as a high-speed video connection, etc?* 

*Chin:* Certainly we had very good video communications, you know,
obviously seeing faces and so forth which helped initially, and as we
grew. Then at the five-year period we asked, What are we going to do
now? So much has happened in the region. We have now had much more
discovery, drug discovery efforts in China and in India, and, for
instance, we have a fairly large chemistry group called Chem Explorer
in Shanghai, and we have a number of collaborations with companies in
India, including Jubilant. It's a very, very, very fine informatics
group. 

*SBNL: Yes, I'm familiar with Jubilant.* 

*Chin:* Then it closes back in saying, Look, how do we utilize the
real wonderful center we have in systems biology in Singapore and then
be able to further augment that? And so what we've done in the growth,
in planned growth in Singapore, is to actually augment our integrated
informatics capabilities, so we're growing that. So while the name has
changed (Lilly Singapore Centre for Drug Discovery[14]), really the
key emphasis is we're continuing to grow our informatics capabilities,
which allows us to increase our capabilities in biomarkers and also in
modeling. 

We also had an excellent relationship with the government with the
economics development board, and so it's about established
relationships. 

*SBNL: How much of your time is currently spent in Singapore?* 

*Chin:* I travel there at least twice a year, and certainly my group
and I have a number of vice-presidents who in some senses share
responsibility, but I have a couple of leaders who are responsible for
that unit. 

*SBNL: Tell me a little bit about what systems biology means to Lilly,
and then we can talk about changes at the Singapore center.* 

*Chin:* Clearly what we face as an industry and what Lilly faces
specifically is the challenge of identifying and developing targets
and drugs that will help patients with their health outcomes. Right
now, there's a big gulf there, isn't there?  So, for example, taking
the idea of a genetic defect in a particular gene and trying to
understand, then, [whether] that target going to be useful,
ultimately, in producing a drug for a particular disease. The gulf is
tremendous in terms of cost and in time that it takes to develop
drugs. That's why we, Lilly, but also the industry, are looking for
ways to bridge that chasm, and obviously biomarkers is one of those
ways. 

*SBNL: I think your description is consistent with what others say. * 

*Chin:* The way we look at it is that if we can understand systems
within preclinical, in preclinical models -- so, for instance, if
we're interested in some biology in the beta cell of the pancreas in
the rat -- what will translate? That is, what will be relevant to
disease in human patients? We think that targets may translate over,
but that may not be as certain as pathways or system sets that
translate over. 

You start with target 'x,' you don't know the connection fully with
target 'x' prime in humans, right, so animals to humans. So we test
the hypothesis in rats and mice, asking the question whether it'll be
useful in humans. If we could just bridge that gulf a little bit
better, if we could be more predictive, shall we say, then we'd be
much better off. And so I think it turns out for us, we think that
looking at pathways and systems is a better way of doing it. The whole
idea is that these systems and pathways are probably better conserved
than any single molecular target. 

*SBNL: Is this new thinking at Lilly?* 

*Chin:* You know, in many senses, if you're sort of cynical, people
would say this is old-time physiology. Physiologists knew that
everything was connected to each other, but what we did not know was
precisely what those connections were. Now, we're able [to do that]
because we're able to handle more information either from gene arrays
or proteomics. We're able to tie together systems a bit better, and
this is looking at systems in a normal setting. 

The advantage we have in the pharmaceutical industry is that we create
potential drugs that perturb a system, right, and so then you can ask
if I perturb particular target, a particular target in a pathway, what
will happen? We're beginning to have some examples where we can
actually be predictive, where we know when you perturb a particular
pathway, you're actually going to act on disease and then be able to
say that drug might have activity in disease. 

_continued below ad_        

[15]        

__ 

_continued_  

*SBNL: Obviously it would be wonderful to take these data sets from
experiments to create simulation platforms where you could play
"what-if" games.* 

*Chin:* Exactly. So you're talking about what we refer to more simply
as molecular modeling. But it's also pathway modeling, you know,
modeling of the systems. We even think of disease state modeling, so
you can see almost a continuum, each step leading to more complexity,
of course. If you focus on a particular area you might be able to be
predictive. [There's] a model called the Archimedes model -- it's a
project largely emanating from the Kaiser Permanente healthcare group
in California. They have a number of folks who, using clinical data,
have been trying to create a model in which if you could modulate a
certain part of physiology you could help regulate diabetes. The whole
concept of disease state modeling is very important to us. 

*SBNL: Does Lilly do most model building internally, or are you using
collaborators such as Entelos, Gene Network Sciences, and companies
like that? * 

*Chin:* We actually realized that we can't do it ourselves. I guess we
knew this. We should have known that a long, long time ago, but we now
actually create a network ourselves of academia, of small companies
such as Entelos, and our own efforts such as the one we have in
Singapore, so it's a collection of activities. 

*SBNL: How about ties with academic researchers?* 

*Chin:* Well, we have several advisors, and I think you may know at
least one or two of these, but one is Doug Lauffenburger. Doug has
been with us since the center's inception. There's Gary Nolan at
Stanford, and then Edison Liu who is at the Genome Institute of
Singapore. These three advisors obviously played important roles in
systems biology.  

I particularly like how Gary Nolan thinks about systems. You've heard
him talk about the systems of the network very much like a spider web.
In fact, I think you have a company called Nodality, that talks about
how if you think about a web there are many sort of connections,
right, and so they're all interconnected, so a spider sitting in one
spot can actually tell precisely, for instance, when an insect has
landed somewhere else on the web and knows how to pretty quickly get
to it. It's that interconnectedness and how you understand
relationships that are important and then, ultimately, to be able to
predict what might happen if you perturbed one. 

*SBNL: How long has Lilly had the systems biology effort in
Singapore ?* 

*Chin:* Our systems biology center has been in existence for almost
five years now, since 2002, and so we have developed enough experience
to realize that this work can be extremely useful. Again developing
new markers, we've developed a good number of new markers that are
proprietary. 

*SBNL: Can you tell the areas, at least, in which those markers are?* 

*Chin:* I can say they are largely in cancer. And, we have, for
instance, utilized some of this information for pharmacokinetics,
pharmacodynamic modeling in a particular cancer program, which has
allowed us, for instance, to help convince the regulatory agency, the
FDA, that as we enter the clinic that we have chosen the right doses. 

*SBNL: FDA is pretty enthusiastic about using PD/PK modeling, and they
have this huge database.* 

*Chin:* They do, and the database is not privy to any particular
pharmaceutical company. It's a collective experience. If you'll permit
me to editorialize, I think this is something we as an industry need
to do much more of. That is, be able to share, encourage FDA somehow
to create a consortium so that these data can be useful for everybody. 

*SBNL: One interesting thing to think about in systems biology is,
will it be most effective housed in the centers or does the next step
need to be spreading SB into therapeutic research groups?* 

*Chin:* Ultimately you're correct. I think it has to be spread out and
be used in that way, but I think it's also critical that you develop a
critical mass of people who are quite adept in these computational
science efforts to partner with [experimentalists]. It's an iterative
learning process, right? It's not a matter of handing over a problem
to an informatics group. It's a circular thing where you do something,
you learn something, go back to other scientists within the company,
and then you may even refine the question. 

In many ways system biology is sort of a paradigm for what we do in
our business because we all need to be interacting and integrating our
activities together. 

*SBNL: So you've come to the five-year point - 2007 -- and you think
proven value, and decide to move forward with this substantial
expansion investment in Singapore. What are the near-term and
short-term goals for the center?* 

*Chin:* Yes. Well, we want to continue our biomarker discovery
efforts, again focusing on cancer. We'd like to expand also in the
area of metabolism, which is largely diabetes. These are two areas
that are important for us. We'd also like to be able to develop the
additional capabilities of actually developing drugs in the region.
The region is also very interested in translational medicine. In fact,
they've invested heavily in that, including imaging. They brought very
senior individuals, world leaders in imaging. I believe Siemens is now
coming in. We hope to be able to capitalize on all this. 

*SBNL: The Singapore Biopolis.* 

*Chin:* Exactly. Have you been there? 

*SBNL: I've been to Shanghai, but not Singapore.* 

*Chin:* It's an amazing place. Yeah, so to capitalize on the Biopolis
systems and what the university is trying to do, the government's
trying to do in terms of really fostering the bridging of this gulf. 

*SBNL: So the biomarker activity, I'm guessing, encompasses many
different kinds of biomarkers such gene expression and proteomics.
It's not focused on just one of those technologies. Is that correct?* 

*Chin:* That is correct. Ideally, serum markers would be great, but
clearly we're also looking at -- in the case of cancer -- tumor gene
expression signatures, for instance. You know, all things that
everybody's aware of in the field. 

*SBNL: Are you open to additional collaborations with commercial
technology providers? And how do they identify opportunities inside
Lilly?* 

*Chin:* Well, we're always interested in interacting with
collaborators. As part of our center of systems biology we have
interacted with the Broad Institute and with TGen. We're always
looking for partners who can help us in this process. You mentioned
Entelos, and they're not so -- or we're not so -- specialized in the
cancer area, but Optimata and GNS are two companies who are and have
had some success in those areas. So yes, we are actively working with
collaborators. 

*SBNL: Thanks for your time.*        

[16]   

** 

*Email to a Friend*        

*Commentary*    

*Is Systems Biology at a Crossroads?
 *_By John Russell_ 

It's been suggested to me that systems biology (SB) may be headed to a
crossroads. That early advocates such as Novartis and GSK are
basically abandoning it as a distinct focus, while newer-comers such
as Pfizer and Johnson & Johnson are simply a year or two from coming
to the same conclusion and will abandon or de-emphasize SB.  

I'm also told that Lilly's $150-million expansion of its Singapore SB
initiative is more about getting matching funds from Singapore than
driving SB -- though Lilly's global head of discovery, Bill Chin,
makes a strong case otherwise in an interview in this issue of SBNL.
(Maybe the complaint was simply sour grapes.) 

Stir into this bubbling stew the ongoing difficulties SB technology
providers have had developing proven business models and it seems like
a good time to ask, Where is SB headed? Is enthusiasm waxing or
waning? Are we in for tougher times in the short term (six-to-twelve
months) and a rebound longer-term? 

There are definitely mixed messages in the market. _SBNL/Bio-IT World_
plans to publish a deeper look at the systems biology landscape later
this spring. Here are quotes gathered in the early stages of
researching this article from five very senior SB authorities spanning
academia, pharma, and SB technology providers. For the moment, they'll
go unidentified: 

1. "Some of the changes affecting SB within big pharma are driven by a
myriad of causes: from budget cuts from the failure of a single drug,
to the politics of a new research head in place, to semantics of the
name of a department or function. And so it is hard to read a lot into
each piece of news." 

2. "I am entirely confident about the bright future of systems
biology, even if some pharmas bail out in the short run. This is a
long-term revolutionary approach to biology, so it is patently
unfeasible for it to 'dissipate'." 

3. "Many companies are successfully doing SB type studies without
calling it that way, having a SB department, or even anyone with a SB
title. I think this is the (pre)maturing of the space. Not so
different from when the Internet came and companies had these small
departments of Internet geeks." 

4. "I believe the 21st century will become the era of 'dry biology'. I
have been to too many SB conferences reporting work where huge
databases are created with no clue about what the question is and how
to make heads and tails of this gigantic information." 

5. "My take on this is the groups that are failing are [those] that
are exclusively focused on computational areas, and the groups that
are succeeding or getting by are [those] that combine some wet lab
work with computational approaches." 

Stay tuned for the "SB at the Crossroads" analysis. What are your
thoughts on present and future systems biology? Tell me at [email-masked].
 [17]                  

*SBNL ARCHIVES*    

Towards a Cancer Interactome[18]
March 21, 2007 

Entelos Strikes In-Licensing Deal with J&J
 [19]February 14, 2007 

Burning Questions in SB; Executives Look Ahead; Trends[20]
January 10, 2007  

The Novartis Conjurer; Outlook 2007: SB Execs Survey; Trends[21]
December 13, 2006  

Systems Biology DREAM(s) Big[22]
November 13, 2006 

Pfizer SB Chief David de Graaf Looks Back and Ahead 
 [23]October 18, 2006  

SB in the Hot Seat; Regulomics Conference[24] 
September 13, 2006  

Pfizer's Progress, GNS Growth, and more[25]
August 24, 2006  

Conversation with Genstruct's Keith Elliston[26] 
July 27, 2006  

Sunrise for Systems Biology[27] 
June 15, 2006  

*Bio-IT World SB Links* 

Pathway Pioneers[28] 

Marvelous Models of Biological Systems[29] 

Pharsight Lands CRADA to Assist FDA with Modeling Initiative[30] 

FDA Mulls Drug/Disease Model Library[31] 

Welcome MIRIAM: Researchers Propose Modeling Standard[32]           

*Contact the Editor*     

We invite your comments and feedback for this edition of _Systems
Biology_. 
 John Russell
 [33]Executive Editor                                     

[34]Published by Bio-IT World[35] Copyright &copy; 2007, a business of Cambridge
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reprints and/or copyright permission, please contact RMS, 1808
Colonial Village Lane, Lancaster, PA; 17601 (717) 399-1900 ext. 128,
or email: [email-masked][37]         

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