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Open-source research, which started as a
counterculture movement in the software
industry 15 years ago, has since grown into a
business model whose best-known product,
Linux, has become a credible alternative to
Microsoft’s Windows. Now, with biology
increasingly becoming an information-
orientated science, some have suggested
that what worked for software might be part
of the answer to the spiralling cost of drug
R&D. With this in mind, this article exam-
ines the relevance to pharmaceutical R&D
of the open-source model developed by the
software industry. In this context, open-
source no longer refers to source code, but
instead to the open origin of contributors.
Open-source R&D has already made
inroads into bioinformatics and research
tools for drug hunters. However, key
differences between software and biology,
such as regulatory requirements, have
limited its application to drug development.
Nevertheless, in the past 5 years a new
breed of organizations called public–private
partnerships (PPPs) have adapted the
open-source concept and combined it with
outsourcing to create a new, low-cost
business model, which they have applied
with encouraging results to the discovery
of new treatments for neglected diseases.
Advances in data mining, visualization
and networking now make it feasible to go
one step further. It is possible to offer scien-
tists a computerized toolbox that lets them
harness the creativity of numerous volunteers
to address the key questions that are holding
back innovation. For example, what is the
aetiology of a disease? What are the pathways
involved? What are the better targets? Once
these questions are answered, laboratory and
clinical studies can be outsourced to institu-
tions with the requisite capacity through the
help of matchmaking software.
The resulting model is a hybrid in which
a part of R&D is open-sourced while the
rest is outsourced. To function, however,
it needs strong project leadership and
expertise in the minutia of drug R&D,
which mostly exist in big pharmaceutical
firms. This suggests that, far from being
a threat to conventional drug R&D,
open-source could be a way to leverage
big pharma’s capabilities in order to tackle
challenges that the blockbuster model can-
not address economically, such as neglected
diseases. As pharmacogenomics takes hold,
it might also be a way to address market
niches that cannot support blockbusters.
A brief primer on open-source
Open-source R&D is a novel approach to
research that lets scientists join hands freely
across organizations, disciplines and borders
to solve problems in which they share an
interest. The movement’s icon is Linux, the
operating system started in the early 1990s by
student Linus Torvalds, who used the nascent
Internet to circulate it to fellow computer
enthusiasts. Soon they were busy adding fea-
tures and improving the code, with Torvalds
overseeing the process. Fifteen years later,
this grassroots experiment has blossomed
into a new culture that is spreading to other
disciplines. It is most prominent in computer
software development, for which dedicated
websites such as such as SourceForge or
Subversion help over a million people
collaborate on more than 100,000 projects.
But other areas, such as life sciences, have
spawned open-source initiatives of their own.
The impetus to create open-source soft-
ware often comes from developers looking for
challenge. They agree on an attractive project,
form a team and produce a ‘bare-bones’ pro-
gram with basic functionality. Then, they offer
it at no cost on the Internet under a public-
domain license (there are many different
types of open-source license; some, notably
the ‘copyleft’ or General Public License (GPL),
require those who download a program to
share any improvements they make). If the
project draws interest, others add features and
post their code on the project’s webpage for
fellow programmers to critique. New code of
sufficient quality is added to the authorized
version of the program.
Open-source’s chief benefit is to cross-
fertilize minds and tap creativity quickly,
cheaply and on a scale that is beyond the reach
of scientists working in the ‘ivory towers’ of
academia or behind the ‘corporate moats’
of industry. Hollingsworth1,2 has shown that
innovation spikes when diverse minds interact
frequently in an unstructured manner. By
drawing talent from all around the world,
open-source research takes these dynamics
to a new scale. And by making innovation
immediately available to all, it speeds up the
accumulation and application of knowledge.
Outsiders are often puzzled by the open-
source idea. Why would anyone work for
free? Simply put, because some people value
non-cash compensation more than money.
They volunteer their expertise to satisfy ideal-
ism or curiosity, seek new challenges, hone
skills, build a reputation or enhance careers.
Feldman3 quotes the example of Australian
programmers who, within hours of Netscape’s
release of its browser code, attached an
‘add-on’ to enable secure internet transactions.
No money changed hands, but the authors
received respect from the programming com-
munity and the satisfaction of turning out an
elegant and useful piece of software.
Companies are learning to use open-
source to their advantage, and many now
allow their employees to participate on com-
pany time. They might use it to gain market
share against entrenched competitors, or
OUTLOOK
Can open-source R&D reinvigorate
drug research?
Bernard Munos
Abstract | The low number of novel therapeutics approved by the US FDA in recent
years continues to cause great concern about productivity and declining innovation .
Can open-source drug research and development, using principles pioneered by
the highly successful open-source software movement, help revive the industr y?
PERSPECTIVES
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Nature Reviews Drug Discovery
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AOP, published online 18 August 2006; doi:10.1038/nrd2131
PSAC
antagonist
Dihydrofolate
reductase
Novel
macrolides
Isoquine
(improved
aminoquinoline)
OZ + PQP
RBx11160/
OZ277
+ piperaquine
Chlorproguanil-
dapsone
(Lapdap)
-artesunate (CDA)
Lead
identification
Lead
optimization Transition Phase I Phase II
Pf enoyl-ACP
reductase
(Fab i)
New
dicationic
molecules
4(1H)-
pyridones
Backups
AQ-13 new
aminoquinoline
Paediatric
coartem
Cyclofarnesyl
sequiterpenes
Pf protein
farnesyl-
transferase
(Pf-PFT)
Falcipain
(cysteine
protease)
Pyronaridine–
artesunate
Next
generation
antimalarials
Entantio-
selective
8-amino-
quinolines
EuArtekin (dihydroartemisinin–piperaquine)
Novel
imidazolidine
-diones
MMV active support ended MMV/GSK portfolio New projects to be added
Exploratory Discovery Preclinical Clinical development
Phase III
to entice developers to create applications
for their product, possibly in the hope of
turning it into a ‘platform’. Some of them
have been quite successful at turning open-
source into profits. Red Hat, for instance,
has attained a US$5-billion market cap from
selling support services for Linux.
Can it work for drugs?
If biomedical scientists could adapt the
open-source model, it could make a huge
difference to such projects as developing
drugs for neglected diseases, for which
needs are great but funds are scarce4. Only
10% of R&D resources are spent on illnesses
that represent 90% of the burden of disease.
Open-source drug R&D might not change
that equation, but could make it possible
to get much more from that 10%.
There are, however, significant barriers to
the deployment of open-source approaches
to drug R&D5. One is economic. All it takes
to write open-source software is a laptop and
an internet connection. With drug research,
someone must pay for laboratory expenses
and clinical trials. And the costs are high, at
more than US$800 million for the discovery
and development of a novel drug by most
estimates.
Research dynamics between the two indus-
tries also differ. Software development does
not have a discovery phase. Once the objective
is set, programmers set to work and make
steady progress towards their goal. By contrast,
drug discovery cannot flourish until a certain
amount of knowledge about the target disease
has been accumulated. That knowledge
acquisition can take years or decades, with no
way to know at the outset whether the store
of knowledge at hand is nearly sufficient or
will require years of painstaking additional
research before innovation can thrive.
Software development is also simpler:
it spans only a few disciplines and has no
equivalent to clinical trials. For the most
part, a single programmer can master all the
skills needed to write a program from start
to finish. By contrast, drug development
requires coordination of multiple specialties
with little overlap. Biomedical knowledge,
which grows at the rate of 1,000 publications
per day, must be peer-reviewed and repli-
cated before it is accepted. All this is slow
and enormously expensive.
Drug R&D can go off-track more easily
than software programming. Biologists
can get mired in the complexity of biology
without ever making much progress towards
a drug — chemists handed the wrong target
cannot do much good no matter how hard
they try; inadequate toxicology can derail
a compound late in development, or even
after launch. One misstep along the way can
render all downstream work useless.
In contrast to drug developers, software
publishers are lightly regulated. They do
not need FDA approval. The quality stand-
ards they face are far less onerous than the
minutia of Good Laboratory Practice
(GLP), Good Clinical Practice (GCP) and
Good Manufacturing Practice (GMP).
One sloppy programmer seldom jeopardizes
the achievements of others, and errors can
be patched without requiring the rewrite of
the whole program. With drugs, one care-
less worker can compromise years of work
costing tens of million of dollars.
Finally, the two industries follow different
intellectual property regimes. Software is
protected by copyrights that arise automati-
cally as code is written, even if nothing is
filed. Drug research is protected by patents
that are costly to file and maintain, and
for which meeting the legal standards that
define innovation is much harder.
Open-source biomedical research
Early efforts. Despite these differences, the
open-source idea has entered biomedical
research6. The first inroads were made in bio-
informatics7,8 , as might have been expected.
These efforts resulted in a collection of pro-
grams such as Biojava, BioPerl, BioPython,
Bio-SPICE, BioRuby and Simple Molecular
Mechanics for Proteins9, and inspired other
initiatives such as the Human Genome
Project, the SNP Consortium, the Alliance
for Cellular Signaling, BioForge, GMOD
and Massachusetts Institute of Technology’s
BioBricks (some of these have the transpar-
ency and feel of open-source, although the
resources needed to get involved do not allow
all volunteers to participate; however, we still
call them ‘open-source’).
An old idea. One could argue that there has
long been an active, if invisible, collabora-
tive process akin to open-source in drug
development, as, for some diseases, half
of all prescriptions are for off-label uses10 .
Somehow, physicians share their ideas and
experiences informally to uncover novel
uses for existing medicines. For instance,
oncologists routinely use drugs approved for
one kind of cancer to treat other types. In a
recent study, DeMonaco11 found that 59% of
drug therapy innovations were discovered
by practicing clinicians via field discovery.
The way by which physicians uncover these
new indications is quick and inexpensive
compared with Phase III trials. From an eco-
nomic and medical standpoint, there would
be merit in exploiting these clinical observa-
tions and sharing them with physicians as a
complement to, or replacement for, some of
the traditional clinical development.
Public–private partnerships. Taking a different
approach, a new kind of organization, known
as the public–private partnership (PPP), has
recently developed a clever virtual business
model that emulates the collaborative features
of the open-source concept12 . An example is
Figure 1 | Portfolio of the Medicines for Malaria Venture. PSAC, plasmodial surface anion
channel.
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Director, Drug Discovery
and Technology
Contracts Officer
Administrative Assistant
Director, Clinical
Development
Director, Clinical
Development
Associate Director,
Clinical Development
CEO
Administrative Assistant
Communication
and Advocacy Officer
Chief Scientific Officer
Chief Finance Officer and
Donor Relations
Human Resources Officer
Director, International Ops
the Medicines for Malaria Venture (MMV),
which was established in 1999 to discover and
develop new, affordable antimalarial drugs.
Established as a nonprofit entity with a staff
of only 13 people, it has assembled a portfolio
of 19 projects ranging from discovery to
Phase III (FIG. 1).
MMV gets its projects through open
calls — anyone with an idea can contribute.
An Expert Scientific Advisory Committee
reviews the submissions and selects the
projects that will be funded. Each is managed
by a project manager who outsources the
R&D to a network of 300 scientists at 40 insti-
tutions (universities, big pharma, biotechs
and research institutes). Funding comes from
public and philanthropic partners (BOX 1).
After each step, the Scientific Advisory
Committee reviews the data and decides
whether to proceed or terminate the project.
MMV’s cumulative spend from 2000 through
2005 is about US$100 million, 90% of which
funded actual research. MMV plans to out-
source manufacturing to low-cost partners,
sell drugs at cost to developing countries, and
market them through partners in developed
markets (for example, to treat travellers).
Its alliance with GlaxoSmithKline supports
25 scientists funded equally by the partners.
The Initiative on Public–Private
Partnerships for Health reckons that there
are about 24 PPPs engaged in drug and
vaccine R&D (TABLE 1). Most of them were
created in the past 7 years and share a com-
mon profile13. First, they focus on neglected
diseases. Second, they operate as virtual drug
companies, with a small staff getting project
ideas from outside, vetting them through a
committee of experts and outsourcing R&D
to a network of institutions. Third, they man-
age growing portfolios of projects ranging
from discovery through to Phase III trials.
Fourth, they have been able to function on
lean budgets with a cumulative spending
that seldom exceeds US$50 million. This
makes them attractive vehicles to fund
research in areas that are not economical for
traditional drug R&D.
By the end of 2005, PPPs had attracted
funding in excess of US$1.5 billion.
Foundations have given about US$1.15 billion
(with the Gates Foundation alone contributing
more than US$950 million), governments
US$244 million and private entities US$36
million. In addition, donors have committed
another US$3.5 billion which will be
disbursed as needed by The Global Fund to
Fight AIDS, Tuberculosis and Malaria.
Open-source versus alliance networks. It can
be argued that the 25,000 alliances wrought
by the 8,000 pharma and biotech companies
over the past 15 years add up to a vast open-
innovation system that mimics the collabo-
rative features of the open-source model.
Some scholars have countered, however, that
alliances are less effective than open-source
research at promoting innovation. This is
because open-source networks are richer in
‘weak links’ (loose relationships), whereas
alliances pride themselves on the strength
of the connections between partners.
DeBresson14 has shown that weak links bring
novel ideas into the fray whereas strong links
tend to reinforce orthodoxies.
PPPs and big pharmas. TAB LE 2 lists some of
the projects and organizations coordinated
by PPPs. As can be seen, GlaxoSmithKline
features prominently, with Bristol-Myers
Squibb, Novartis, Bayer, Sanofi-Aventis and
Ranbaxy involved to a lesser extent.
Lessons learned
PPPs have advantages and drawbacks
compared with traditional R&D15. Advantages
include the following.
Box 1 | The Medicines for Malaria Venture
Management team
The Medicin es for Malaria Venture (MMV) i s run by a staff of 13. Its CEO repo rts to a Board of 12
Directors who represent funding organizations. An Expert Scientific Advisory Committee, which
includes chemists, biologist s, clinicians, malariologists and drug development exper ts, advises on
project sel ection and research stra tegy. The Manag ement Team’s responsi bilities are to:
• Encourage the s ubmission of research pro posals
• Select proposals and negotiate with partners
• Set up project-mana gement teams and mon itor progress
• Organize manuf acturing and mar keting
• Earn appropriate returns from marketed products
• Raise funds
• Communicate with government agencies
Backers
• Gates Foundation
• BHP Billiton
• ExxonMobil
• Global Forum for Health Research
• International Federation of Pharmaceutical Manufacturers Associations
• Netherlands Minister for Development Cooperation
• Rockefel ler Foundati on
• Swiss Agenc y for Development and Co operation
• United Kingdo m Department for I nternational Develop ment
• United States Agency for International Development
• World Bank
• Wellc ome Trus t
• World Healt h Organ izati on
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Agility. Virtual R&D makes it easier to
terminate projects that no longer look
promising. The project manager does not
have to deal with entrenched advocates
manoeuvering to save their project or move
it underground.
Creativity. PPPs enable experts from dif-
ferent countries, specialties and styles of
thought to leverage each other’s ideas. They
harness the problem-solving skills of a much
greater population than is typically available
to traditional research organizations.
Focus. PPPs focus on one or few diseases.
This helps them build deep expertise for better
decisions (for example, target selection).
Risk sharing. The open-innovation
model of PPPs makes it easier for scientists
to collaborate on pre-commercial research
such as biomarkers or cell signalling.
Affordability. PPPs lower the critical mass
required to be a pharmaceutical company. By
leveraging external expertise and capabilities,
they allow small organizations to do much of
what was once the domain of large companies.
Impact. PPPs engage scientists in developing
nations who have first-hand experience in
many neglected diseases. It helps them build
their clinical research capacity, which in turn
leverages the effectiveness of their public
health systems.
Speed. Lean PPPs can decide quickly, partly
because they do not have layers of committees
to satisfy. In addition, because they tap their
partner’s unused capacity, they can advance
swiftly as there is often a qualified laboratory
somewhere that can do the work without
having to wait in someone else’s queue.
There are also some disadvantages to PPPs,
which include the following.
Funding. US$5 billion has been committed
to PPPs ($1.5 billion disbursed). However,
despite the thriftiness of PPPs, there is
concern that these funds will be stretched
as more projects move into late, expensive
clinical development.
Sustainability. PPPs have not demon-
strated the sustainability of their business
model. Some of their projects come from
companies that had shelved them because
of insufficient commercial prospects. To
survive, PPPs will need to replenish their
portfolios. There are also worries that, in
some areas of science, the pool of contribu-
tors might be too thin to perform the work
that must be done.
TABLE 3 shows that the PPP R&D model
has worked reasonably well. Some of this
success comes from targeting low-hanging
fruits in diseases that have long been
neglected, but it also suggests that the PPP
model can be a potent tool in finding new
cures. Whether the PPP business model
becomes a transformational force or
remains a non-threatening niche depends
on how it ultimately performs against
traditional pharmaceutical R&D. To
succeed, it must go beyond tools and soft-
ware and tackle large projects where it will
rival the big firms that are helping it today.
Yet, this rivalry need not be a zero-sum
game. On the contrary, there is a place for
collaborative and proprietary research in
drug R&D, just as in software16. If open-
source drug R&D takes hold, what will
probably emerge is not the replacement of
one model by another, but an ecology in
which big pharma, biotech and collabora-
tive research compete and collaborate at
the same time, feeding off each other
synergistically, while moving towards
therapies along their own distinctive paths.
A template for open-source drug R&D
Can the PPP model succeed beyond
neglected diseases? To answer this, it helps to
break down drug R&D into knowledge-based
activities and rule-based tasks.
Table 1 | Public–private partnerships engaged in drug and vaccine development
Name Focus Year created
Aeras Global T B Vaccine Foundatio n Tuberculosis 1997
BIO Ventures for Glob al Health Biotech drug s for neglected
diseases
2004
Consor tium for Industrial Colla boration in
Contraceptive Research
Development of new
contraceptives
1995
Contraceptive Research and Development Improving reproductive h ealth in
developing countries
1986
Dengue Vaccine Projec t Dengue feve r 1989
Drugs for Ne glected Diseases Initiati ve Sleeping sick ness, visceral
leishmaniasis, Chagas disease
2003
European Malar ia Vaccine Initiative Malaria 1998
Gates Foundati on–UNC Partn ership for
Development of N ew Drugs
African tr ypanosomiasis,
leishmaniasis
2000
Global Alliance for TB Tuberculosis 2000
Global Microbicide Project New microcides for women 2000
Human Hook worm Vaccine Initiative Hookworm 2000
Infectious Disease Research Institute Tuberculosis, leishmaniasis,
Chagas disease, malaria, leprosy
and Buruli ulcer
1993
Institute for One World Health Visceral leishmaniasis, cutaneous
leishmaniasis, Chagas disease,
paediatric secretory diarrhoea
2000
Internatio nal AIDS Vaccine Initiative AIDS 1996
Internation al Partnership for Micro bicides HIV 2002
Japanese Pharmaceutical, Ministry of
Health, WHO Mal aria Drug Partner ship
Malaria 1999
Lapdap Antimalarial Product Development Malaria 1998
Lassa Fever I nitiative Lassa feve r 2001
Malaria Vaccine Initiative Malaria 1999
Medicines for Mal aria Venture Malaria 1999
Meningitis Meningitis 2001
Microbicides Development Programme HIV 2001
Pediatric Dengue Vaccine In itiative Dengue 2001
PneumoADIP Pneumococcal vaccines 2004
UNC, Un iversity of No rth Carolina; WH O, World Health Organ ization.
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Knowledge-based work requires lots
of intelligence and intuition, but little
infrastructure. Examples include identifying
targets, understanding metabolic networks,
and designing clinical trials or computer-
ized disease models. It is about scientists
leveraging each other’s ideas, and using
tools to gain deeper insights that might lead
to breakthroughs. This work is ideally
suited to the open-source model.
Rule-based work requires physical assets
(laboratories, equipment, patients and so on)
and money. It is tightly scripted and must
conform to rigid regulatory requirements.
It is about organization, discipline and
implementation. Examples include toxicol-
ogy studies, Chemistry Manufacturing and
Controls (CMC) studies, and the conduct
of clinical trials. Rule-based work is ideally
suited to outsourcing, and much of it is
already outsourced to contract research
organizations.
This division of labour suggests a busi-
ness model template in which part of the
R&D value chain is open-sourced, while
the rest is outsourced, with the following
features.
Template features: operating principles
Open-sourcing. The open-source part of
our model should allow anyone who can
contribute to join. Volunteers should be
able to log on to a website, find the page(s)
that matches their area of expertise, peruse
challenges to be solved, review others’ con-
tributions, download computerized tools
and start working towards contributions of
their own. As they progress, they can pub-
lish their findings in scientific journals and
discuss their insights in on-line forums.
Over time, the better ones will gain authority
and become the de facto leaders of their
open-source community.
Outsourcing. Work to be outsourced
should be posted on a website for all to see.
Scientists and organizations qualified for the
job can bid, and the sponsor picks the best
candidate for each task.
Template features: procedures
Governance. Three decision-making bodies
provide leadership and guidance: the Board
of Directors, the Steering Committee
and the Scientific Advisory Committee.
The Board of Directors includes senior
executives and outsiders who represent
shareholders and stakeholders. It approves
strategy and ensures that management
performance is consistent with the organi-
zation’s mission. The Steering Committee
is a group of senior executives that rules
on important operational issues such
as fundraising, budgets, project funding,
key hires and selection of partners.
It also approves recommendations from
the Scientific Advisory Committee. The
Scientific Advisory Committee (SAC) is a
group of external experts from academia
and industry. It sets R&D strategy, proposes
new projects, reviews existing ones and
recommends termination of those that no
longer deserve support.
Scope. This template calls for focusing
on single diseases or related illnesses.
An organization working on unrelated
diseases should establish separate websites
for each one.
Projects origination. There is a permanent
open call for new projects. Scientists are
invited to submit ideas online for review by
the SAC.
Portfolio management. The SAC is
responsible for maintaining an adequate and
balanced pipeline of projects.
Project management. Each project is man-
aged by a Project Team led by a member
of the organization, and staffed by external
experts in drug discovery, clinical research
and regulation. The Project Team is respon-
sible for developing the budget and timeline,
overseeing outsourced tasks and ensuring
compliance with GxP. One of its crucial
duties is selecting what will be open-sourced
Table 2 | Public–private partnerships and their partners
Project Industry partner University/public
health partner
Other PPP
Medicines for Malaria Venture
Improved 4-aminoquinoline GlaxoSmithKline University of Liverpool
Farnesyl transferase inhibitors Bristol-Myers Squibb Universit y of Washington
Manzamine derivatives Univer sity of Mississipi
Cysteine protease inhibitors GlaxoSmithKline UCSF
Fatt y acid bio synth esis
inhibition
Tex as A &M, A. E ins tei n,
Jacobus
Pyridone GlaxoSmithKline
New di-cationi c molecules Immtech Universit y of North
Carolina
Dihydrofolate reductase
inhibition
Biotec Thailand
Artesunate derivatives GlaxoSmithKline,
Shin Poong
TDR, DNDi
Artemisone Bayer University of Hong Kong
Synthetic perox ide Ranbaxy Universit y of Nebraska
Intravenous artesunate Walter Reed
Coartem in infants Novartis TDR
TB Alliance
Pyrido nes and quinolizines Taejon, Yonsei
Isoniazid ana logue Wellesley College
PA-824 NIH, Johns Hopkins
Mocifloxa xin Bayer CDC, J ohns Hopkins
Institute for One World Health
Paromomycin TDR
Azole Yale
TDR
Miltefosine Zentaris
Oral eflornithine Aventis
CDC, Cente rs for Disease Con trol and Prevention; D NDi, Drugs for N eglected Disea ses Initiative; NIH ,
National I nstitutes of Healt h; TDR, UNICEF– UNDP–World Bank–WH O Special Programm e for Research
and Training in Tropical Diseases.
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and what will be outsourced. The project
leader is accountable for generating the data
used to decide whether to fund the next step.
Commitment to a project is limited to the
current step, until the data warrants commit-
ting funds for the next one. Open-sourced
tasks are posted on the project’s website,
each on its own page, and outsourced ones
are posted on a companion matchmaking
website such as Innocentive, or Scienteur.
Outsourcing bids are reviewed by the Project
Team, which issues recommendations
to the SAC.
Intellectual property ownership. There is
often a misperception that open-source
initiatives are hostile to patents and bent
on putting discoveries in the public domain.
The reality is more nuanced. Most open-
source activities occur at a pre-commercial
R&D stage, when the ideas and hypotheses
debated fall short of the legal standards that
define inventions in patent law. They are an
on-going scientific conversation that can be
likened to a global instant-messaging system
linking scientists interested in a topic. In that
sense, open-source is no more threatening
to patents than other forms of scientific
publishing. A scientist who engages in that
conversation and comes up with an idea that
can lead to a patentable invention will need
to exercise caution with disclosures until the
invention has been reduced to practice and
patent applications have been filed, just as
would be necessary in a traditional research
setting. It is generally accepted that open
communication promotes advancement
of science, but needs to be balanced by the
need to protect the rights of inventors.
The same applies to open-source activities.
Template features: tools
The discovery toolbox. As of February 2006,
349 genomes have been published and
another 1,575 are being sequenced. A new
generation of smart, computerized tools
is becoming available to mine data, comb
the literature, map metabolic networks,
perform in silico modelling, visualize bind-
ing sites, identify chemical leads, design
molecules and predict toxicity. These tools
should be packaged into a convenient
toolbox, together with access to major
databases, and offered to volunteers willing
to contribute their expertise.
Outsourcing software. Several programs
already exist to match projects with talent
and capacity. Two examples are Scienteur,
a free e-marketplace that allows companies
to post tasks, and experts to register their
skills, and Innocentive, an online problem-
solving tool that lets a company post a
challenge with a reward: whoever finds the
solution gets the money.
Template features: costs
PPPs have been able to function on very low
budgets for several reasons (TABLE 4). First,
they have few people, low overhead costs
and no fixed assets. They rely on someone
else’s unused capacity, and the market seems
to price such capacity at marginal instead
of full cost. Second, they outsource much of
their work where it is cheaper to do so and
do most of their trials in developing coun-
tries. Third, they concentrate on infectious
diseases for which costs are lower. Fourth,
they receive in-kind donations.
Will it work?
Despite the promise of open-source drug
R&D, both its pioneers, and the veterans
of open-source software, point to several
potentially troublesome issues that could
affect the success of the open-source model.
Availability of talent. Typical open-source
projects do not require a large number of
contributors. Data from the software indus-
try suggests that the ideal number ranges
from 6 to 20 people. Yet much of the drug
R&D expertise resides in an industry that
has a strong proprietary culture. Employees
are routinely asked to assign their intellectual
output, including that created on their own
time, to their employers17. This could stifle
talent supply in key areas. Two developments,
however, might give open-source drug R&D
the permanent talent pool it needs. First,
thousands of highly trained pharmaceutical
scientists are nearing retirement and might
Table 3 | Public–private partnerships lower the critical mass required to discover and develop new cures
Organization Focus Staff Pipeline
Number of
projects
Discovery PK Clinical Cumulative
spending through
2005 (US$ million)
Medicines for
Malaria Venture
Malaria 13 19 12 1 6 103
TB Alliance Tuberculosis 18 12 8 1 3 20
Drugs for N eglected
Disease Initiative
Tr ypa nos omi asis , vi sce ral
leishmaniasis, Chagas disease
36 20 9 4 7 20
OneWorld Health Leishmaniasis, malaria, Chagas
disease, diarrhoeal diseases
40 5 1 3 1 ?
International AIDS
Vac cine Ini tia tive
HIV/AIDS 169 6 – 1 5 120
Malaria Vaccines
Initiative
Malaria 32 10 4 2 4 ?
Source: Ann ual reports . PK, pharmacok inetics.
Table 4 | R&D costs for public–private partnerships (US$ million)
Stage MMV TB Alliance DNDi IAVI Big Pharma
Discovery and PK 8.3 18.6 16.2 20.0 26.0
Phase I 1.6 0 .6 Unpublish ed 2.0 15.2
Phase II 1.2 3.4 Unpublished 5.0 23.5
Phase III 9.5 22.6 Unpu blished 30. 0 86 .3
Total clinical 12.2 26.6 24.2 37.0 125.0
Source: REF. 19. DNDi, Dru gs for Neglecte d Diseases Initiat ive; IAVI, Internation al AIDS Vaccine Initiative;
MMV, Medicines for Ma laria Venture.
PERSPECTIVES
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ADVANCE ONLINE PUBLICATION www.nature.com/reviews/drugdisc
welcome the opportunity to put their skills
to good use. Second, drug companies might
be persuaded to ease restrictions on their
employee’s involvement. There is indeed little
conflict of interest in being a cancer scientist
by day and an anthrax researcher at night,
and firms might gain valuable goodwill from
letting employees seek cures for diseases in
which they have no interest.
Availability of data and standards. Open-
source scientists cannot accomplish much
unless they can access data. Biological data
is plentiful and getting richer, with terabytes
of genomic and metabolic data continuously
being added to the pool. Chemical and
structural data, on the other hand, are more
scarce. In addition, the formats used to
handle these data are still evolving. Biologists
use a reasonably small number of them, but
chemists are further from such consensus.
Both the lack of standards and the scarcity of
data in certain areas can cause problematic
choke points in an open-source R&D effort.
Availability of tools. Open-source scientists
need open-source tools to practice their
craft. Until recently, such tools were plentiful
in bioinformatics, but less so in chemistry,
which has long been dominated by com-
mercial software. This is changing. The 2004
launch of PubChem has brought online a
powerful suite of tools that allows scientists
to connect chemical information with
biomedical research and clinical informa-
tion in an unprecedented way. Non-profit
scientists can now access small-molecule
high-throughput screening, chemistry and
informatics on a scale previously available
only to industry. They can even get grants to
turn their online discoveries into assays for
high-throughput screening18. Other tools
such as eMolecules, Jmol or the Chemistry
Development Kit are adding powerful
chemical search and visualization capabilities
to the open-source scientist’s toolbox.
Intellectual leadership. Just as putting ingre-
dients into a vat does not necessarily cause
them to react, connecting smart people online
does not guarantee they will produce anything
valuable. In both cases, a catalyst is needed.
For open-source drug R&D, the presence of
a subgroup of highly innovative contributors
who can tune in the on-going conversation
and fuel it with their own creative insights acts
as such a catalyst. Without it, the conversation
could remain shallow and fizzle out.
Momentum. Enticing people to join is a
challenge. A good website helps, but it’s not
enough. As Darren Carroll, former CEO of
Innocentive, puts it, “If you build it, they will
not come!”. It takes a sustained effort to get the
word out and build trust with stakeholders.
It also takes a leader who can connect with
people, understand their motivation and foster
trust. Linux attracts thousands of contributors
because they identify with Torvalds’ ideals and
trust him to do the right thing. Open-source
drug R&D must build such leaders.
Web interface. The design of the project’s
website is crucial. It must be engaging and
appeal to visitors’ curiosity. They must be
able to quickly find the pages that match
their interests, download the toolbox, and be
‘up-and-playing’ in minutes.
Quality assurance/quality control. When
something as complex as drug R&D gets
parceled out around the world, quality
assurance can become an issue. Oversight,
due-diligence, audits, good practices and
prior experience can be used to ensure quality.
International Organization for Standardization
standards could also help in the future.
Selectivity. Not all projects will be equally
suitable. Cancer might draw contributors,
but hair loss might not.
Conclusion: a new ecology of drug R&D?
Is there still room for big pharma in open-
source R&D? One must stress that ‘virtual’
does not mean ‘leaderless’. To succeed,
open-source R&D will need deep expertise
in the minutia of drug R&D, which today
resides overwhelmingly in the pharma-
ceutical industry. There might be many
volunteers, but they must be shepherded
towards a goal. Such stewardship is a core
competency of pharmaceutical companies.
Our model is not a substitute for them, but
a way to leverage their capabilities to tackle
unmet medical needs, such as the diseases of
poverty, orphan diseases and niche markets.
Pharmaceutical companies stand to gain
from co-opting the open-source model and
allowing it to flourish in ‘coopetition’ with
traditional R&D, to handle the diseases or
R&D steps for which it is best suited.
Bernar d Munos is at E li Lilly & Co., L illy Corp orate
Center, 1085, Indianapolis, Indiana 46285, USA.
e-mail: bhmunos@stanfordalumni.org
doi:10.1038/nrd2131
Published online 18 August 2006
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Acknowle dgements
I thank A. Tash jian (Har vard School of Publi c Health and
Harva rd Medic al School ), B. Smith (Center for B iosecurity,
Univers ity of Pit tsburg h Medica l Center) a nd M. Munos
(Gardner Carton & Douglas) for valuable feedback on
previous versions of the manuscript.
Competing interests statement
B.M. work s for Eli L illy & Co., whic h has spons ored the
Scienteu r and Innocentiv e ventures mention ed in this artic le.
This declaration of potential competing financial interests is
also available in the Web version.
FURTHER INFORMATION
SourceForge: http://sourceforge.net/
BioForge: www.bioforge.net
PubChem: http://pubchem.ncbi.nlm.nih .gov
eMolecule: www.emolecules.com
Jmol: http://jmol.sourceforge.net
CDK: http://almost.cubic.uni-koeln.de/cdk
Emboss: http://emboss.sourceforge.net/
Medici nes for Malar ia Venture: www.mmv.org
The Init iative on Publ ic-Private Pa rtnersh ips for Health :
www.ippph.org
Global Fund to Fight AIDS, Tuberculosis and Malaria:
www.theglobalfund.org
Aeras, Global TB Vaccine Foundatio n: www.aeras.org
Drugs f or Neglecte d Disease s Initiative: www.dndi.org
Global Alliance for TB: www.tballiance.org
Instit ute for One World H ealth: www.oneworldhealth.org
International AIDS Vaccine Initiative: www.iavi.org
Malaria Vaccine Initiative: www.malariavaccine.org
Access to t his interac tive links b ox is free onlin e.
PERSPECTIVES
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