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36USING MARKET-DRIVEN

COLLABORATION TO ACCELERATE INNOVATION

IN BIOMEDICINEElizabeth Iorns

Science Exchange Inc., Palo Alto, CA, USA

Collaborative Innovation in Drug Discovery: Strategies for Public and Private Partnerships, First Edition.Edited by Rathnam Chaguturu.© 2014 John Wiley & Sons, Inc. Published 2014 by John Wiley & Sons, Inc.

The research landscape is currently undergoing an evolution driven by an “innovation crisis” that has left the pharmaceutical industry facing empty pipelines, patent cliffs and unsustainable development costs [1, 2]. Looking toward other industries for inspira-tion provides an opportunity to identify new collaborative models that may facilitate an innovation revolution that will enable faster, cheaper and better drug discovery in biomedicine.

A single scientist can no longer master all the techniques required to make major discoveries (many biomedical papers now have more than 10 authors [3]). Therefore, driving more collaboration between scientists is both necessary and highly beneficial. First, it increases the efficiency of research spending by promoting more complete utilization of resources and expertise, and enabling economies of scale. Second, it increases the speed of research because it can be conducted in parallel, and there is no downtime required for nonexperts to learn new techniques. Third, it increases the quality of research by enabling experts to conduct specialized, complicated techniques, which often have a steep learning curve. Improving quality is more important than ever—the quality of published research has recently been questioned, with more than

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70% of published results estimated to be irreproducible [4–6]. Using experts not only improves the quality of research produced, but it removes single investigator bias, which may help to improve reproducibility of the results.

The collaborative economy is one model that shows great promise to facilitate increased scientific collaboration. Fueled by social networks and payment systems, the collaborative economy empowers individuals to buy goods and services from each other, rather than large corporate entities. The collaborative economy is highly efficient, allowing better use of existing resources and expertise, and generates higher quality products by enabling the use of specialized equipment and highly trained individuals. Interestingly, dramatic increases in collaboration have been observed in numerous industries where the barriers to adoption of a collaborative economy are far greater than in scientific research (e.g., sharing spare rooms via Airbnb or personal cars via Getaround). This widespread adoption has been enabled by aggregating demand at centralized online marketplaces, establishing trust via integration with social networks, and promoting transactional ease with payment platforms.

EXAMPLES FROM OTHER INDUSTRIES

In the last five years, numerous companies have emerged to enable the collaborative economy to transform several industries (Table 36.1).

The most well-studied is probably the transportation industry, which has seen companies like Lyft, RelayRides and Getaround enable car-sharing on a widespread scale. A University of California study found that every car-sharing vehicle replaces 9–13 vehicles [7], reducing the idleness of cars and car ownership overall. This obvi-ously has tremendous benefits for the environment but also challenges the transportation industry’s existing players, many of which have adapted with innovative collaborative solutions of their own. For example, multiple automobile manufacturers have launched their own car sharing networks, including BMW’s “DriveNow,” Volkswagen’s “Quicar,” and Daimler’s “Car2Go,” creating rental markets for their previously purchase only automobiles. Zipcar was one of the early movers in this space, and was acquired by Avis for $500 million demonstrating the enormous value of the collaborative economy in the transportation industry.

Following closely behind the transportation industry—in terms of impact from the collaborative economy—is the accommodation industry. In this space homeowners are disrupting hotels, renting out their spare rooms or entire homes via online marketplaces like Airbnb, HomeAway and VRBO. Although only founded five years ago Airbnb now has more rooms available for rent than the entire Hilton group [8]. This market is esti-mated to be worth more than $26 billion [9].

Other examples of industries undergoing disruption from the collaborative economy include the labor market, where virtual workers can be hired on demand via oDesk and Elance, tasks and errands can be run using TaskRabbit’s, and businesses can manage contractors and freelancers with Workmarket; and the banking industry, where consum-ers can lend to each other at lower rates via Prosper and Lending Club.

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TABLE 36.1. Examples of Industries Transformed by Companies Creating Collaborative Economies

Industry Example Company

Transportation Lyft: A peer-to-peer ride-sharing network with a community of background-checked drivers who offer rides in their own vehicles. Raised over $80M from Andreessen Horowitz.

RelayRides: A peer-to-peer car-sharing marketplace where people who need a car can “rent” one from an individual vehicle owner. Raised over $30M from Google Ventures, and General Motors Ventures.

Getaround: Similar to RelayRides, a peer-to-peer car-sharing marketplace that enables car owners to rent their cars. Raised $19M from Menlo Ventures.

DriveNow: Zipcar-like car-sharing membership program started by BMW and Mini. Similar initiatives have been started by Volkswagen (Quicar) and Daimler (Car2Go).

Uber: A mobile application that provides on-demand access to black car and limo operators. Raised $307M from Google Ventures, Goldman Sachs and Jeff Bezos.

BlackJet: Membership based program from the creators of Uber that provides “private jet convenience and reliability, at a fraction of the cost”.

Accommodation/Space Airbnb: Peer-to-peer marketplace for renting spare rooms and entire homes. Raised $326M and recently valued at over $2B.

HomeAway: Marketplace for vacation homes. Listed on NASDAQ (AWAY).

ShareDesk.net: a peer-to-peer marketplace matching unused workstations, offices and desks with free-floating workers.

ParkingPanda: Online marketplace for parking enabling parking owners to drive extra traffic when yield is low and improve pricing when the lot is full. Raised ∼$5M.

Labor oDesk: An online workplace that enables businesses to find, hire, manage, and pay talented independent professionals via the Internet. Raised $44M from Benchmark Capital.

Elance: Online marketplace to access 2 million freelance workers. Raised $95M from Kleiner Perkins.

TaskRabbit: Online and mobile marketplace that helps people outsource their errands and tasks. Raised $38M from Founders Fund.

Work Market: An enterprise-class platform and marketplace for managing contractors and freelance labor. Raised $15M from Spark Capital.

Banking Prosper: Peer-to-peer lending marketplace with 2M customers. Raised over $120M from Sequoia Capital.

Lending Club: Peer-to-peer lending platform that offers an alternative to banks with great rates for both borrowers and investors. Has over $2B in personal loans.

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WHAT HAS LED TO THE RISE OF THE COLLABORATIVE ECONOMY?

The major driver of the collaborative economy has been advancement in technology and its widespread adoption. Social networking, often integrated into collaborative economies, facilitates peer-to-peer transactions by matching supply and demand, and promotes trust by providing transparency around the profiles of the interacting individu-als. The creation of online payment systems has been essential for enabling transactions to be easily completed between buyers and sellers.

A second important driver has been the ongoing economic pressure that individuals and businesses face. The ability to monetize excess idle inventory and expertise, and increase financial flexibility by only accessing what is required rather than over-investing in expensive capital equipment and full time hires, has driven adoption of the collaborative economy in other sectors.

These drivers are also applicable to scientific research. Companies in the collabora-tive economy have developed platforms that help people create wealth from excess and underused assets such as cars, houses and their own spare time. Can the same sort of model be applied to accelerate innovation in biomedicine?

THE EVOLUTION OF SCIENTIFIC COLLABORATION

Scientific collaboration is currently undergoing an evolution as the research landscape changes from an individual pursuit to the era of team science. The different types of collaboration used in scientific research are summarized in Table 36.2 with the key features of each approach identified.

Traditionally, basic research has been conducted by a single scientist or a small team of scientists within a single laboratory, mostly within academia. The scientist(s) would conduct the majority of required experiments themselves, even if they did not initially have the necessary expertise or equipment. If they could not conduct an experi-ment themselves, they would attempt to find a collaborator in another academic lab to help them using a barter system. This barter system essentially involves one scientist asking for a favor from another scientist, with the potential upside being co-authorship on any publications that are produced by the work. This type of collaborative arrange-ment depends heavily on personal networks developed by scientists.

As research has become increasingly specialized and complex, this DIY/barter system has ceased to function effectively. It is no longer possible for a single scientist to master all the techniques or purchase all the equipment required to conduct their experiments. Collaboration allows the many technical components of a research project to be conducted by multiple experts, which improves the efficiency and quality of the research conducted. However the current bartering model of collaboration is not opti-mally efficient because the platforms to facilitate it and the incentives to promote it are not fully optimized. Middle authorship on a possible future publication may not incen-tivize the best experts to conduct experiments and it is difficult for scientists to maintain sufficient personal networks to enable effective bartering for all of the complex experi-ments required. Frequently, even an entire university cannot provide all the expertise

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TABLE 36.2. Sharing Practices in Biomedical Research

Type Example Features

Nonmarket collaboration (aka Bartering)

Exchange of experiment for co-authorship on future publication.

Free for “requester”May be suboptimal “provider” due to poor incentives for them to contribute.

Professional experience not likely (no fixed deliverables or turnaround time etc negotiated up front).

Control over IP not retained.Costly for “provider” in terms of expenditure on reagents and time.

Largely limited to personal network of “requester”.

Outsourcing partnership

Exchange of experiment (usually large project based) for monetary compensation and sometimes co-owned intellectual property (IP).

Professional experience (clear milestones and deliverables negotiated up front).

Possibility of shared risk and upsides through IP sharing agreements.

Legal fees invested in complex agreements can be costly and time consuming.

Experts and resources available are limited to partners, reducing flexibility and efficiency.

Market-driven collaboration

Exchange of experiment for monetary compensation.

Experts and resources available are limited only by the participants in the marketplace.

Identifying and engaging best experts for specific experiments is quick and easy.

Professional experience (clear milestones and deliverables negotiated up front).

Control over IP is retained.

necessary for a research project, as over 60% of papers are now co-authored by inves-tigators from multiple institutions [10].

The amount of collaboration required in research will continue to increase. This will be driven by many factors including the need for more complex and large scale instrumentation to delve deeper into biological and physical processes; the need to pool knowledge with others to make original significant advances, and an increasing desire for research that crosses multiple disciplines.

So with large teams of scientists, often based at remote institutions, increasingly needing to work together to solve complex problems, there is a demand for new tools to help facilitate collaboration. Specifically, there is an increasing need for tools that allow researchers to easily find and access other scientists with the expertise required to advance their research projects. To operate most efficiently, these tools also need

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new methods to reward researchers for participating in these collaborations. A market-driven collaborative economy seems to be an obvious solution.

MARKET-DRIVEN COLLABORATION FOR RESEARCH

The digital marketplace model provides a mechanism for researchers to list their expertise so that other researchers can easily find them and request collaborations. Several sites that allow for scientific networking exist including Mendeley.com, ResearchGate.net, Academia.edu and BiomedExperts.com, but these are not specifi-cally designed to facilitate formal transactions between scientists. Science Exchange (http://www.scienceexchange.com) offers a transparent fee-for-service marketplace, delineating a clear incentive for experts to participate in collaborations that they may not have previously been interested in. If we look at the factors that have facilitated the collaborative economy in other sectors, the social network and payments system pro-vided by Science Exchange may allow market-driven collaboration in science to flour-ish. One other factor—the ongoing economic pressure that is currently facing individual scientists and funders—may also serve to promote adoption of a market-driven collabo-ration system in science.

THE EMERGENCE OF VIRTUAL RESEARCH INSTITUTES

In fact, the basis for a market-driven collaboration system has already been established and is flourishing in the private sector. This has been driven by the availability of sci-entific expertise on a fee-for-service basis from contract research organizations (CROs). The rapid rise in CROs has enabled research to be conducted by organizations, which would previously have had to invest in wet lab space and the associated research per-sonnel. This “virtual” method of conducting research is highly efficient and has been widely embraced by the biotech sector [11], where biotech start-ups outsource experi-mental work rather than build in-house capabilities. This is very cost effective as it allows these companies to avoid the purchase of expensive equipment and the hiring/training of staff for highly specialized one off techniques. This model is also increas-ingly used by pharmaceutical companies, which have cut in-house research staff and have started relying on more efficient mechanisms of accessing expertise via outsourc-ing. One example is AstraZeneca, which has outsourced its entire clinical pharmacology research to the CRO Quintiles [12].

This model has been slower to be adopted by academia, which predominantly still relies on bartering to facilitate collaboration. Given the significant funding restrictions that are now in place, researchers will need to adapt to become more efficient and ensure they are monetizing their assets effectively to fund their research programs. One aca-demic sector that has moved to a market-driven system is core facilities at academic research institutes which house specialized equipment and expertise for fee-for-service use by investigators.

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Many core facilities and CROs have begun creating the basis for an effective sci-entific collaborative economy by listing at Science Exchange. By aggregating demand, establishing trust via a reputation system and integration with publication databases, and promoting transactional ease with a payment platform, Science Exchange is provid-ing the central components that have enabled the collaborative economy to thrive in other sectors.

An important point to note is that while the rise of CROs has enabled major effi-ciencies to be gained, the model as depicted earlier, is not a true collaborative economy of peer-to-peer transactions. This requires the individuals who are sharing their exper-tise and resources to be available for engagement on an individual level via a market-place. This type of individual engagement has enabled other industries to be vastly more collaborative. Examples of this include home-share rentals on mediocre websites, which have been common for more than a decade. However, it took Airbnb increasing engage-ment by encouraging individuals to transact with each other via their platform, to grow this into a $26 billion industry. Another example is Etsy, which has dramatically grown the market for handmade goods by encouraging individuals to create storefronts on their platform and sell directly to their peers. This innovation is ultimately where Science Exchange offers the most promise to accelerate innovation in biomedicine. By providing a platform for individual scientists to offer their expertise, a collaborative economy for scientific research can thrive.

BENEFITS OF MARKET-DRIVEN COLLABORATION IN BIOMEDICINE

The major benefit of market-driven collaboration for scientific research is the increase in the amount of collaboration that will occur due to the alignment of incentives. Using a monetary transaction system motivates the best experts to share their expertise because they are fairly compensated to do so. Likewise, researchers seeking expertise are provided with a professional service and experience that comes from a payment model. This type of system can dramatically increase the amount of collaboration occurring in a specific industry. This has been clearly demonstrated by companies like Airbnb and Lyft, which have dramatically grown home- and car-sharing, respec-tively, from activities limited to personally connected individuals, to billion dollar industries.

Driving more collaboration between scientists through a collaborative economy will accelerate innovation by increasing the efficiency of research, allowing more research to be conducted per dollar spent, and increasing the speed at which discoveries are made. One of the biggest advantages of increased collaboration is improvement in the quality of research. Irreproducibility, particularly in preclinical research, has emerged as a major challenge to innovation in biomedical research.

Most scientific advancement occurs not through blockbuster papers, which defini-tively solve a problem, but through careful and incremental progress, building on prior work. However, recent work by the pharmaceutical companies Bayer Healthcare [5] and Amgen [6] indicate that 70–80% of academic preclinical biomedical studies are not reproducible. This highlights a significant problem that must be addressed to

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enable scientific progress. To try to solve this problem, various organizations are now funding replication studies to identify reproducible research [13]. The most prominent example is the Cancer Biology Reproducibility Project [14], which is replicating 50 recent high-impact cancer biology studies using the Science Exchange network. Notably, the market-driven collaboration model of the Science Exchange network has been critical for delivering and publishing these replication studies. Using monetary compensation as an incentive for participation has enabled rapid delivery of high-quality replication experiments. Quality control by independently replicating key experimental results will be an important component to enable successful innovation in biomedicine.

BARRIERS

Collaboration between academia and industry is essential for translating the basic dis-coveries made in academic labs into applications that benefit the public. A new model that enables the connection of individual researchers to the right expertise at the right time is required to enable this effectively. However, there are significant hurdles to overcome in the form of institutional bureaucracy, inertia, and incentive systems. By examining the success of other industries that have adopted collaborative models, we learn that the platform must enable individualized decision-making, provide trust, and ensure transactional ease. It is possible that efforts that promote high level partnerships between two large organizations fail to deliver on their promise simply because they don’t allow individuals to operate freely with the right incentives. A phrase known as “consortium fatigue” [15] has already emerged to describe the disappointments of many high level public-private partnerships.

The collaborative economy works in sectors where it “builds on real customer need and creates experiences that are human and personal” [16]. This individualized personal component, which is trust-enabling, is essential for the success of this approach. Trust requires knowledge of the individuals collaborating via the platform. It previously seemed unthinkable that ordinary people would let strangers stay in their homes or get in their car, but the power of social networks that have enabled deep knowledge of an individual without a prior in-person relationship, has provided a “reputation” that enables the trust required for these transactions to occur. Monetary compensation pro-vides the incentive. In a similar way, a platform for market-driven scientific collabora-tion must also provide this individualized approach—researchers must trust the scientists they will be working with.

The final barrier that must be eliminated is the institutional bureaucracy that is inherent to large organizations such as universities and pharmaceutical companies. The most valuable assets at any research institute are clearly the expertise and resources that are housed there. Yet these assets are currently incredibly difficult to access. For market-driven scientific collaboration to succeed, research organizations will have to empower their individual scientists to operate with freedom in the research-on-demand marketplace.

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SUMMARY

The collaborative economy has changed the behavior of individuals in ways that could not have been imagined a decade ago. By providing online platforms that aggregate demand, promote trust, and ease payment, even the most risky industries have created enormous peer-to-peer markets. Biomedical research can take advantage of this model too. By moving to a collaborative economy model, we can enable efficient collaboration between the best scientific experts, which will ultimately drive the innovation, produc-tivity and quality control needed to accelerate biomedical research.

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