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16COLLABORATIVE INNOVATION IN

PHARMACEUTICAL INDUSTRY: APPROACHES

AND REQUIREMENTSMonika Lessl and Khusru Asadullah

Bayer HealthCare Pharmaceuticals, Berlin, Germany

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 pharmaceutical industry is facing a number of challenges. The model of block-buster drugs is waning due to patent expiries (influx of generics), “me-too” drugs and increased competition. Expensive late stage failures and increasing value requirements by payors add to these challenges [1]. As a consequence, the pharmaceutical industry needs to consider new approaches to overcome the emerging portfolio gap.

One approach is to promote innovation by joining forces with partners such as biotech companies, other pharmaceutical companies, and academia. Such open inno-vation concepts are now gaining increasing importance. Whereas classical in-licensing or mergers and acquisitions have been traditionally pursued, early research col-laborations aiming to enrich the idea pool and “de-risk” early research projects are gaining interest. Novel models are emerging such as crowdsourcing initiatives or concepts based on the sharing of tools and assets. These endeavors are matched with a rise in interest in academia to contribute to drug discovery, resulting in the establishment of academic screening centers or open access initiatives. This is strengthened by the announcement of the NIH to increase its engagement in drug discovery [2]. This development is on one hand driven by governments to get a

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return on their investment in research and on the other hand by the movement of scientists toward more clinically focused research and an interest in bringing their findings to the clinic.

A number of models are currently being tested on how to best promote drug dis-covery in academic settings that foster the productive and mutually rewarding interac-tion between pharmaceutical industry and academic research institutes. The challenge remains how the translation of ideas from academic research to novel treatments for the patients can be accomplished and managed best and what models exist to promote the generation of value out of collaborative efforts. Depending on the questions to be addressed, different open innovation models can be applied to foster early drug discov-ery. These encompass approaches such as crowdsourcing, strategic alliances, incuba-tors, industry on campus concepts, or consortia. For what type of question what model fits best as well as their key characteristics will be discussed in this chapter. Besides novel models for collaborative innovation, the chapter will highlight requirements within the industry to ensure the uptake and further development of innovative ideas from academic partners.

OPEN INNOVATION VERSUS OPEN ACCESS

As the use of the term open innovation varies and often gets mixed up with the term open source or open access definitions—as they will be used throughout this chapter—they have been summarized in Table 16.1. Accordingly, the term open innovation means the flexible use of internal and external paths and ideas to generate value [3]. Thus, this chapter will focus on models of innovation sourcing and not take into account outsourcing of offshoring. To distinguish innovation sourcing from mere out-sourcing, definitions are required. Outsourcing subsumes contract research and fee for service contracts, innovation sourcing encompasses collaborative efforts of two or more partners where novel, value-generating ideas are created jointly and translated into products. Thus, innovation is defined as the implementation of novel ideas that create value [4].

OPEN INNOVATION MODELS: KEY CHARACTERISTICS AND SUCCESS FACTORS

To further evaluate different open innovation models, key characteristics as well as key success factors for each model have been determined. Models taken into account in this analysis were crowdsourcing approaches, strategic research alliances between academia and industry (including industry on campus approaches), as well as incubator concepts and precompetitive consortia. Table 16.2 provides an overview on the different collabo-ration schemes and their key success factors.

OPEN�INNOVATION�MODELS:�KEY�CHARACTERISTICS�AND�SUCCESS�FACTORS� 257

TABLE 16.1. Definition of Open Innovation, Open Access, and Open Source

Open innovationOpen innovation is a paradigm that assumes that firms can and should use external and internal ideas as well as internal and external paths to generate value [3].

Open accessOpen access is a term used for free access to scientific literature (http://wirtschaftslexikon.gabler.de/Archiv/569867/open-access-v2.html). In the field of drug discovery, this term is discussed for open access to chemical and clinical probes to reduce duplication of efforts and increase productivity [10].

Open sourceThe term “open source” has originally been used for software whose source code is published and made available to the public, enabling anyone to copy, modify, and redistribute the source code. The term was adapted to the scientific field:• Research—The “Open Source Science Project” was created to increase the ability for

students to participate in the research process by providing them access to microfunding, which, in turn, offers nonresearchers the opportunity to directly invest and follow cutting-edge scientific research. All data and methodology are subsequently published in an openly accessible manner under a Creative Commons fair use license (http://www.theopensourcescienceproject.com/opensourcescience.php).

• Open source drug research and development can help revive the industry, using principles pioneered by the highly successful open-source software movement. There has been another proposal for open-source pharmaceutical development, which led to the establishment of the Tropical Disease Initiative. There are also a number of not-for-profit “virtual pharmas” such as the Institute for One World Health and the Drugs for Neglected Diseases Initiative.

• The term “open source genomics” was coined to describe the combination of rapid release of sequence data (especially raw reads) and crowdsourced analyses from bioinformaticians around the world that characterized the analysis of the 2011 Escherichia coli O104:H4 outbreak.

TABLE 16.2. Overview of Different Collaboration Schemes and Their Key Success Factors

Models Key Characteristics Key Success Factors

Crowdsourcing (drug discovery)

Funds are provided to researchers to solve a specific question in drug discovery

Useful to establish initial contacts

Starting point for further collaborations

Easy access to fundsTransparency in operational processes and awarding of funds

Clear IP regulation requiredClear definition of scope and goals of initiative

(Continued )

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Models Key Characteristics Key Success Factors

Strategic alliances between industry and academia

Bilateral partnerships encompassing multiple projects

Useful to evaluate and translate ideas from research to the clinic

Joint teams (industry and academia) to select and promote projects

Exchange of personnel or joint labs to promote understanding of each other’s goals and to exchange know-how

Identification of partners with complementary skills and competencies as well as matching goals

Establishment of trustful relationship as a basis for collaboration

Open-minded attitude and receptor in the company required to adopt novel ideas

Professional alliance managementSufficient resources (in terms of capacity) at both partners to ensure close interaction and exchange (communication, meetings, etc.)

Long-term commitment Incubators Physical entity for start-up

companies where additional support in terms of know-how in drug development, project management, and/or access to technology platforms is provided

Long-term commitment requiredIncubators require innovation promoting surroundings (innovation hubs)

In case of industry incubators independence of start-ups and influence by Big Pharma have to be balanced

Precompetitive consortia

Association of multiple partners with the goal to develop standards and infrastructure for drug discovery and development

Increase knowledge on drug discovery in academia

Professional overall alliance management and consortium leadership

Clear responsibilities for subprojects (strong project leaders)

Clear definition of joint goals and milestones—recognitions of the value each partner brings into the consortium

Infrastructure to share dataLong-term commitmentClear communication schedules (regular meetings, communication rules)

TABLE 16.2. (Continued)

CROWDSOURCING�APPROACHES�ARE�USEFUL�TO�LEVERAGE�THE�KNOW-HOW� 259

CROWDSOURCING APPROACHES ARE USEFUL TO LEVERAGE THE KNOW-HOW OF A LARGE GROUP OF PEOPLE TO ADDRESS SPECIFIC QUESTIONS

While there are a number of examples of industry collaborating with one major partner, there has been a lack of approaches that make use of the expertise of a larger scientific community to address specific questions. The Internet provides an ideal platform for such an approach, being easily accessible from all over the world. Such an innovation model called “crowdsourcing” was first introduced by Jeff Howe [5] and has success-fully been used in the Business to Consumer sector. One example is the Procter & Gamble (P&G) “Connect and Develop” portal (http://www.pgconnectdevelop.com), which allows consumers to bring their ideas for product improvements or novel product ideas. According to P&G, around 50% of their product initiatives involve significant collaborations with outside innovators, and they achieved a 70% higher-than-average net present value from connect- and develop-enabled projects [6].

Pharma companies are now piloting this approach in drug discovery [7]. In the original meaning of the term, crowdsourcing is a concept by which specific problems are communicated to an unknown group of potential solvers in the form of an open call, usually via the Internet. The community (the crowd) is asked to provide solutions and the “winners” are rewarded. The first company to introduce this concept in drug discovery was Eli Lilly in 2001, with the establishment of the InnoCentive platform (http://www2.innocentive.com). InnoCentive is now an independent organization with a solver community or more than 200,000 experts in more than 20 countries. Further crowdsourcing initiatives have followed in recent years [7]. In these cases, the clas-sical concept has been extended in a way that companies or institutions seek for novel ideas, which are then further evaluated in a collaborative approach (Figure 16.1). Examples are the Phenotypic Drug Discovery (PD2) platform by Eli Lilly (http://www.pd2.lilly.com), the Grants4targets (http://www.grants4targets.com) initiative by Bayer HealthCare or the Call for Targets (http://www.callfortargets.org) program by the Medical Research Council Technology UK.

Within its Grants4Targets initiative, Bayer HealthCare is seeking for novel targets in their strategic disease areas, namely oncology, cardiology, and selected gynecologic diseases [8]. Through the platform, scientists can apply for financial support to further evaluate and validate a specific target. To make it attractive, a nonbureaucratic submis-sion process has been established, a fast processing of the proposals set up, and an intellectual property (IP) policy developed where the IP rights remain with the appli-cants. After the grant period, promising targets could be further pursued via collabora-tive agreements. Since the beginning of the initiative, 10 calls have been completed, approximately 1000 grant applications received, and more than a hundred grants awarded to academic groups all over the world.

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STRATEGIC ALLIANCES

Strategic alliances require long-term commitment and provide the basis for a close interaction between the alliance partners (Table 16.3). They usually encompass a substantial—in terms of resources and finances—and long-term commitment. To make alliances successful, not one-dimensional technology transfer, but multidimensional interchange of information and know-how should be the basis of such relationships [9]. Strategic alliances are an appropriate model to evaluate and translate ideas from research and jointly develop them along the value chain. Thus, complementary skills and com-petencies as well as matching goals are a key prerequisite for success. Exchange of personnel or joint labs further promote such partnerships. Examples are the strategic alliance between Bayer HealthCare and the German Cancer Research Center [11] or the alliance between Pfizer and the University of California San Francisco. Joint Committees to select projects, joint project management, and financing additionally promotes real collaborative efforts.

INDUSTRY ON CAMPUS OR INCUBATOR MODEL

Also, industry labs directly located on the university campus provide a good model to promote close interaction and make use of the informal knowledge spillover effect promoted by physical proximity. The increasing importance of such models can be

Figure�16.1.� Crowdsourcing:�an�approach�to�leverage�the�worldwide�know-how�to�solve�a�

specific�question.�aSuch�as�the�search�for�novel�targets,�compounds,�or�indications�for�known�

assets.

Internet ascommunication

platform

Collaboration(industry and

academia)to addresschallenges

Challengea to be solveddefined by seeking institution

(pharma company)

Solutions/ideas provided byscientific community

Reviewof proposedideas

INDUSTRY�ON�CAMPUS�OR�INCUBATOR�MODEL� 261

TABLE 16.3. Examples of Different Collaboration Schemes and Their Main Characteristics

Models to Foster Drug Discovery Examples Main Characteristics

Crowdsourcing Grants4Targets Program(Bayer Healthcare) (http://www .grants4targets.com)

Grants are provided for the validation of novel drug targets in BHC’s strategic areas (oncology, gynecology, and cardiology).

Strategic alliances

Strategic allianceBayer Healthcare German Cancer Research Center Heidelberg

(http://www.dkfz.de/de/presse/pressemitteilungen/2013/dkfz_pm_13_22.php)

Strategic alliance to develop novel treatment paradigms for cancer; innovative setup by risk and reward sharing approach (each partner contributes 1 million euros/year to the join budget), joint selection committees, and joint project groups.

Industry on Campus

Bayer Healthcare Innovation Center at Mission Bay (UCSF)

(http://www.pharma.bayer.com/scripts/pages/en/news_room/news_room/news_room92.php)

Bayer Innovation Center at Mission Bay (UCSF) represents an innovative concept to locate the industry labs directly on the campus to facilitate the exchange and translation of ideas.

Incubators Bayer CoLaborator (www .colaborator.bayer.com)

The CoLaborator is an innovative incubator space for young start-ups close to Bayer labs. It provides infrastructure and options to exchange and collaborate with Bayer experts on aspects related to drug discovery.

Consortia Innovative Medicine Initiative(http://www.imi-europe.org)

IMI is a partnership between the European Union and the European Federation of Pharmaceutical Industries and Associations (EFPIA). The goal is to promote drug discovery by precompetitive research driven by consortia between industry and academia. Focus of activities is to increase efficacy and safety and to promote knowledge and education on drug discovery.

(Continued )

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demonstrated by the successful development of the mission bay campus at the UCSF. In the meantime many biotech companies have established their labs on campus and in January 2011 also, Bayer HealthCare opened its new Innovation Center on the campus. The concept—to create an advantage out of the physical proximity promoting know-how exchange and joint learning—is also a key driver of the incubator model. As an incubator we understand a physical entity that hosts young start-up companies—mostly spinouts from universities. Besides infrastructure, some incubators offer finan-cial support for the companies as well as advice regarding development of their products. Examples of industry incubators are the Biogen Idec bi3, the Bayer CoLaborator, or the Janssen Labs. The QB 3 garage is another example fostered by the academic sector. To make such a model successful, a long-term commitment, appropriate support, and an innovation-promoting environment are key prerequisites. In case of industry incuba-tors, a balance has to be found in creating synergies by close interaction between the biotech partner and the industry to preserve the integrity and independence of the biotech company in the incubator.

PRECOMPETITIVE CONSORTIA

Precompetitive consortia are important models to address general aspects in drug dis-covery such as tools or standards. Examples are predictive toxicity models, biomarkers, or improved simulation tools for pathway analyses (Table 16.2). Recently, a number of consortia between industry and academia have been established to address these kinds

Models to Foster Drug Discovery Examples Main Characteristics

Enlight Biosciences(http://www.enlightbio.com)

Enlight is a VC company established in partnership with a group of pharmaceutical companies to support the development of breakthrough technologies promoting drug discovery.

Asian Cancer Research Group (ACRG)

(www.asiancancerresearchgroup.org)

ACRG is a nonprofit organization established by Lilly, Merck, and Pfizer with the goal to establish a publicly available genomic database of profiled tumor samples as a basis for the development of novel approaches for cancer treatment.

TABLE 16.3. (Continued)

PROFESSIONAL�ALLIANCE�AND�COLLABORATION�MANAGEMENT� 263

of questions. Examples are the Innovative Medicine Initiative with a total funding of 2 billion euros over 7 years (Table 16.3). The goal is to promote safety and efficacy in drug discovery and development and to foster education and knowledge in these fields. Another example is Enlight Biosciences. Enlight Biosciences has been founded by a group of pharmaceutical companies and a venture capitalist to support the development of novel enabling technologies driving and facilitating the R&D process. The key driver for the establishment was the fear that transformative technologies fostering discovery of novel drugs may remain overlooked if their development is not adequately supported. Similarly, the nonprofit partnership between Lilly, Merck, and Pfizer to accelerate research and improve treatment of lung and gastric cancers in Asia (Table 16.3) is an example of a precompetitive consortium.

PROFESSIONAL ALLIANCE AND COLLABORATION MANAGEMENT

In addition to the selection of appropriate models, professional management of the collaborations and alliances is a prerequisite to generate value out of the collaborative efforts. By a number of interviews with key leaders from industry and academia, the RESOLVE model has been developed highlighting key success factors for collabora-tive projects (Figure 16.2) [8]. A key aspect of the model is to put effort into relationship

Figure�16.2.� RESOLVE�Model:�Key�success�factors�for�industry–academic�collaborations.

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management. This is often undervalued by scientists, but studies have shown that poor relationships are the main cause of failures in alliances. Personnel contacts, exchange of personnel, respectful behavior built on trust, and integrity are key aspects to provide fertile ground for the collaboration. Another prerequisite for successful collaborations is to ensure a strategic fit between the partners and matching goals. Complementary strengths and competencies are other key aspects as the value of doing things together must be greater than doing it alone. Often this aspect isn’t addressed properly prior to the start of an alliance and not enough time is invested to identify the real drivers of the potential partners. This could result in disappointments later on as partners don’t strive in the same direction. Professional operational management forms another key pillar to make alliances successful. The outline of the contract and the implemented governance structures have to match and support the goals of the collaboration. These have to be clearly defined and agreed upon. Learning capabilities and openness toward new ideas are key aspects to promote innovation. Partners have to be open to look beyond their own principles and boundaries. Added value has to be created; otherwise, each partner could do the task alone. Furthermore, valued communication as well as enthusiasm and commitment at all levels are key aspects for successful collaborations. Based on the RESOLVE model, a checklist has been developed summarizing key aspects to be considered when initiating a collaboration [9] (Table 16.4). To support the professional management of collaborations, “alliance managers” in industry and academia are important. Whereas industry has recognized the need of dedicated func-tions and is currently establishing respective positions, only few examples exist in academia so far. Seminal examples can be found at the UCSF and the German Cancer Research Center, where professional alliance management have been established. As alliance management goes beyond mere administrative aspects and aims to guide the overall alliance toward the set goals, respective positions have to be at an appropriate hierarchical level and position holders have to be respected personalities in the community.

CONCLUDING REMARKS

In the pharmaceutical industry, open innovation approaches are gaining importance due to the pressing need to overcome the innovation gap and to de-risk early research. On the other hand, academia is moving to a more translational model, driven by their interest to field-test ideas and promoted by governments to demonstrate a return on investment in public research. How such collaborative innovation approaches can be accomplished depends on the question to be answered. There is no one-size-fits-all solution. The model chosen has to match the needs and requirements of each partner. It is critical to invest enough thoughts in the beginning on the goals and expectations of the partnerships. In addition, it has to be evaluated whether the goals of both partners strive in the same direction. Partnerships driven by opportunistic motives (such as the goal to gain extra funding) will not be successful in the long run. Only if both partners are willing to invest time, commitment, and resources can a long-term success can be

CONCLUDING�REMARKS� 265

TABLE 16.4. Checklist for Initiation of Joint Projects between Pharmaceutical Industry and Academia

1. Identifying matching partnersDo the partners fit together?Do they share the same values? Is there a cultural fit?Is there a willingness to respect and support each other?

2. Strategic fitWhat are the expectations of the partners and the respective goals?Can the expectations with respect to scientific quality and expertise be provided by the

partner?What do the partners want to get out of the collaboration?Will the goals fit together?Do the partners provide complementary skills and expertise?

3. Operational managementWho is in the driver’s seat for the collaboration, on a management level and on an

operational level?Will there be a single interface for effective collaboration management?Have clear agreements been made before the start of the collaboration regarding objectives

at each site, timelines, publication strategy, IP rights (who owns what?), budget, decision processes, conflict management?

Have all stakeholders been involved in the agreement and do they support it?4. Learning capability

Is there a willingness and interest to learn from each other?What programs can be initiated to foster cross-organizational learning (e.g., exchange

programs, seminars)?Can specific training be offered for members of the alliances (skill and competency

building)?5. Communication

How is the communication culture of the partner?How will timely communication be ensured?How can an efficient and satisfactory exchange of information be ensured (e.g., regular

meetings, communication platforms)?Are conflict management and conflict escalation measurements in place?

6. CommitmentAre all stakeholders committed to the collaboration (from scientist at the bench to senior

management)?What can be done to overcome resistance and to motivate the people involved?Will the credit of the collaboration be shared? What’s in for each partner?

achieved. To guide the collaboration, alliance management is key, which needs to be implemented and professionalized on both sides (industry and academia). The partner-ship should be built on the strengths of each partner to generate added value. Only if the value in doing it together is greater than doing it alone, can a partnership be successful.

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ACKNOWLEDGMENT

The authors thank Stefanie Schoepe for her help and fruitful contributions in preparing the manuscript.

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