Collaborative Innovation in Pharmaceutical Industry: Approaches and Requirements
Bayer HealthCare Pharmaceuticals, Berlin, Germany
The pharmaceutical industry is facing a number of challenges. The model of blockbuster 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 innovation concepts are now gaining increasing importance. Whereas classical in-licensing or mergers and acquisitions have been traditionally pursued, early research collaborations 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 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 discovery in academic settings that foster the productive and mutually rewarding interaction 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 discovery. These encompass approaches such as crowdsourcing, strategic alliances, incubators, 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 outsourcing, 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].
TABLE 16.1. Definition of Open Innovation, Open Access, and Open Source
| Open innovation Open 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 source The 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:
|
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 collaboration schemes and their key success factors.
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 funds Transparency in operational processes and awarding of funds Clear IP regulation required Clear definition of scope and goals of initiative |
| 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 management Sufficient 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 required Incubators 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 data Long-term commitment Clear communication schedules (regular meetings, communication rules) |
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 successfully been used in the Business to Consumer sector. One example is the Procter & Gamble (P&G) “Connect and Develop” portal (http://www.pgconnectdevelop.com
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