Curing Consortium Fatigue

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Science Translational Medicine  28 Aug 2013:
Vol. 5, Issue 200, pp. 200fs35
DOI: 10.1126/scitranslmed.3006903


The complex pathology of consortium fatigue provides diagnostic data on how to improve collaboration in biomedical innovation.

Biomedical innovation is complex, expensive, and risky, and emerging science and technology have created tantalizingly high expectations. Converting innovation into health value in a timely, cost-effective, and sustainable manner requires a capacity for collaboration across disciplines, organizations, and nations. As we move forward with plans for major new multistakeholder initiatives, these alliances need to be evaluated with—and informed by—the same degree of rigor as other critical enablers of translational science, creating a timely opportunity for the advent of a new discipline focused on the science of collaboration.


In the past decade, diverse stakeholders have launched numerous collaborations in the global pharmaceutical industry in an attempt to address challenges to biomedical innovation. Since its inception in 2008, the largest multistakeholder effort—the European Union’s Innovative Medicines Initiative (IMI;—has established more than 40 consortia with financial and in-kind investments totaling €2 billion; IMI is now contemplating new collaborations and substantial scaling of investments to nearly €3.5 billion through the proposed Horizon 2020 innovation framework. Aligned with global trends, the U.S. President’s Council of Advisors on Science and Technology (PCAST) recommended formation of a U.S. counterpart to IMI ( The prevalence of multistakeholder initiatives reflects a continued optimism about the value of this collaboration approach for addressing biomedical innovation bottlenecks.

At the same time, concerns have arisen about how well these collaborations have been executed. Stakeholders suffering from “consortium fatigue” express frustration with the perceived redundancy, lack of productivity, and sense of chaos in the evolution of the collaboration landscape. Contributing to this frustration is the lack of an accurate and shared taxonomy, illustrated by the increasingly broad use of the term public-private partnership so that it now lacks utility for identifying a coherent collaboration subtype.

There is a growing desire to channel resources toward a smaller number of strategically coordinated initiatives that address critical translational gaps in ways that increase the likelihood of achieving and quantifying success. For example, 10 major pharmaceutical companies launched TransCelerate BioPharma in 2012 in order to align their decision-making, monetary resources, and in-kind support of collaborative initiatives, first by developing clinical-trials standards and best practices ( Despite the recent collaboration proliferation, little research has been conducted to assess the effectiveness of these alliances or to identify successful characteristics that can be applied to future ones (1). Given that stakeholders are now considering whether to make substantial additional investments in existing and new initiatives, it is time to figure out what works and what doesn’t. We need an evidence-based approach—a science of collaboration—to evaluate and inform the evolving multistakeholder collaboration environment in biomedical innovation. Our approach to learning and continuous improvement should parallel the rigorous scientific methodologies that are applied in biomedical research.


One of the first and most compelling cases for multistakeholder collaboration unfolded in the human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS) field of research in the United States in the 1980s and 1990s ( (2) and stands out as an object lesson in the power of aligning patient advocates, regulators, and drug-makers to speed drug development and access to urgently needed treatments.

Building on this initial success story of a reactive collaborative response to a global crisis, new initiatives prospectively designed for multistakeholder collaboration began to proliferate in the late 1990s. The first ones focused mainly on therapeutic development for diseases of the developing world, such as the International AIDS Vaccine Initiative (formed in 1996), the Malaria Vaccines Initiative (MMV; 1999), and the Drugs for Neglected Diseases Initiative (DNDI; 2003). The focus of collaborations was later broadened to address other types of innovation challenges, beginning with the sharing of proprietary data at the earliest stages of development, which was perceived as lower risk in terms of potential intellectual-property conflicts. Examples include the Alzheimer’s Disease Neuroimaging Initiative (ADNI) ( and the Biomarkers Consortium (Table 1), both of which focused on the development and validation of biomarkers for use across the global industry. More recently, multistakeholder collaborations are reaching beyond the early stages of the innovation life cycle to include later-stage challenges in product development, manufacturing, regulation, reimbursement, and postmarket use and monitoring for safety, efficacy, and effectiveness.

Table 1

Consortia that address various stages of the value chain.

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Although there is currently no central repository for tracking collaborative initiatives globally, in Table 1 we list examples that illustrate the broad range of focus areas across the innovation value chain. The modern trend to establish collaborations that target a broad range of innovation challenges is driven by a recognition that the growing complexity of science and the scale of associated data analysis and knowledge management can no longer effectively be addressed by a single organization or market sector. Collaboration is essential for reducing the cost and risk of innovation as well as enhancing its value for patients and society. Although the need for collaboration is no longer in question, it is worth noting the importance of this development. A willingness to share proprietary data among industry competitors represents a dramatic shift in the culture of the historically highly competitive pharmaceutical industry.

However, multistakeholder consortia operate collectively as a cottage industry rather than as coordinated components of a strategy appropriate for a global industry facing concerns about its sustainability (3). Leaders in collaborative innovation recognize the need to evolve from the current chaotic state to one of order and insight. TransCelerate and IMI represent early attempts to address this need through strategic and financial alignment among industry participants. In addition, several research groups have undertaken descriptive studies of the diverse types of collaborations in the biomedical innovation ecosystem (4, 5), whereas others are considering how to address the pressing need for a way to track global initiatives. Such efforts are important first steps in charting this vast and dynamic landscape, but we also must mind insights from our experiences in order to continuously improve how we design, manage, and evaluate collaborations. A science of collaboration can provide a shared taxonomy, a conceptual framework, and tools to build a knowledge base that informs strategies and tactics for funding, design, management, monitoring, and coordination of new initiatives. Research and education in the field should focus not only on success-enablers tied directly to the design and operational elements of consortia but also on those associated with other areas with more indirect but important impact on outcomes. Examples of these areas include collaboration strategy and implementation at the level of the macro-industry, participating organizations, and even human-capital management involving individual participants.

Although there may be a strong temptation to try to extrapolate from our experiences to date in order to rapidly advance to normative guidance such as best-practice models, this approach would likely constrain evolution of the collaboration model. Rather, the task of the first wave of researchers is to effectively characterize the vast array of differentiating elements of past and existing initiatives in order to define our initial palette of design levers for future application. Understanding how and when various models of funding, intellectual property management, and leadership, for example, have proven useful can provide exemplars to inform how we design new collaborations to address emerging innovation challenges, or how we marry the efforts of existing synergistic initiatives for greater efficiency and global impact. A critical area for development is to enhance our ability to define qualitative and quantitative success metrics that are meaningful to all participating stakeholders. Last, the knowledge base we develop should be scalable so as to foster continuous learning and improvement, setting an expectation that emerging innovation challenges are likely to require an evolution in our practices over time.

Fortunately, there are rich sources of knowledge and experience that can help to inform the evolution of this field. Management and social sciences and systems engineering both within and outside of the health care and biomedicine sectors offer useful perspectives for strategic planning and tactical implementation. Ideas to enrich our thinking may also be drawn from a wide range of domains, such as distributed innovation (6) and leadership models, complex adaptive systems (7), network mapping (8), collective intelligence (9), and even network-centric warfare, among others (Table 2). There is also much to be learned from multistakeholder collaborative initiatives in other industries, such as the early examples of SEMATECH (10) in the semiconductor industry and the Partnership for a New Generation of Vehicles (PNGV) in the automobile industry, or more recent ones, such as the SunShot Initiative in renewable energy (

Table 2 Mobilizing multiple stakeholders.

Domains of theory and practice that may aid evolution of the science of collaboration.

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In a world in which meaningful success metrics often remain elusive, the phenomenon of consortium fatigue provides a valuable lens through which to identify opportunities for improvement across a range of variables in multistakeholder collaborations. The science of collaboration will provide the foundational tools and methods we need to expedite our learning and enable the full exploitation of this powerful collaboration model in the face of emerging challenges and opportunities.

References and Notes

  1. Acknowledgments The views expressed here are those of the authors and should not be understood or quoted as being made on behalf of or reflecting the position of MIT, the Center of Biomedical Innovation (CBI), or the MIT New Drug Development Paradigms collaboration (NEWDIGS), all of which represent affiliations of the authors. The authors are grateful to C. C. Morton for assisting in the preparation and editing of this manuscript and useful discussions. Competing interests: The authors declare that they have no direct competing interests. The MIT Center for Biomedical Innovation currently receives or has received financial support from the Sloan Foundation, U.S. Defense Advanced Research Projects Agency, Kauffman Foundation, Merck Company Foundation, Sanofi Innovation Award Program and Alliance Management, Massachusetts Technology Collaborative, and individual philanthropists, as well as consortia members: Alnylam, Amgen, Baxter, Biogen-Idec, BioMarin, Boehringer Ingelheim, Bristol-Myers Squibb, EMD Millipore, Genentech, Genzyme, GlaxoSmithKline, Inno Biologics, Johnson & Johnson, LFB Biotechnologies, Medimmune, Merial, Merrimack Pharmaceuticals, Metabolix, Millipore, Novartis Pharma AG, Pfizer, Quintiles, Sanofi Pasteur, and Shire.

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