The Precompetitive Space for Drug or Vaccine Development: What Does It Look Like Now and What Could It Look Like in the Future?

The pharmaceutical industry including small and large organizations and biotech as well as other stakeholders in the health arena are increasingly aware of the benefits of working together in the precompetitive phase to address common problems. While they rightly remain focused on developing their own independent products and services in healthy competition, there is an increased awareness of the need to improve precompetitive efficiency by identifying and addressing common issues. A major challenge is defining the domain of precompetitive research. The basic biology, the understanding of disease, biomarkers of prognosis, and even drug responses all can be areas of precompetitive research and development (R&D).Precompetitive collaboration allows a group of competing companies to come together to develop a solution for a problem that they all share, and from which none of them would gain a competitive advantage. Although the primary goal is often cited as the development of that solution, the process of conversing and collaborating is in itself of great value, and a project that enables colleagues from across the industry to develop closer working relationships with each other can be beneficial, even if the deliverables do not live up to expectations.Several different precompetitive collaboration types have evolved to date. Collaborations are typically classified regarding whether they have open or restricted participation and open or restricted outputs. They also vary according to their goals. Likewise, there are typically 2 broad collaboration goals: to build enabling platforms and to conduct research. These goals can be further subdivided by the 4 different types of outputs they produce, including the development of standards and tools, the generation and aggregation of data, knowledge creation, and product development.In general, collaborations aimed at building enabling platforms focus on developing standards and tools or generating and aggregating data to achieve a necessary scale for research. Collaborations that conduct research seek to create new knowledge or to turn that knowledge into a product by accessing resources and capabilities across organizations. Barriers to sharing data are often an obstacle. Different data systems, privacy rules, and sharing protocols often make it difficult for community-based organizations in nonmedical sectors to work in concert with health care organizations.Regulatory hurdles, complex research for new drug and vaccine targets, and the low predictability of animal models are some examples of why both drug and vaccine industries are struggling. Such internal and external challenges make it necessary for companies to improve their R&D efficiencies by methods including outsourcing to reduce overhead costs, installation of proof-of-concept organizations, or by enhanced scientific rigor in data-driven project decision-making.1 The recent pandemic also provided a heightened sense of urgency to accelerating collaborations beyond R&D, including manufacturing competitors’ products,2 conducting platform trials,3 and sharing precompetitive data without the usual contractual and legal bottlenecks.4,5 One of the more publicly acknowledged short-term, precompetitive collaborations during the pandemic was the ICODA (International COVID-19 Data Alliance) initiative,6 an open and inclusive global collaboration of leading life science, philanthropic, and research organizations that came together to harness the power of health data to respond to the COVID-19 pandemic.Some pioneering organizations started to complement their internal R&D efforts through collaborations as early as the 1990s. In recent years, various extrinsic and intrinsic factors created an opportunity for external sources of innovation resulting in new models for open innovation, such as open sourcing, crowdsourcing, public-private partnerships, innovations centers, and the virtualization of R&D. This new reality also influences the construction and intention around precompetitive collaboration. This perspective challenges the preconceptions of the precompetitive space from the standpoint of their value, construction, and sustainability and highlights the necessity of a convener to facilitate the scope and intentions of precompetitive collaborations particularly as they evolve over time.Precompetitive collaboration is often generalized as 2 or more companies within the same industry, coming together to address a shared problem or pain point that does not affect direct business competition and is often focused on joint social or environmental impacts. These private sector partners might also be joined by community actors such as nongovernmental organizations (NGOs), donors, or foundations in the target region or value chain. Together, they forge new solutions to overcome shared obstacles—unlocking opportunities for the partners, and the ecosystem they all share. See the Figure for a conceptualized view of the precompetitive space and the stakeholders that often comprise the relevant ecosystem. Keep in mind that many of the stakeholders contribute to the precompetitive space in a variety of ways and that the contributions are about more than data. Precompetitive collaboration empowers the private sector to meaningfully address systemic challenges by coordinating sustainability efforts; bringing a wider range of perspectives, resources, and expertise to the table; and scaling more impactful solutions.The notion of precompetitive collaboration is viewed as a positive approach in general allowing a group of competing companies to come together to develop a solution for a problem that they all share, and from which none of them would gain a competitive advantage. Although the primary goal is often cited as the development of that solution, the process of conversing and collaborating is of great value, and a project that enables colleagues from across the industry to develop closer working relationships with each other can be beneficial, even if the deliverables do not live up to expectations. Simply waiting for an existing group to come up with something might appear to be risk-free, and certainly reduces effort, but passive bystanders to precompetitive collaboration projects are typically losing out on more than they imagine.Success in a precompetitive collaboration is often reliant on a convener to develop a successful data ecosystem for the data collaboration. There are various roles essential to the inner working of a data ecosystem that enables precompetitive collaboration. Typically, there are the following main roles: data suppliers, data intermediaries, and data consumers.7 This view holds true also for data collaboratives, as the minimal value chain therein is also about matching data supply and data demand.8 The term convener typically refers to a neutral third party (i.e., facilitator or mediator) who gathers information to test the feasibility of a particular stakeholder involvement process or outcome. Neutral in this context refers to impartiality and a lack of bias in decision-making.Two commonly viewed neutral conveners are the Institute of Medicine (IOM) and the Critical Path Institute (C-Path). The IOM has a singular capacity to bring together various stakeholders to work together on health problems of shared interest. Through both ongoing roundtables, sometimes called forums, and through unique partnerships, the IOM shapes the conversation around health and health care. Partnerships with outside organizations bring complementary strengths and enable the IOM to amplify the size and character of its audience and the impact of its work.11 The IOM has pursued a number of such new opportunities with outside organizations in recent years. C-Path is a nonprofit, public-private partnership with the US Food and Drug Administration (FDA), created under the auspices of the FDA’s Critical Path Initiative program in 2005. C-Path’s aim is to accelerate the pace and reduce the costs of medical product development through the creation of new data standards, measurement standards, and methods standards that aid in the scientific evaluation of the efficacy and safety of new therapies. These precompetitive standards and approaches have been termed drug development tools (DDTs) by the FDA, which established a process for official review and confirmation of their validity for a given context of use. C-Path orchestrates the development of DDTs through an innovative, collaborative approach to the sharing of data and expertise. C-Path strives to build consensus among participating scientists from industry and academia with FDA participation and iterative feedback. The process culminates in a formal application to FDA for official “qualification” of the DDT for a given use in product development.Table 1 provides a more extensive list of generally regarded neutral conveners including several from sectors outside of life sciences along with “case for” and “case against” neutrality considerations. In most situations the “case for” sentiments are well appreciated by their stakeholders, while the “case against” assessment reflects the view from some that these organizations have a limited geographic or disciplinary scope and not as broad in their convening scope as necessary nor as they could be. The global perspective is certainly not a requirement for a neutral convener but it does occasionally project an optics concern for restriction to a more colonial interest.Specific Examples. There are in fact some good examples of organizations working in the precompetitive space in certain therapeutic areas (e.g., Oncology12) and for certain purposes (e.g., genomics13 and data standards (e.g., Pistoia Alliance) that transcend multiple and diverse stakeholders. Table 2 provides a list of precompetitive collaborations that represent a multistakeholder environment with high visibility and demonstrated impact.Pharma companies have increasingly moved away from internal R&D constructs towards more open and collaborative R&D models following a paradigm of open innovation.23 In this approach, they establish specific collaborations with academic centers of excellence, build innovation centers, create joint ventures with academic institutions (public-private partnerships), establish precompetitive consortia, or experiment with crowdsourcing and virtual R&D.24–27 Some models even let competitors collaborate and become partners,28 though these are more rare. Currently, many companies have put greater emphasis on leveraging external knowledge, licensing or acquiring drug candidates, and changing their R&D models from primarily inside-driven concepts to plans that more closely follow the open innovation paradigm.Bloom et al29 evaluated the elements necessary for successful collaboration between patient groups and academic and industry sponsors of clinical trials, in order to develop recommendations for best practices for effective patient group engagement. The most important elements for effective patient group engagement include establishing meaningful partnerships, demonstrating mutual benefits, and collaborating as partners from the planning stage forward. Although there is a growing appreciation by sponsors about the benefits of patient group engagement, there remains some resistance and some uncertainty about how best to engage. Barriers included mismatched expectations and a perception that patient groups lack scientific sophistication and that “wishful thinking” may cloud their recommendations. The larger question here is how do you know you got it right and are on a good path for the future. What are good metrics for successful precompetitive collaboration? What does a healthy precompetitive collaboration look like?Each stakeholder likely has their own perspective on this topic. Industry’s perceptions of the domain of precompetitive research have been expanding, though internal tensions can point to areas of ambiguity and the boundary can vary among companies and academic researchers. Universities and other organizations need to take advantage of multiple opportunities to change traditional practices. New ways of measuring achievement would provide incentives for more researchers to participate in precompetitive collaborations. What is clear from the examples discussed herein is that elements of successful collaborations should include the necessity of a good convener, plans for sustainability, responsible and constructive social behaviors, and customized platforms that can evolve with the demands of the collaboration. A key observation in the C-Path example has been the benefit of creating a dynamic research community with clear goals, a research agenda that evolves with the science, and a modern data and compute environment that encourages collaboration.30,31 When certain facilitating factors are present, intended collaborators can overcome competitive market dynamics and competing institutional priorities to align financial incentives, quality measurement, and data feedback to support practice transformation. Lessons from multistakeholder initiatives may be helpful to promote more and better collaborations (precompetitive or not) in the future. While regulatory authorities have suggested that precompetitive research offers the highly competitive pharmaceutical and medical device industries a way to reduce ballooning development costs,32 it will be up to sponsors to develop and sustain these efforts in conjunction with a diverse stakeholder community so that all benefit in some way.Thanks to David Sibbal for his thoughtful review of the paper. Data availability statement: Data generated herein are based on literature and web review but are available from the PI, Jeffrey S. Barrett, PhD, FCP, upon request.