Four archetypes of Open Science Partnerships

Connecting aims and means in open research collaborations

Maria Theresa Norn^*, Laia Pujol Priego^**, Irene Ramos-Vielba^*** and Thomas Kjeldager Ryan^***

^*mtn@ps.au.dk

https://orcid.org/0000-0001-7523-2920

The Danish Centre for Studies in Research and Research Policy, Aarhus University, Denmark, and The Centre for Technology Entrepreneurship, Technical University of Denmark, Denmark

^**laia.pujol@esade.edu

https://orcid.org/0000-0001-6796-729X

Department of Operations, Innovation and Data Sciences, ESADE Business School, Ramon Llull University, Spain

^*** iravi@ps.au.dk; tryan@ps.au.dk

https://orcid.org/0000-0002-8998-0388; https://orcid.org/0000-0002-4763-5308

The Danish Centre for Studies in Research and Research Policy, Aarhus University, Denmark

1. Introduction

A growing number of Open Science Partnerships (OSPs) have emerged around the world (Ali-Khan, Jean, and Gold, 2018; Ali-Khan et al., 2018; Gold, 2021; Gold et al., 2019). They are precompetitive public-private research partnerships that adhere to principles of open science. This includes putting the research outputs into the public domain and precluding participants from seeking Intellectual Property (IP) rights protection on such outputs from the partnership. More specifically, Gold (2021, p. 2) defined OSPs as “private-public collaborations that have certain common elements: open access publications, open sharing of data, tools and materials and the absence of intellectual property rights that restrict improvement or use of jointly created inventions.”

Therefore, the open principles that define OSPs differ markedly from standard practices in precompetitive research partnerships which often restrict the sharing of outputs and allow participants to secure the rights to any IP that may be developed in the collaboration (Stevens et al., 2016). Conversely, OSPs are typically aimed at removing “roadblocks not only to the sharing of information, but to its use” (Gold, 2021, p. 7). They seek to address long-standing challenges associated with the patenting of early-stage basic research, mitigating barriers to university-industry collaboration, and accelerating/strengthening the uptake of scientific research outputs in industry and society.

Despite the growing interest in OSPs, they have been the subject of limited scholarly attention, save for two prior studies on the Structural Genomics Consortium (SGC) (Morgan Jones et al., 2014; Morgan Jones and Chataway, 2021; Perkmann and Schildt, 2015). To counteract this situation, our aim is to shed light on the essence of OSPs, examining their similarities and differences. By furthering our understanding of key differences in how OSPs can be designed and deployed, we hope to inspire both further research into this growing form of collaboration and the potential development of new OSPs.

To this end, we conducted a comparative qualitative study of five OSPs in biomedicine. In this paper, we propose two crucial dimensions in OSP design - research aims of the partnership and degree of industry orientation - as the basis for four archetypes of OSPs. These archetypes are intended to provide a starting point for researchers interested in a better understanding of the nature and scope of OSPs, and for practitioners wishing to ensure that means applied match the desired ends that motivated the OSP.

2. Data and method

The archetypes are developed based on a cross-country comparative study of OSPs within the biomedical field, in which the vast majority of OSPs has emerged. The selected OSPs were identified through internet searches and assessed according to the following criteria: (i) are public-private partnerships; (ii) involve formal, goal-oriented agreements among at least one public academic partner and at least one private sector partner; (iii) have explicit focus on open sharing of knowledge, data, tools, materials and other research outputs; (iv) preclude participants from seeking IP protection on outputs of the collaboration and have no (or minimal) restrictions on sharing and further use of research outputs; (v) are ongoing at the time of study or completed within the past five years.

Five OSPs met these criteria: The Structural Genomics Consortium (SGC); Open Targets (OT); The Enabling & Unlocking Biology in the OPEN (EUbOPEN); The Early Drug Discovery Unit (EDDU); and The Open Discovery Innovation Network (ODIN). These OSPs are briefly described in Table 1.

Table 1. Presentation of the five OSPs included in the comparative study

The dimensions and archetypes proposed in the paper have been developed based on: (i) a review of relevant literature, (ii) desk research on the five selected OSPs, and (iii) semi-structured interviews with representatives of each of the OSPs, which were undertaken in late 2021 and early 2022 to identify common features and relevant singularities across OSPs. A preliminary set of possible dimensions for characterising OSPs was then explored in a second round of interviews in early 2023. Resulting ideas for archetypes were presented and discussed at an online workshop held in March 2023 with representatives from the OSPs covered in the comparative study. Thus, the proposed archetypes draw on findings from the comparative study as well as insights and experiences from practitioners developing and leading OSPs initiatives.

3. Results

Two key dimensions. How OSPs differ and how this matters

Our comparative study reveals significant differences across OSPs designs. These differences set the conditions under which the OSP will operate and ultimately shape its outcomes. We consider two crucial dimensions: the research aims of the partnership and the degree of industry orientation. Both dimensions address key motivations for the establishment of the OSP and its intended aims.

The first dimension, research aims of the partnership, concerns the degree to which the OSP is aimed at advancing science within a specified, focused direction. Some OSPs pursue very specific aims, for instance the SGC’s mission is to understand all proteins encoded by the human genome in order to accelerate the discovery of new medicines. Other OSPs are motivated not by a desire to achieve specific research objectives but rather to promote open research within a given topic and thus pave the way for more exploratory research. For instance, the EDDU’s mission is to undertake fundamental research that can lead to the development of new and improved treatments for neurological disorders. What their projects have in common is that they build on induced pluripotent stem cells, but the projects themselves can differ greatly in scope and aims. Similarly, ODIN was established to promote open university-industry collaboration within early-stage drug discovery research. ODIN has funded projects within two thematic areas, biomarkers and target validation, but these were selected not due to specific scientific aims but because they were deemed well-suited for open, precompetitive collaboration. Therefore, we argue that achieving specific, complex scientific aims calls for a different design of an OSP due to the need to ensure direction and to coordinate the efforts of participants.

The second dimension we propose, the degree of industry orientation, refers to the extent to which the partnership is explicitly expected to advance the uptake and use of science in industry. Some stated motivations of OSPs seem to give priority to scientific missions over industrial applications. An example of an OSP driven primarily by scientific aims (i.e. with lower industry orientation) is the SGC, which aims to advance and enhance the quality of scientific research that ultimately seeds the development of new drug discovery programs. Meanwhile, other OSPs emphasise the involvement of, and expected impact on, industry. An example of an OSP with higher industry orientation, driven both by scientific and industry aims is ODIN, which was established to increase and accelerate the use of science in industry. We argue that the degree to which an OSP is explicitly oriented to primarily advancing science as opposed to supporting industry uptake of science will affect key decisions in the OSP, e.g. about the mechanisms set in place for knowledge sharing in the public domain.

Four archetypes of OSPs

Based on these two dimensions we propose four archetypes for OSPs, as illustrated in Figure 1. These archetypes seek to capture ideal-type models for OSPs based on the aims that motivated them and are presented in more detail in the following.

Figure 1. Four archetypes of OSPs

1. The collaborative mission refers to OSPs which are focused on specific research aims and have a lower degree of industry orientation. These could be large-scale partnerships involving coordinated efforts pulling in a highly targeted direction. The core activities of the SGC to understand the functions of proteins encoded in the human genome would be an example of this.

2. The collaborative node is also primarily scientifically-driven, but rather than concentrating on certain research aims, seeks to engage in more exploratory projects that fit within the scope of the partnership, e.g. based on an existing scientific infrastructure, biobank, set of methods or the like. EDDU provides an example of collaboration built on its existing capabilities and infrastructure to work with induced pluripotent stem cells.

3. Among the OSP archetypes that are more explicitly oriented towards industry in addition to the pursuit of scientific aims, we find the collaborative club, which refers to industry-oriented but highly focused partnership on both specific goals and industry needs. Open Targets is an example of such a partnership that has developed a trusted and bounded collaboration amongst selected pharmaceutical companies and research labs to accelerate target identification and validation in key strategic areas of interest for the industry participants.

4. Finally, the collaborative hub, like the collaborative node, is more exploratory than focused on its research aims. OSPs of this type are likely to provide a platform for collaborative activities oriented at and closely engaged with industry. ODIN is an example of an OSP which stimulates needs-oriented basic research collaborations developed and executed in close collaboration with industry partners, resulting in a portfolio of heterogeneous activities developed on a bottom-up basis by project participants.

The four archetypes present distinct rationales which are reflected in certain key components of the OSPs. These differences affect how openness is implemented in practice and, subsequently, the corresponding outputs obtained from such collaborative endeavours.

These main contrasting characteristics of the OSP archetypes are presented in Table 2.

Table 2. Characteristics of the four OSP archetypes

4. Conclusion

The growing phenomenon of OSPs therefore calls for fine-grained approaches that are capable of exploring potential implications in the practice of research in domains where collaborative arrangements are usually shaped by IP and in the valorisation of this change in knowledge flows and technology transfer processes.

Towards that goal, our findings uncover that despite fundamental similarities, OSPs are not a homogeneous phenomenon. On the contrary, the OSPs examined show important organisational variety. We propose two dimensions that can help explain key differences across OSPs: their research aims and their degree of industry orientation. Based on these dimensions, we identify four archetypes and further characterise their different supporting rationales and the implementation mechanisms they employ to achieve their goals. Likewise, these partnerships also display differentiated openness patterns conducive to diverse research outputs.

It should be stressed that the archetypes represent ideal types, and not necessarily real-life OSPs. In practice, an OSP may include multiple programs and projects that fit into different ideal types. The purpose of the archetypes we propose is not to capture the full complexity of individual OSPs but to highlight crucial differences in their objectives, which affect the way in which OSPs are designed.

Finally, our proposed archetypes are intended to serve as a managerial inspiration for the design and development of future OSPs, particularly for practitioners and funders, by fostering informed decisions about critical OSP goals and how to organise the collaborative sphere to achieve both scientific and industry ends.The article may additionally spark new insights and help to identify future research paths in the area of open innovation in science by taking a closer look at different models for OSPs and their functionality.

References

Ali-Khan, Sarah E, Antoine Jean, and E Richard Gold. 2018. "Identifying the challenges in implementing open science." MNI Open Research, 2 (5). https://doi.org/10.12688/mniopenres.12805.1.

Ali-Khan, Sarah E, Antoine Jean, Emily MacDonald, and E Richard Gold. 2018. "Defining Success in Open Science." MNI Open Research, 2 (2). https://doi.org/10.12688/mniopenres.12780.2.

Gold, E Richard. 2021. "The fall of the innovation empire and its possible rise through open science." Research Policy, 50 (5), 104226. https://doi.org/10.1016/j.respol.2021.104226.

Gold, E Richard, Sarah E Ali-Khan, Liz Allen, Lluis Ballell, Manoel Barral-Netto, David Carr, Damien Chalaud, Simon Chaplin, Matthew S Clancy, and Patricia Clarke. 2019. "An open toolkit for tracking open science partnership implementation and impact." Gates Open Research, 3. https://doi.org/10.12688/gatesopenres.12958.2.

Morgan Jones, Molly , Sophie Castle-Clarke, Daniel Brooker, Edward Nason, Farah Huzair, and Chataway. Joanna. 2014. The Structural Genomics Consortium: A Knowledge Platform for Drug Discovery. Santa Monica, CA: RAND Corporation.

Morgan Jones, Molly, and Joanna Chataway. 2021. "The Structural Genomics Consortium: successful organisational technology experiment or new institutional infrastructure for health research?" Technology Analysis & Strategic Management, 33 (3), 296-306. https://doi.org/ 10.1080/09537325.2021.1882673.

Perkmann, Markus, and Henri Schildt. 2015. "Open data partnerships between firms and universities: The role of boundary organizations." Research Policy, 44 (5),1133-43. https://doi.org/10.1016/j.respol.2014.12.006.

Stevens, Hilde, Geertrui Van Overwalle, Bart Van Looy, and Isabelle Huys. 2016. "Intellectual property policies in early-phase research in public–private partnerships." Nature Biotechnology, 34 (5), 504-10. https://doi.org/10.1038/nbt.3562.

Open science practices

The document studies undertaken and the OSP descriptions developed in connection with the comparative study presented in this paper can be shared, though they have not yet been made openly available. The paper also draws on interview data, which due to GDPR issues is not shared openly, but which can be shared subsequent to removal of personal data.

Moreover, the study draws on close engagement of OSP practitioners from the OSPs included in our comparative study.

Acknowledgments

The authors would like to thank representatives from the five OSPs included in the comparative study for their valuable inputs to the development of the paper.

Author contributions

All four authors have contributed substantially to the following activities: conceptualization; investigation; formal analysis; methodology; and writing.

Competing interests

The authors have no competing interests to declare.

Funding information

Three of the four authors would like to acknowledge funding from the Novo Nordisk Foundation for the project “Impact assessment of ODIN”, which has contributed data to the comparative study of OSPs that the current paper draws on (Grant no. NNF20SA0061466).