Ten Simple Rules for Cultivating Open Science and Collaborative R&D

How can we address the complexity and cost of applying science to societal challenges? Open science and collaborative R&D may help [1]–[3]. Open science has been described as “a research accelerator” [4]. Open science implies open access [5] but goes beyond it: “Imagine a connected online web of scientific knowledge that integrates and connects data, computer code, chains of scientific reasoning, descriptions of open problems, and beyond …. tightly integrated with a scientific social web that directs scientists' attention where it is most valuable, releasing enormous collaborative potential.” [1]. Open science and collaborative approaches are often described as open source, by analogy with open-source software such as the operating system Linux which powers Google and Amazon—collaboratively created software which is free to use and adapt, and popular for Internet infrastructure and scientific research [6], [7]. However, this use of “open source” is unclear. Some people use “open source” when a project's results are free to use, others when a project's process is highly collaborative [4]. It is clearer to classify open source and open science within a broader class of collaborative R&D, which can be defined as scalable collaboration (usually enabled by information technology) across organizational boundaries to solve R&D challenges [8]. Many approaches to open science and collaborative R&D have been tried [1], [9]. The Gene Wiki has created over 10,000 Wikipedia articles, and aims to provide one for every notable human gene [10]. The crowdsourcing platform InnoCentive has reportedly facilitated solutions to roughly half of the thousands of technical problems posed on the site, including many in life sciences such as the $1 million ALS Biomarker Prize [11]. Other examples include prizes (X-Prize [12]), scientific games (FoldIt [13]), and licensing schemes inspired by open-source software (BIOS [14]). Collaborative R&D approaches vary in openness [15]. In some approaches, the R&D process and outputs are open to all—for example, open-science projects like the Gene Wiki described above. In other approaches which demonstrate what might be called controlled collaboration, there are strong controls on who contributes and benefits—for example, computational platforms like Collaborative Drug Discovery or InnoCentive that support both commercial and nonprofit research [9], [11]. Collaborative approaches can unleash innovation from unforeseen sources, as with crowdsourcing health technologies [11]–[13], [16]. They may help in global challenges like drug development [17], as with India's OSDD (Open Source Drug Discovery) project that recruited over 7,000 volunteers [16] and an open-source drug synthesis project that improved an existing drug without increasing its cost [18]. If you want to apply open science and collaborative R&D, what principles are useful? We suggest Ten Simple Rules for Cultivating Open Science and Collaborative R&D. We also offer eight conversational interviews exploring life experiences that led to these rules (Box 1). Box 1. Conversations on Open Science and Collaborative R&D Many commentators have considered challenges in translating open science and collaborative methods to biomedical research [2]–[4], [9], [17], [20], [24], [26], [28], [29]. How can protecting intellectual property be balanced with freeing researchers to build on previous knowledge? If R&D results are collaboratively created and freely available, who will take responsibility for costly clinical trials and quality control? What will be the Linux of open-source R&D? To explore such challenges and convey life experiences in biomedical open science and collaborative R&D, we offer eight conversational interviews by the first author of this article as supplementary material. The conversations were done on behalf of the Results for Development Institute and are with: Alph Bingham, cofounder of InnoCentive (Text S1) Barry Bunin, CEO of Collaborative Drug Discovery (Text S2) Leslie Chan, open access pioneer and director of Bioline International (Text S3) Aled Edwards, director of the Structural Genomics Consortium (Text S4) Benjamin Good, coleader of the Gene Wiki initiative (Text S5) Bernard Munos, pharmaceutical innovation thought leader (Text S6) Zakir Thomas, director of India's Open Source Drug Discovery (OSDD) project (Text S7) Matt Todd, open science and drug development pioneer (Text S8)

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.