The emergence of open science practices in a health-related area and at such a global scale is quite a novel event. So far, open science projects in this area have been mostly dedicated to seeking solutions for diseases with non-profitable markets, such as Malaria, which are financially supported by philanthropic or public organizations. Most milestones in open science have been observed in the milieus of basic research, where science is perceived as a public good with few practical applications to be sold in markets. This is the case for instance of the Human Genome Project, which was developed thirty years ago and involved the participation of twenty organizations around the world committed to deciphering the human genetic map and sharing it openly. The present case of COVID-19 is quite different, as the scientific discoveries are much closer to applicable solutions and hold an immense potential demand (and economic profitability). However, it is not entirely surprising that open science has emerged in this context for several reasons.
Firstly, open science boosts efficiency by avoiding duplication, promoting collective intelligence mechanisms (Nielsen 2011) and creating positive externalities (David 2005). Openly available data and research outcomes also prevent or reduce the effect of defensive strategies based on intellectual property rights (IPR) mechanisms that slow down or impede urgently needed solutions. While in a normal situation there are few economic incentives to open up highly profitable health-related research, the pandemic context may have led to international pressures to prioritize efficiency over private profitability. Thus, open science becomes a promising path to deal with this urgency.
Secondly, the process of opening science is not starting from scratch. The scientific community has already gained experiences and developed capabilities, infrastructure, and instruments to enhance the economic benefits of open science which can be useful to apply in the current situation. For example, the Human Genome Project and its more recent development of the Structural Genoma Consortium are providing evidence about the economic benefits associated to openness (Simon Tripp and Grueber 2011). There have also been multiple experiments on open source health-related business models (M4K Pharma 2020) as well as other open source drug development projects for neglected diseases which provide concrete evidence on breakthroughs and opportunities created by open science (OSM; TSL; Spangenberg et al. 2013; Veale 2019).
In sum, the pandemic is shaking structures and forcing us to rethink the status quo. In the scientific field, traditional research methods are being questioned not only by external actors claiming greater commitment to society, but also within the research community. A recent article in the American Economic Review argues that research productivity is falling (Bloom et al. 2020).  This is particularly present in pharmaceutical research where the therapeutic value of new drugs is marginal and the productivity of R&D in medicine is shrinking (Scannell et al. 2012). This has been associated with the expansion of patents that, far from promoting, hinders the generation of new ideas by occluding the collective knowledge previously generated. Let us hope that the movements produced by this extraordinary situation allow the scientific and political community to see the opportunities that open science pathways create. We need open science practices to be sustained after the pandemic ends as it may be the way to improve the impact that science, technology and innovation have on the numerous challenges faced by humanity.
 The virus strain that causes coronavirus disease 2019
 Where the populations suffering the disease tend to be poor and the cure/treatment for the disease does not have a potential market with high purchasing power
 Competition and secrecy, rather than collaboration and openness, define both market success and the opportunity to obtain exclusive rights through intellectual property.
 Medida como crecimiento de la productividad total de factores por investigador
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