The knowledge production model of the New Sciences: The case of Translational Medicine

Abstract

The tremendous achievements of life sciences research in the last 40 years have brought relatively little improvements to medical practice, suggesting a deficiency of the medical innovation system in capitalizing on these fundamental advances. We argue that a major cause of the poor innovative performance is the slow adaption of the scientific system to the novel research technologies made available by the progress in the life sciences - rather than resistance of practitioners. We interpret the changes in the organization of medical research through the lenses of the theory of New Sciences, which puts forward that the application of novel research technologies promotes new epistemological and methodological approaches to the investigation of complex phenomena, increasing interdisciplinary intellectual exchanges. In oncology, Translational Research, that embodies the features of a new science, coexists with the standard model of knowledge production in clinical medicine. Our comparison of the two approaches finds that Translational Research allows investigations across diverse and cognitively distant knowledge bases, thanks to the intensive use of research technologies that emerge from fundamental research. Unlike standard studies, the scientific impact of translational studies benefits from the adoption of an interdisciplinary approach. However, translational studies have an overall lower impact than their counterpart.

DIY Laboratories and business innovation ecosystems: The case of pharmaceutical industry

“…However, they still face another profound challenge brought by the biological revolution, i.e. how to effectively transform latest findings in biopharma research into real R&D outputs (Lauto and Valentin, 2016). In fact, over the last two decades when advanced biotechnologies were intensively applied to the pharmaceutical R&D, the success rate of new drug development projects dramatically declined (Tierney et al, 2013;Malerba and Orsenigo, 2015).…”

“…In order to fully capitalise on the recent advancement in biopharma research, various R&D models, such as biopharma consortium and collaborative discovery platform, are proposed and tested (Allarakhia and Walsh, 2012;Sabatier et al, 2012;Tierney et al, 2013;Lauto and Valentin, 2016). These new models aim to introduce multiple stakeholders into the biopharma business ecosystem (Lauto and Valentin, 2016), by which firms, research institutes, and others Citation: Wu, Q. and He, Q. ( 2020) "DIY Laboratories and Business Innovation Ecosystems: The Case of Pharmaceutical Industry", Technological Forecasting & Social Change, In press.…”

“…( 2020) "DIY Laboratories and Business Innovation Ecosystems: The Case of Pharmaceutical Industry", Technological Forecasting & Social Change, In press. can share their respective knowledge bases, resources and technical competencies in search for specific biopharma innovations (Tierney et al, 2013;Lauto and Valentin, 2016).…”

The nature of rapid response to COVID-19 in Latin America: an examination of Argentina, Brazil, Chile, Colombia and Mexico

“…This specialization in disciplinary profile was expected due to nature of the COVID-19 topic, favoring knowledge accumulation. However, it may be less conducive to technological problem-solving and innovation, which requires an interdisciplinary outlook (Gibbons et al, 1994;Lauto and Valentin, 2016;Institute of Medicine, 2005).…”

An empirical knowledge production function of agricultural research and extension: The case of the University of California Cooperative Extension

“…The analysis suggests a more productive knowledge process in which innovative firms use knowledge and information produced by external sources. Working on a related industry, Lauto and Valentin (2016) estimated a knowledge production function for what was coined the new science development model for clinical medicine, in which research can be conducted in a transnational effort, or locally. This is a very interesting distinction that may indicate the efficiency of transnational simultaneous research benefitting from a variety of conditions and its superiority to knowledge spillover of research conducted separately.…”