Browsar Examensarbeten för kandidatexamen // Bachelor Theses efter Författare "Ågren, Felix"
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- PostCuring a 70-year-old disease(2021) Svennung, Gustaf; Ekström, August; Halleröd, Oscar; Torell, Stina; Jonsson, Erik; Ågren, Felix; Chalmers tekniska högskola / Institutionen för teknikens ekonomi och organisation; Bohlin, Erik; Isaksson, AndersProblem: The pharmaceutical industry has for a long time been characterized by exponentially declining R&D productivity, which even got its own term – Eroom's law. The R&D productivity has in the last ten years experienced a turnaround, and the factors underlying this productivity increase are yet to be fully understood. The underlying factors must be well understood so that the productivity turnaround can be preserved and continue in the future. Aim: The report aims to investigate the underlying factors to the R&D productivity turnaround. Method: The study is divided into two parts: one literature study of previous research, and one interview study with Swedish industry experts. It has an abductive approach, basing the findings on the existing theory and complementing it with experience and knowledge from interview respondents. Results and implications: The result highlights six main factors that relate to the turnaround in R&D productivity. These are the types of drugs developed and the role of increased scientific understanding, externalization of R&D, the role of the regulators, the development of clinical trials, the role of digital technology, and the role of managerial efforts. Implications regarding key differentiation between external and internal factors as well as the longevity of the productivity increase are further discussed. Conclusion: The study concludes that previous research conforms well to the perspective of the respondents, with particular emphasis on the importance of greater scientific understanding, increased specialization, regulatory incentives and flexibility, and efficient managerial efforts. A conceptual framework is also provided that can be used to better understand the intercorrelation between the different factors.