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“Pulling the Plug:” Time Allocation between Drug Discovery and Development Projects
Author(s) -
Subramanian Annapoornima M.,
Lévesque Moren,
van de Vrande Vareska
Publication year - 2020
Publication title -
production and operations management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.279
H-Index - 110
eISSN - 1937-5956
pISSN - 1059-1478
DOI - 10.1111/poms.13255
Subject(s) - drug discovery , restructuring , business , pharmaceutical industry , discontinuation , key (lock) , process (computing) , productivity , risk analysis (engineering) , industrial organization , operations management , process management , economics , computer science , finance , medicine , pharmacology , computer security , bioinformatics , surgery , macroeconomics , biology , operating system
Biotechnology and pharmaceutical firms invest billions of dollars in R&D, primarily in new drug discovery. Nonetheless, the industry is facing declining returns on R&D investments. Failure to discontinue less‐promising new drug discovery projects is a key driver of this decreased productivity. Hence, firms are scrambling to restructure the new drug discovery process to improve decision‐making and to limit the attrition rate to the early stages of drug discovery. Drawing on insights from the exploration–exploitation literature, our study addresses this timing problem by using a formal model and empirically testing its implications on how the time to discontinuation of new drug discovery projects are impacted by project‐ and firm‐specific characteristics, so that a firm's resources can be promptly redeployed to more fruitful endeavors. Our findings, based on an analysis of 1274 early‐stage drug discovery projects worldwide, suggest that the time to discontinuation of early‐stage drug discovery projects requires careful consideration of these project‐ and firm‐specific characteristics. These findings hold important implications for the industry, which is undergoing tremendous stress and transformation. The results also contribute to the exploration–exploitation literature by modeling and testing the time‐allocation decision between exploratory and exploitative activities.