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Title: Did the COVID-19 pandemic propel usage of AI in pharmaceutical innovation? New evidence from patenting data
Authors: Rathi, Sawan
Majumdar, Adrija
Chatterjee, Chirantan
Keywords: Innovation management; AI; Pharmaceutical industry; Patents; Pandemic
Issue Date: 1-Jan-2024
Publisher: Elsevier
Abstract: It is now much discussed that Artificial Intelligence (AI) as a General-Purpose Technology (GPT) can resolve the efficiency problems of industries, including in pharmaceutical markets where productivity challenges continue in costs and time for new drug discovery. But did the COVID-19 pandemic inadvertently accelerate the pace of AI adoption in pharmaceutical innovation? We answer this question using novel data on pharmaceutical patents. We use two different databases to analyze abstracts of pharmaceutical patents applied in the USA. Topic modeling was used to identify patents with technical artifacts and classify them as treated group AI-adopting patents. An AI dictionary is used to match AI-related keywords in the patent abstracts. Subsequently, using a difference-in-differences research design we observe that both presence and count of AI keywords in pharmaceutical patents have increased with pandemic. An increase in AI is also related to reduced time taken from application to publication of a patent suggesting innovation efficiencies in the industry. Finally, we find that results are driven by firms that have already built AI capability in the past. Our results remain consistent with various robustness checks, and we conclude by discussing managerial and policy implications of our findings.
ISSN: 18735509
Appears in Collections:Open Access Journal Articles

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