2019年冠状病毒病(COVID-19)
步伐
大流行
制药工业
稳健性(进化)
生产力
计算机科学
2019-20冠状病毒爆发
数据科学
产业组织
业务
经济
医学
传染病(医学专业)
病理
宏观经济学
病毒学
化学
爆发
地理
基因
药理学
疾病
生物化学
大地测量学
作者
Sawan Rathi,Adrija Majumdar,Chirantan Chatterjee
标识
DOI:10.1016/j.techfore.2023.122940
摘要
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.
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