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Did the COVID-19 pandemic propel usage of AI in pharmaceutical innovation? New evidence from patenting data

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  • Rathi, Sawan
  • Majumdar, Adrija
  • Chatterjee, Chirantan

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.

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  • Rathi, Sawan & Majumdar, Adrija & Chatterjee, Chirantan, 2024. "Did the COVID-19 pandemic propel usage of AI in pharmaceutical innovation? New evidence from patenting data," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    • Handle: RePEc:eee:tefoso:v:198:y:2024:i:c:s004016252300625x
    DOI: 10.1016/j.techfore.2023.122940
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    as
    1. Erik Brynjolfsson & Daniel Rock & Chad Syverson, 2021. "The Productivity J-Curve: How Intangibles Complement General Purpose Technologies," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(1), pages 333-372, January.
    2. Hélène Dernis & Flavio Calvino & Laurent Moussiegt & Daisuke Nawa & Lea Samek & Mariagrazia Squicciarini, 2023. "Identifying artificial intelligence actors using online data," OECD Science, Technology and Industry Working Papers 2023/01, OECD Publishing.
    3. Daron Acemoglu & Pascual Restrepo, 2020. "The wrong kind of AI? Artificial intelligence and the future of labour demand," Cambridge Journal of Regions, Economy and Society, Cambridge Political Economy Society, vol. 13(1), pages 25-35.
    4. Wagner, Stefan & Wakeman, Simon, 2016. "What do patent-based measures tell us about product commercialization? Evidence from the pharmaceutical industry," Research Policy, Elsevier, vol. 45(5), pages 1091-1102.
    5. Igna, Ioana & Venturini, Francesco, 2023. "The determinants of AI innovation across European firms," Research Policy, Elsevier, vol. 52(2).
    6. DiMasi, Joseph A. & Grabowski, Henry G. & Hansen, Ronald W., 2016. "Innovation in the pharmaceutical industry: New estimates of R&D costs," Journal of Health Economics, Elsevier, vol. 47(C), pages 20-33.
    7. Charles Ka Yui Leung & Joe Cho Yiu Ng & Edward Chi Ho TANG, 2019. "What do we know about Housing Supply? The case of Hong Kong," GRU Working Paper Series GRU_2019_012, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
    8. Rotolo, Daniele & Hicks, Diana & Martin, Ben R., 2015. "What is an emerging technology?," Research Policy, Elsevier, vol. 44(10), pages 1827-1843.
    9. Harry Bloch & Stan Metcalfe, 2018. "Innovation, creative destruction, and price theory," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 27(1), pages 1-13.
    10. Wei Chen & Zaiyan Wei & Karen Xie, 2022. "The Battle for Homes: How Does Home Sharing Disrupt Local Residential Markets?," Management Science, INFORMS, vol. 68(12), pages 8589-8612, December.
    11. Iacus, Stefano & King, Gary & Porro, Giuseppe, 2009. "cem: Software for Coarsened Exact Matching," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 30(i09).
    12. Haris Tabakovic & Thomas G. Wollmann, 2018. "From Revolving Doors to Regulatory Capture? Evidence from Patent Examiners," NBER Working Papers 24638, National Bureau of Economic Research, Inc.
    13. David Dranove & Craig Garthwaite, 2022. "Artificial Intelligence, the Evolution of the Health Care Value Chain, and the Future of the Physician," NBER Chapters, in: The Economics of Artificial Intelligence: Health Care Challenges, pages 9-45, National Bureau of Economic Research, Inc.
    14. Lei, Zhen & Wright, Brian D., 2017. "Why weak patents? Testing the examiner ignorance hypothesis," Journal of Public Economics, Elsevier, vol. 148(C), pages 43-56.
    15. Erzurumlu, S. Sinan & Pachamanova, Dessislava, 2020. "Topic modeling and technology forecasting for assessing the commercial viability of healthcare innovations," Technological Forecasting and Social Change, Elsevier, vol. 156(C).
    16. Lynn Wu & Lorin Hitt & Bowen Lou, 2020. "Data Analytics, Innovation, and Firm Productivity," Management Science, INFORMS, vol. 66(5), pages 2017-2039, May.
    17. Hammadou, Hakim & Paty, Sonia & Savona, Maria, 2014. "Strategic interactions in public R&D across European countries: A spatial econometric analysis," Research Policy, Elsevier, vol. 43(7), pages 1217-1226.
    18. Momeni, Abdolreza & Rost, Katja, 2016. "Identification and monitoring of possible disruptive technologies by patent-development paths and topic modeling," Technological Forecasting and Social Change, Elsevier, vol. 104(C), pages 16-29.
    19. Iain M. Cockburn & Samuel Kortum & Scott Stern, 2002. "Are All Patent Examiners Equal? The Impact of Examiner Characteristics," NBER Working Papers 8980, National Bureau of Economic Research, Inc.
    20. Frank Tietze & Pratheeba Vimalnath & Leonidas Aristodemou & Jenny Molloy, 2020. "Crisis-Critical Intellectual Property: Findings from the COVID-19 Pandemic," Papers 2004.03715, arXiv.org, revised May 2020.
    21. Sophie Boutillier & Blandine Laperche & Didier Lebert & Sana Elouaer-Mrizak, 2023. "A systemic analysis of the technological trajectory at company level based on patent data: The case of Sanofi's vaccine technology," Post-Print halshs-04028255, HAL.
    22. Matthew Blackwell & Stefano Iacus & Gary King & Giuseppe Porro, 2009. "cem: Coarsened exact matching in Stata," Stata Journal, StataCorp LP, vol. 9(4), pages 524-546, December.
    23. Agrawal, Ajay & Gans, Joshua S. & Goldfarb, Avi, 2019. "Exploring the impact of artificial Intelligence: Prediction versus judgment," Information Economics and Policy, Elsevier, vol. 47(C), pages 1-6.
    24. Avi Goldfarb & Bledi Taska & Florenta Teodoridis, 2020. "Artificial Intelligence in Health Care? Evidence from Online Job Postings," AEA Papers and Proceedings, American Economic Association, vol. 110, pages 400-404, May.
    25. Secundo, Giustina & Del Vecchio, Pasquale & Simeone, Luca & Schiuma, Giovanni, 2020. "Creativity and stakeholders' engagement in open innovation: Design for knowledge translation in technology-intensive enterprises," Journal of Business Research, Elsevier, vol. 119(C), pages 272-282.
    26. Flavio Calvino & Lea Samek & Mariagrazia Squicciarini & Cody Morris, 2022. "Identifying and characterising AI adopters: A novel approach based on big data," OECD Science, Technology and Industry Working Papers 2022/06, OECD Publishing.
    27. Sawan Rathi & Anindya S. Chakrabarti & Chirantan Chatterjee & Aparna Hegde, 2022. "Pandemics and technology engagement: New evidence from m‐Health intervention during COVID‐19 in India," Review of Development Economics, Wiley Blackwell, vol. 26(4), pages 2184-2217, November.
    28. Sipior, Janice C., 2020. "Considerations for development and use of AI in response to COVID-19," International Journal of Information Management, Elsevier, vol. 55(C).
    29. Manuel Trajtenberg, 2018. "Artificial Intelligence as the Next GPT: A Political-Economy Perspective," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 175-186, National Bureau of Economic Research, Inc.
    30. Yang, Chih-Hai, 2022. "How Artificial Intelligence Technology Affects Productivity and Employment: Firm-level Evidence from Taiwan," Research Policy, Elsevier, vol. 51(6).
    31. Stefano Bianchini & Moritz Müller & Pierre Pelletier, 2022. "Artificial intelligence in science: An emerging general method of invention," Post-Print hal-03958025, HAL.
    32. Kim, Yee Kyoung & Oh, Jun Byoung, 2017. "Examination workloads, grant decision bias and examination quality of patent office," Research Policy, Elsevier, vol. 46(5), pages 1005-1019.
    33. Laura B. Cardinal, 2001. "Technological Innovation in the Pharmaceutical Industry: The Use of Organizational Control in Managing Research and Development," Organization Science, INFORMS, vol. 12(1), pages 19-36, February.
    34. Boutillier, Sophie & Laperche, Blandine & Lebert, Didier & Elouaer-Mrizak, Sana, 2023. "A systemic analysis of the technological trajectory at company level based on patent data: The case of Sanofi's vaccine technology," Technovation, Elsevier, vol. 124(C).
    35. Alfons Palangkaraya & Elizabeth Webster & Paul H. Jensen, 2011. "Misclassification between Patent Offices: Evidence from a Matched Sample of Patent Applications," The Review of Economics and Statistics, MIT Press, vol. 93(3), pages 1063-1075, August.
    36. Lee, Sang M. & Trimi, Silvana, 2021. "Convergence innovation in the digital age and in the COVID-19 pandemic crisis," Journal of Business Research, Elsevier, vol. 123(C), pages 14-22.
    37. Iain M. Cockburn & Rebecca Henderson & Scott Stern, 2018. "The Impact of Artificial Intelligence on Innovation," NBER Working Papers 24449, National Bureau of Economic Research, Inc.
    38. Izumi Yamashita & Akiyoshi Murakami & Stephanie Cairns & Fernando Galindo-Rueda, 2021. "Measuring the AI content of government-funded R&D projects: A proof of concept for the OECD Fundstat initiative," OECD Science, Technology and Industry Working Papers 2021/09, OECD Publishing.
    39. Wang, Qinyu Ryan & Zheng, Yanfeng, 2022. "Nest without birds: Inventor mobility and the left-behind patents," Research Policy, Elsevier, vol. 51(4).
    40. Alexander V. Giczy & Nicholas A. Pairolero & Andrew A. Toole, 2022. "Identifying artificial intelligence (AI) invention: a novel AI patent dataset," The Journal of Technology Transfer, Springer, vol. 47(2), pages 476-505, April.
    41. Iacus, Stefano M. & King, Gary & Porro, Giuseppe, 2012. "Causal Inference without Balance Checking: Coarsened Exact Matching," Political Analysis, Cambridge University Press, vol. 20(1), pages 1-24, January.
    42. Giovanni Abramo & Ciriaco D’Angelo & Flavia Di Costa & Marco Solazzi, 2011. "The role of information asymmetry in the market for university–industry research collaboration," The Journal of Technology Transfer, Springer, vol. 36(1), pages 84-100, February.
    43. Singh, Anuraag & Triulzi, Giorgio & Magee, Christopher L., 2021. "Technological improvement rate predictions for all technologies: Use of patent data and an extended domain description," Research Policy, Elsevier, vol. 50(9).
    44. Iain M. Cockburn & Rebecca Henderson & Scott Stern, 2018. "The Impact of Artificial Intelligence on Innovation: An Exploratory Analysis," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 115-146, National Bureau of Economic Research, Inc.
    45. Junbyoung Oh & Yee Kyoung Kim, 2017. "Examination workloads, grant decision bias and examination quality of patent office," Inha University IBER Working Paper Series 2017-3, Inha University, Institute of Business and Economic Research, revised Apr 2017.
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    Cited by:

    1. Miozza, Mario & Brunetta, Federica & Appio, Francesco Paolo, 2024. "Digital transformation of the Pharmaceutical Industry: A future research agenda for management studies," Technological Forecasting and Social Change, Elsevier, vol. 207(C).
    2. Fang, Xubing & Liu, Maotao, 2024. "How does the digital transformation drive digital technology innovation of enterprises? Evidence from enterprise's digital patents," Technological Forecasting and Social Change, Elsevier, vol. 204(C).

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    More about this item

    Keywords

    Innovation management; AI; Pharmaceutical industry; Patents; Pandemic;
    All these keywords.

    JEL classification:

    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • I10 - Health, Education, and Welfare - - Health - - - General

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