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Koichi Sumikura Director of Research, NISTEP

Are We Making the Best Use of Academic Knowledge in Innovation System ? Introduction: the studies on the impact of academic knowledge in innovation system. Koichi Sumikura Director of Research, NISTEP. Key issues.

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Koichi Sumikura Director of Research, NISTEP

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  1. Are We Making the Best Use of Academic Knowledge in Innovation System?Introduction: the studies on the impact of academic knowledge in innovation system. Koichi Sumikura Director of Research, NISTEP

  2. Key issues • To what extent does the corporations count on academic knowledge, produced by basic research in universities or PRIs, as sources of innovation? • Can we measure to what extent academic research contributes to innovation and leads to social and/or economic impact?

  3. Cohen, W. M. and D. A. Levinthal (1990). Absorptive capacity: A new perspective on learning and innovation, Administrative Science Quarterly, 35(1), 128–152. • Specifically, firms may conduct basic research less for particular results than to be able to provide themselves with the general background knowledge that would permit them to exploit rapidly useful scientific and technological knowledge through their own innovations or to be able to respond quickly – become a first second – when competitors come up with a major advance.

  4. Mansfield, E. (1998) “Academic research and industrial innovation: An update of empirical findings,” Research Policy, 26, 773-776. • To sum up, the evidence for 1986-1994 confirms out earlier results for 1975-1985: over 10% of the new products and processes introduced in these industries could not have been developed (without substantial delay) in the absence of recent academic research.

  5. Mansfield, E. (1998) “Academic research and industrial innovation: An update of empirical findings,” Research Policy, 26, 773-776. Percentage of new products based on recent academic research, 1986-1994 and 1975-1985.

  6. Zucker, LG et al. (2002) “Commercializing knowledge: university science, knowledge capture, and firm performance in biotechnology,”Management Science, 48(1), 138-153. • A robust indicator of a firm’s tacit knowledge capture (and strong predictor of its success) is the number of research articles written jointly by firm scientists and discovering, “star” scientists, nearly all working at top universities. An operationally attractive generalization of our star measure—collaborative research articles between firm scientists and top research university scientists—replicates the impact on firm success. In panel analyses, publications by firm scientists with stars and/or top 112 university scientists increase the number and citation rate for firm patents.

  7. Cockburn, Iain M. & Henderson, Rebecca M. (1998) “Absorptive Capacity, Coauthoring Behavior, and the Organization of Research in Drug Discovery,”Journal of Industrial Economics, 46(2), 157-182 • We have suggested firms wishing to take advantage of public sector research must do more than simply invest in in-house basic research: they must also actively collaborate with their public sector colleagues. Further, we have shown that one measure of the nature and extent of this collaboration, coauthorships across institutions, is correlated with private sector research productivity.

  8. Toole, Andrew A. (2012) “The impact of public basic research on industrial innovation: Evidence from the pharmaceutical industry,” Research Policy, 41, 1-12. • Applying an econometric approach, this study found a systematic relationship between NIH investments into basic biomedical research performed in academic laboratories and pharmaceutical industry innovation. The preferred model implies a 1% increase in the stock of public basic research is associated with a 1.8% increase in the number of industry new molecular entity (NME) applications after a substantial lag. • For an average NME, the lag between public investment and industry application is seventeen to twenty fouryears.

  9. Stevens, Ashley J. et al. (2011) “The Role of Public-Sector Research in the Discovery of Drugs and Vaccines,”New England Journal of Medicine, 364(6), 535-541. • We found that during the past 40 years, 153 new FDA-approved drugs, vaccines, or new indications for existing drugs were discovered through research carried out in PSRIs. These drugs included 93 small-molecule drugs, 36 biologic agents, 15 vaccines, 8 in vivo diagnostic materials, and 1 over-the-counter drug. More than half of these drugs have been used in the treatment or prevention of cancer or infectious diseases. PSRI-discovered drugs are expected to have a disproportionately large therapeutic effect.

  10. Survey on Research Activities of Private Corporations in Japan 2011, NISTEP • Enquiry Target- corporations in Japan- capital> 100M yen- engaged in R&D- 3,443 corporations • 1,263 responded (37.4%) • Enquiry Period: Feb-Mar 2012 • R&D activities in FY2010 was surveyed.

  11. Results of recent studies Koichi Sumikura (NISTEP, GRIPS) Hiromi Saito (NISTEP, Chiba Univ.)

  12. <1> Saito, Hiromi and Sumikura, Koichi (2010)“An Empirical Analysis on Absorptive Capacity Based on Linkage with Academia,” International Journal of Innovation Management, 14(3), 491-509. • We empirically explained how scientific knowledge assimilated from academia affects corporate performance, particularly in the pharmaceutical industry of Japan. • We use balanced panel data on 46 pharmaceutical firms in Japan for the period 1992–2005. Then, we introduced a new concept, propensity to capture basic research (PCBR), to index how much scientific knowledge firms have assimilated from universities and public research institutes. • We used this index to verify whether absorption of such knowledge influences corporate performance. According to econometric analysis, PCBR is positively significant for patent applications and patent efficiency but not for number of approved drugs. • This obviously implies that scientific knowledge assimilated from academia is effective for technological performance in firms.

  13. How to count PCBR ? ~An Example of our patent description data~ 1 (Y univ) + 1 (Mr.X*) =2 →B firm’s PCBR is 2. Number of co-application N is number of patent co-application with co-applicant N. *In Japanese data before April 2004 , we can usually regard individual names as researchers in university.

  14. Estimation results of patent efficiency (obsolescence rate = 10%). ***; 1% significant, **; 5% significant, *; 10% significant

  15. <2> Saito, Hiromi and Sumikura, Koichi “Analysis on absorption of scientific knowledge using database on collaborative research in Japan (tentative),” forthcoming. • Target: collaborative research in National University in Japan. • Data period: 1983～2002 • Data contents: year, name of university researchers, name of company, annual research budget, etc. • Focusing on pharmaceutical companies in Japan. • We built up a panel data of companies by processing original data.

  16. Data Processing <Original Data> In 1983 the X company carried out 3 collaborative research. <After Processing> 17

  17. Result of estimation

  18. Summary focus on absorption of scientific knowledge Basic Research (Scientific knowledge) Applied research Development research Patent △ Patentefficiency○ Drug

  19. <3> GRIPSSurvey (K.Sumikura, H.Saito) • “GRIPS Corporate Survey”（Respondent: mainly managementof a corporation）- 2008.12.17- 2009.1.5- 5,123 (among 20,455, 25%) corporations carrying out R&D responded.- 23 Parmaceuticals. • “GRIPS Pharma/Biotech Inventors Survey” （Respondent: corporate inventors）- 2009.12.1-18- 332 inventors were extracted, 48% collected. • “GRIPS ICT Inventors Survey” (Respondent: corporate inventors)- 2012.2.17-3.14- 356 inventors were extracted, 36% collected.“In your company what is the percentage of products or services that could not have been developed in the absence of research results in universities or PRIs?”

  20. (Pharma/Bio) Firm-level vs Inventor-level GAP Drug firms; N=23, Inventors; N=149 Data Source; GRIPS Corporate Survey ; GRIPS Pharma/Biotech inventors survey

  21. ICT InventorvsPharma/Biotech Inventor Difference ICT; N =126, Pharma/bio; N =149 Data source; GRIPS ICT inventorssurvey, GRIPS Pharma/Biotech inventors survey

  22. (ICT) Firm-level vs Inventor-level GAP Inventors; N =126, Managers; N =219 Data source; GRIPS ICT inventorssurvey, GRIPS Pharma/Biotech inventors survey

  23. <4> Case Study: Tocilizumab (Actemra) • Developed by collaborative research between Prof. TadamitsuKishimoto (Osaka University) and Chugai Pharmaceutical Co., Ltd. • Recombinant antibody drug (humanized anti human IL-6 receptor monoclonal antibody) • Product of Chugai Pharmaceutical Co., Ltd. that is under strategic alliance with Roche. • Drug for Castleman’s disease (approved in 2005) • Drug for rheumatoid arthritis(approved in 2008) • The first made-in-Japan antibody drug • Approved in more than 100 countries and sold in more than 90 countries. • Going to be a blockbuster (more than 1 billion dollars sales worldwide) in 2013.

  24. Key to success, according to interview of Prof. Kishimoto • Prof. Kishimoto directly talked with the president of Chugai and explained potential of anti IL-6 receptor antibody as new drug. Good communication and reliance between Prof. Kishimoto and president of Chugai made it possible for Chugai to invest in building fermentation tanks (volume of 10t) at Utsunomiya.-> Direct communication between star scientist and top management is key to bridging the gap between management and R&D. • Prof. Kishimoto started his career as clinician and later changed his way to basic science. As he knew both culture of basic science and clinical site, he could successfully accomplish innovative drug development.-> Promotion of translational research, bridging the gap between basic science and clinical site, is key to successful new drug discovery.

  25. Inhibitory environment forscience-driven innovation Recognition gap on contribution of academic knowledge to innovation between corporate management and inventor. Corporate management hesitating to decide on huge investment on R&D and insufficient budget for commercial development. Failure to develop new drugs. Lower evaluation of academic knowledge , from the viewpoint of corporate management.

  26. Promotive environment forscience-driven innovation Recognition gap on contribution of academic knowledge to innovation between corporate management and inventor. Direct communication between star scientist and top management. Decision on huge investment on product development. Promotion of translational research. Development of new drugs. Higher evaluation of academic knowledge , from the viewpoint of corporate management.

  27. In this symposium, • Koichi Sumikura “Introduction: the studies on the impact of academic knowledge in innovation system.” • Stevens, Ashley “The Role of Public-Sector Research in the Discovery of Drugs and Vaccines.” • Zucker, Lynne G. “Accelerating the economic impact of basic research.” • Maki, Kanetaka “The Impact of Technology Transfer Office: Evidence from Natural Experiment in Japan.” • Mu, Rongping “Policy framework for integrating all activities of innovation in China?” • Song, Jong-Guk “Linking Academic Knowledge to Social Needs.” • Discussion

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