How Can We Improve the Transformation Success Rate of Research Results in the Pharmaceutical Industry? The Game Theoretic Model of Technology Transfer Subjects

Sun, Ziyuan; Wang, Man; Zhang, Weiwei; Li, Yanli; Wang, Dan; Dong, Feng

doi:10.3390/ijerph16091588

Cited by 5 publications

(4 citation statements)

References 62 publications

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“…Research on technology transfer also encompasses various areas such as diseases, medicine, and pharmacy [52][53][54][55][56][57][58][59][60][61]. There are relatively fewer publications on the methodology for evaluating technology transfer [62][63][64][65]. Efficient technology transfer in the value chain can be crucial in the diffusion of new innovations and technology-associated knowledge [66].…”

Section: Technology Transfer Landscapementioning

confidence: 99%

Multivariate Pharma Technology Transfer Analysis: Civilization Diseases and COVID-19 Perspective

Śledzik

Płoska

Chmielewski

et al. 2023

IJERPH

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The importance of studying civilization diseases manifests itself in the impact of changing lifestyles, on the number of deaths and causes of death. Technology transfer plays an important role in the prevention and treatment of these diseases. Through this, it is possible to transfer new treatments and diagnostics to clinics and hospitals more quickly and effectively, which leads to better healthcare for patients. Technology transfer can also aid in the development of new drugs and therapies that can be effective in the treatment of civilization diseases. The paper aims to evaluate the technology transfer process in the field of civilization diseases, using COVID-19 as an example of a pandemic that requires quick development and transfer of technology. To achieve the assumed goal, we propose a multivariate synthetic ratio in the field of civilization diseases (SMTT—Synthetic Measure of Technology Transfer) to analyze data from the Global Data database. We used sub-measures like SMTT_value (Synthetic Measure of Technology Transfer_value) and SMTT_quantity (Synthetic Measure of Technology Transfer_quantity) to measure technology transfer and put the data into a graph. Our analysis focuses on 14 diseases over a period of 10 years (2012–2021) and includes nine forms of technology transfer, allowing us to create a tool for analysing the process in multiple dimensions. Our results show that COVID-19 is similar in terms of technology transfer to diseases such as diabetes, cardiovascular diseases, neurodegenerative diseases, and breast cancer, even though data for COVID-19 is available for only 2 years.

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Section: Technology Transfer Landscapementioning

confidence: 99%

Multivariate Pharma Technology Transfer Analysis: Civilization Diseases and COVID-19 Perspective

Śledzik

Płoska

Chmielewski

et al. 2023

IJERPH

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“…Friedman [39] argued that evolutionary game theory overcame the limitations of traditional games based on the complete rational hypothesis and had great application prospects in the economic field. Therefore, it was closer to reality when studying the safety regulation of chemical enterprises [40][41][42].…”

Section: Literature Reviewmentioning

confidence: 99%

Research on Safety Regulation of Chemical Enterprise under Third-Party Mechanism: An Evolutionary Approach

Xing

2019

Symmetry

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In recent years, China’s chemical industry has incurred frequent safety accidents which seriously impact the social environment and public safety. Traditional approaches have reached a bottleneck due to a lack of relevant professionals in the government regulation of chemical enterprise safety production. Thus, a new safety regulation mechanism should be conducted. In this paper, we constructed an evolutionary game model of chemical industry safety regulation based on limited rationality, and the influence of main parameters on the equilibrium evolution process is studied by system dynamics simulation. The results show that government regulation authorities play a leading role in the process of chemical industry safety regulation and increasing punishment will help to achieve an evolutionary stable strategy (ESS). What is more, the feasibility and effectiveness of the third-party regulation service mechanism are verified, and the market access threshold of third-party regulation service needs to be improved to stop the occurrence of rent-seeking activities in the regulatory process. In summary, the introduction of third-party regulation service entities to the chemical industry safety regulation process has far-reaching implications for promoting the healthy development of China’s chemical industry.

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“…In the realm of pharmaceutical and life sciences, university technology transfer (UTT) refers to the process of knowledge spillover and valorization, with the objective of translating university-based technology and knowledge into products and services (Bradley et al, 2013;Siegel et al, 2003;Sun et al, 2019). Numerous UTT models and methods have been reported in previous literature, which encompasses, among others, spillover of transitional research findings, incubation of entrepreneurship-related intellectual properties, and creation of commercial products and practical applications (Boh et al, 2016;Cunningham et al, 2019;Grimpe & Fier, 2010;Siegel et al, 2003).…”

Section: University Technology Transfermentioning

confidence: 99%

“…The process of UTT is complex and entails a variety of requirements and dynamics (Sun et al, 2019;York & Ahn, 2012). In the scientific phase in the universities, Triulzi et al (2014) demonstrated that adequate funding is pivotal in motivating universities to generate new scientific knowledge, which can subsequently spill over into the regional societal-industrial ecosystem through various modes of technology transfer.…”

Section: University Technology Transfermentioning

confidence: 99%

Managing University-Industry Collaborative Innovation in the Pharmaceutical Industry

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The significance of university-industry collaboration becomes even more pronounced within the pharmaceutical R&D context. Such collaborations provide a platform to address potential challenges by offering access to cutting-edge research, specialized facilities, and expertise. Collaborative models, such as multi-university partnerships and university-industry contract research, have emerged as viable methods to support innovation in the pharmaceutical industry. Such collaborations have facilitated universities in accessing invaluable resources from their industrial counterparts, while industries have benefited from enhanced technological capabilities and foundational scientific knowledge. This symbiotic relationship not only benefits the primary stakeholders but also has broader societal implications, as it accelerates the transfer of scientific results to the market. This research adopts a broad definition of pharmaceutical university-industry R&D collaboration. The primary objective is to gain insights to answer the overarching question: How to manage innovation in pharmaceutical university-industry R&D practices? To answer this, the present research employs both quantitative (Chapters 2 and 3) and qualitative (Chapters 4 and 5) methodologies, with a multi-level analysis encompassing landscape- (Chapter 2), collaboration- (Chapter 3), university- (Chapter 4), and company (Chapter 5) perspectives. Based on the landscape perspective, Chapter 2 uses a bibliometric approach to analyze historical and emerging topics in the pharmaceutical UIC R&D context. The study identifies a rise in related publications, emphasizing the research’s importance. The comprehensive review categorizes publications into three levels that are industrial and organizational innovation strategy, -structure, and -culture. The chapter advocates for broader engagement by academic and commercial entities, emphasizing the potential of R&D alliances in the pharmaceutical industry, where university-industry collaborations are particularly promising. Chapter 3, using Neglected Tropical Diseases as the focal point, delves into whether the type of PPPs influences the initiation and duration of NTD-related clinical trials. The research identifies various collaborative types, among which NGO- and public sector-led collaborations are the major subtypes. Key determinants shaping these collaborations encompass scientific, logistical, political, and financial aspects. The chapter emphasizes the pivotal role companies play in combating NTDs, either independently or within public-private partnerships. The identified characteristics and determinants provide suggestions for practitioners to further optimize R&D strategies. Chapter 4 delves into the micro-foundations of dynamic capabilities within the university technology transfer process, drawing from empirical cases of the Industry Alliance Office and the Demonstrator Lab. For sensing capabilities, this chapter underscores the importance of timely identification of opportunities through internal competencies and external partnerships. On the seizing front, the research highlights the critical role of universities in aligning with industrial entities to maximize detected opportunities, emphasizing resource co-allocation and collaborative business models. Reconfiguring capabilities are important for universities to position themselves as central orchestrators within the broader of university-industry ecosystem. It is also important for partnering companies and academic entrepreneurs to employ dynamic capabilities with the aim of academic entrepreneurship. Chapter 5 delves into the micro-foundations of dynamic capabilities essential for academic entrepreneurship within the university-industry ecosystem. It emphasizes that sensing capabilities empower them to strategically allocate resources and address potential challenges. The chapter also underscores the significance of seizing capabilities in facilitating knowledge integration and partnership management. To ensure sustained innovation, it is important for high-tech enterprises to develop reconfiguring capabilities. To further research pharmaceutical UIC R&D innovation management, Chapter 6 then puts forward various recommendations to different stakeholders including universities, research institutes, startup companies, and regulatory agencies. Chapter 6 also adds some of the limitations of Chapters 2-5, based on which the present research hopes to provide some suggestions for future research.

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How Can We Improve the Transformation Success Rate of Research Results in the Pharmaceutical Industry? The Game Theoretic Model of Technology Transfer Subjects

Cited by 5 publications

References 62 publications

Multivariate Pharma Technology Transfer Analysis: Civilization Diseases and COVID-19 Perspective

Multivariate Pharma Technology Transfer Analysis: Civilization Diseases and COVID-19 Perspective

Research on Safety Regulation of Chemical Enterprise under Third-Party Mechanism: An Evolutionary Approach

Managing University-Industry Collaborative Innovation in the Pharmaceutical Industry

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