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157 Seiten, Note: 1,6
List of Figures
List of Tables
List of Abbreviations
1.2. Objective, research gaps and research question
1.3. Definitions and concepts
1.5. Outline of the thesis
2.1. Analytical framework
2.2. Methodological approach
2.2.1. Research philosophy
2.2.2. Research perspective
2.2.3. Research strategy
2.3. Data collection
2.3.2. Secondary data
2.3.3. Design of the field phase
3. Theoretical framework
3.1. The sectoral innovation system
3.2. The innovation value chain and open innovation
3.3. Learning and idea generation through R&D collaborations
4. Research context
4.1. Self-reliance policy: Amendment of the patent law and introduction of the New Drug Policy (1947-1991)
4.2. The phase of liberalization, de-control and product patent (1991- today)
5. Key components of the SIS of the API sector in India
5.1. Descriptive Analysis
5.2. The Government of India
5.2.1. Overall policy framework
5.2.2. The patent regime
5.2.3. Product and quality regulations
5.3. The academia
5.4. The industry
5.4.1. Balance of Trade
5.4.2. Production of APIs
5.4.3. R&D intensity
5.4.4. R&D stages and skills to develop NCEs
6. R&D collaboration strategies
6.1. Sources of innovation information
6.2. Prime motives for R&D collaborative projects
6.3. Collaborative R&D projects aimed at early stage drug development
6.3.1. Invention stage of early stage R&D collaboration projects
6.3.2. Most important objectives of early stage R&D collaboration projects
6.3.3. The contribution to success of early stage R&D collaboration projects
6.3.4. Problems related to early stage R&D collaboration projects
6.4. R&D collaboration cases
6.4.3. Contract research and manufacturing services
6.4.4. Collaborative research projects
6.4.5. Public private R&D partnerships
7. Conclusion and research implications
7.1. Key findings and conclusion
7.2. Conclusions for theory
7.3. Limitations and avenues for further research
Appendix A: Interview guidelines for the firm and industry expert surveys
A 1. Survey for firms
A 2. Survey for industry experts
Appendix B: Lists of interviewed firms and industry experts
Appendix C: Survey results
Appendix D: Tables and Figures
Appendix E: SCImago Journal Ranking
Figure D 1: Social research model
Figure D 2: A model of the SIS approach
Figure D 3: The R&D process for pharmaceuticals (light blue shading) reflecting the integrated innovation value chain (dark blue shading)
Figure D 4: Revenue of the IPI, 2005-2020 (USD billion) (*indicates forecast)
Figure D 5: By absolute growth, India ranks fifth among the top ten pharmaceutical markets between 2005 and 2014
Figure D 6: The ten leading pharmaceutical markets by forecasted value increase between 2014 and 2019
Figure D 7: BoT of the Russian, Indian, and Brazilian pharmaceutical industry (in USD billion), 2005-2014
Figure D 8: Number of patents granted to Indian, Chinese, and Russian inventors in the technology field pharmaceuticals, 2000-2014
Figure D 9: Distribution of interviewee positions (n=24)
Figure D 10: R&D intensity (2014/2015) (n=9)
Figure D 11: Number of patents filed and granted (2010-2015) (n=9)
Figure D 12: The triad of the SIS of the API sector in India
Figure D 13: Bureaucratic and legal hurdles for pharmaceutical R&D activities (n=23)
Figure D 14: Evaluation of enforcement of IPR for R&D activities in the pharmaceutical industry in India (n=23)
Figure D 15: Evaluation of general infrastructure and high technology infrastructure for R&D activities in the pharmaceutical industry in India (n=23)
Figure D 16: Evaluation of finding qualified personnel (pharmacology) and finding qualified personnel (management) for R&D activities in the pharmaceutical industry in India (n=23)
Figure D 17: Evaluation of quality of education in general (n=15), quality of education related to pharmacy (n=23), and quality of education of other related disciplines (n=23) and their impact on R&D activities in the pharmaceutical industry in India
Figure D 18: Country wise comparison of citable research papers published in the category drug discovery
Figure D 19: Country wise citation impact of citable research publications (measured by h-index) in the category drug discovery
Figure D 20: BoT of API products (in USD million), 1994-2014
Figure D 21: Map of India
Figure D 22: R&D intensity in percent (R&D expenditures divided by total sales) of domestic pharmaceutical companies, 1995-2010
Figure D 23: The R&D process stages of pharmaceuticals and their activities involved
Figure D 24: Number of collaborative R&D projects (2010-20105; n=23)
Figure D 25: Evaluation of increazing labor costs, fluctuation of employees (job hopping), and concerns regarding losing internal knowledge for R&D activities in the pharmaceutical industry in India (n=23)
Figure D 26: Prime motives for R&D collaboration, category policy/others (n=22)
Figure D 27: Prime motives for R&D collaboration, category efficiency (enhance flexibility and realize economies of scale and scope, n=22, economies of time and reduce costs, share risks, n=23)
Figure D 28: Prime motives for R&D collaboration, category positioning (n=22)
Figure D 29: Prime motives for R&D collaboration, category resources and capabilities (n=22)
Figure D 30: Invention stage of case collaboration project (n=8)
Figure D 31: The Open Source Drug Discovery platform – a collaborative innovation platform
Table B 1: List of interviewed firms
Table B 2: List of industry experts
Table D 1: Product and process innovation
Table D 2: The major segments of the pharmaceutical industry
Table D 3: Comparison of different research designs: qualitative, quantitative and mixed methods research
Table D 4: The three key processes in the open innovation approach
Table D 5: List of GLP certified test facilities in the national GLP programme
Table D 6: The Novartis AG vs Union of India and Others dispute
Table D 7: NMEs invented between 1995 and 2005
Table D 8: Patent applications from Indian organizations between 1995 and 2005
Table D 9: Geographical distribution of pharmaceutical manufacturing units in India in 2012
Table D 10: The top 15 pharmaceutical companies in the retail market in India, 2015, figures are rounded off to the next whole number and converted based on historical exchange rate as of March 31, 2015
Table D 11: Sources of innovation information (n=8)
Table D 12: Motives for collaboration in R&D
Table D 13: Contribution of early stage R&D collaboration to success levels (n=6)
Table D 14: Problems in early stage R&D collaboration projects between in-house R&D cooperation unit and external partners (n=15)
Table D 15: Target Product Profile for developing VL NCEs
Table D 16: Compounds of Indian companies at different stages of development
Table E 1 Category: Strategy and Management
Table E 2: Category: Management of Technology and Innovation
Table E 3: Category: Business, Management and Accounting
Table E 4: Category: Business and International Management
Table E 5: Category: Pharmaceutical Science
Table E 6: Category: Pharmacology
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The Indian pharmaceutical industry is the country’s leading science-based industry with wide ranging capabilities in the complex field of drug technology and manufacturing. Expanding at a compound annual growth rate of 23.9 per cent, the Indian pharmaceuticals market is anticipated to reach USD 55 billion by 2020. Among the pharmerging markets, it is highly ranked in terms of quality and the extensive range of manufactured drugs. India signed the Agreement on Trade Related Intellectual Property Rights in 1995. This agreement aimed at harmonizing intellectual property rights and patent protection worldwide. India's decision to sign was disputed since civil society campaigners believed it would prevent access to low cost drugs and many Indian generics drug firms susptected to lose their right to reverse-engineer products, which were patent-protected abroad. Most small-scale generics firms remained resistant, while the majority of large-scale firms welcomed the possibility of entering higher-income markets, fuelled by their visions of becoming innovators themselves (S. E. Smith, 2000). Signing the Agreement on Trade Related Intellectual Property Rights necessitated amendments to the Patents Act, 1970. This Act had previously offered Indian firms equivalent protection to that of their foreign counterparts, encouraging them to produce new chemical entities instead of generic drugs (Schüren, 2013). The new institutional framework has resulted in a search for novel drugs and new markets, leading to an increase in collaborations on research and development. This paper investigates whether, and to what extent, external sourcing activities and R&D collaborations between Indian pharmaceutical firms and their partners in the sectoral innovation system constitute a viable option for them to upgrade into the development of new, enhanced drugs . This was achieved through conducting an analysis of the pharmaceutical industry‘s sector innovation system and R&D collaboration modes between Indian pharmaceutical firms and their external partners.
Analysis of the active pharmaceutical ingredient sector’s innovation system in India has shown that partnerships exist mainly within the industry, and not between firms, the academia and the public sector. Industry-academia collaborations are especially lacking within pharmaceuticals, although scientific journals published by universities represent one of the most important source of innovation for the private sector. Most of the firms engaged in general and early stage R&D collaboration projects in order to improve their time and cost efficiencies, as well as to expand their market coverage in order to stay competitive and remain active in the MNC’s global development and production network. Indian firms still depend on their expertise in reverse engineering, gained under the old institutional framework, which incentivized the industry to produce process patents. The Patents Act, 2005, which introduced product patents, has not led to a change in incentives. On the contrary, the strict patent specifications have led to a decrease in the approval of product patents in India.
Analysis of the inter-organizational research and development collaboration modes revealed that some of the issues, which decreased efficiency in cooperation, included cultural differences between private and public entities, as well as a prevailing lack of trust between firms. Out of the modes analyzed, public-private partnerships proved themselves most successful in leveraging synergies for the generation and diffusion of knowledge. The success of these partnerships relies on the ability and motivation of the participants to openly share their knowledge and bring the product to the market. However, the benefits are not guaranteed, and there were also collaboration projects where foreigness proved to be aliability which reduced or compensated the synergies. Based on the assumption that exchanges of internal and external knowledge have a positive impact on the generation of ideas and learning, the liability of foreigness is mainly rooted in the preconditions to share knowledge. Indian firms face a lack of organizational flexibility to coordinate R&D projects as well as a well-functioning bureaucratic structure on the corporate and the public sector levels, which impede the ability of Indian firms to share knowledge. Similarly, Indian firms face deficiencies in motivation within their own businesses, as well as on the side of their partners, to engage in reciprocal learning processes, an issue which is mainly rooted in a deficit of trust on the part of the external partners.
Various policy analysts and researchers have studied sectoral innovation systems (SIS) empirically (Bergek, Jacobsson, Carlsson, Lindmark, & Rickne, 2005; Breschi & Malerba, 1997; Malerba, 2002; Mani, 2009). Within these studies, efforts have been made to comprehend the structure and dynamics of different innovation systems (IS). This thesis aims to capture the SIS forces of the Indian pharmaceutical industry (IPI). More specifically, it focuses on the active pharmaceutical (API)1 sector in terms of its structural components and functionality in diffusing drug innovations.
The IPI has evolved as one of the largest and most developed under the emerging pharmaceutical markets. The revenues of the research-intensive industry grew from USD 36.5 million in 1980 to USD 20 billion in 2015, transferring the industry to the third largest in terms of volume. In 2019, the industry is forecasted to reveal a volume of USD 33.4 billion (Bhadoria, Bhajanka, Chakraborty, & Mitra, 2010; IBEF, 2015a; Sahu, 2014). India’s reversal point in economic history was the opening and liberalization of its economy, which lead to a transfer of foreign technologies to the IPI in the 1990s (Sudip Chaudhuri, 2005b). The country developed from a high-risk area dependent on the re-engineering and launching of multinational companies‘ (MNCs) products as generic competitors on the domestic market by local firms to an attractive location for research and development (R&D) activities and collaboration (Haakonsson, Ørberg Jensen, & Mudambi, 2013).
According to Herstad, Bloch, Ebersberger, and van de Velde (2008), R&D and innovation increasingly takes place in open innovation systems, in which internal corporate R&D is supplemented by external knowledge sourcing. Some of the SIS’ key components include the role of private sector pharmaceutical industry investments in R&D, as well as an understanding of its dimensions, which influence this process. While firms2 engage in many forms of innovation, the most critical is the discovery and development of new chemical and molecular entities (NCEs and NMEs) that evolve into new therapies (DiMasi, Hansen, & Grabowski, 2003). R&D collaboration strategies with external actors in the SIS are viewed as leveraging knowledge sharing and facilitating flows of information, encouraging firms to develop new, enhanced drugs (Bianchi, Cavaliere, Chiaroni, Frattini, & Chiesa, 2011; Chesbrough, 2003b; Dahlander & Gann, 2010; Fey & Birkinshaw, 2005; West & Bogers, 2011). Inter-, and intra-organizational collaboration projects, comparatively to equity investments and joint ventures, offer the partners a higher level of flexibility (Hagedoorn, 2002). Particularly, collaborative reserach projects (CRPs) or public private partnerships (PPPs) allow firms to source and integrate external skills and knowledge in order to attain radical innovation, minimize R&D costs and risks, and enter into new markets (Dunning & Narula, 1996; Noteboom, 2000; Powell, Koputh, & Smith-Doerr, 1996; Zahra, Ireland, & Hitt, 2000).
Based on the IPI’s importance to the global pharmaceutical R&D and production network, and the resulting opportunities for the development of the Indian API sector, this thesis aims to discover what the dynamics of this Indian SIS are and how they facilitate the innovative performance of the API sector with respect to the development of new, enhanced drugs. Specifically, this thesis seeks to answer whether engagement in R&D collaborations displays a feasible opportunity for Indian firms to enhance their capabilities and incorporate new knowledge and technologies, or whether they are exploited by their partners.
The following sections demonstrate the thesis objective, research gaps and research question (section 1.2.). Section 1.3 discusses definitions and concepts, and section 1.4. introduces the delimitations. Finally, the thesis itself is outlined in section 1.5.
In order to capture the questions presented in section 1.1., the thesis’ overaching empirical objective is to analyze whether and to what extent external sourcing activities and R&D collaboration between pharmaceutical firms and between them and their partners in the respective SIS in India constitute a viable option for the firms to upgrade toward the development of new, enhanced drugs.
Recent strands of research that examine this development in detail are the SIS approach and open innovation processes. Organizations influence different forms of external collaborations that underpin and shape interactive learning and idea generation. A range of scholars have influenced the understanding of different forms of IS, based on their units of analysis and research focus (Carlsson, Jacobsson, Holmén, & Rickne, 2002; Edquist, 1997, 2006; Edquist & Johnson, 1997), which include national innovation systems (NIS) (Carlsson & Stankiewicz, 1991; Freeman, 1988, 1995; Galli & Teubal, 1997; Lundvall, 1992, 2007; Nelson, 1993; OECD, 1997, 2002), regional innovation systems (RIS) (Carlsson et al., 2002; Philip Cooke, Uranga, & Etxebarria, 1997; Saxenian, 1994), and technological innovation systems (TIS) (Bergek, 2002; Bergek, Jacobsson, Carlsson, Lindmark, & Rickne, 2008; Carlsson, 1997; Carlsson & Stankiewicz, 1991; Hekkert, Suurs, Negro, Kuhlmann, & Smits, 2007; Malerba & Orsenigo, 1993). While these systems propose either a geographically- or technologically-oriented IS, an SIS highlights the benefits of industrial relationships for a nation’s economic growth (Bergek et al., 2005; Breschi & Malerba, 1997; Malerba, 2002). Mani (2009) analyzed the shapes and dynamics of the IPI’s SIS. This has cased the theoretical IS approach to become increasingly popular, becoming widespread within different areas of research.
Another increasing theoretical line of research, which is connected to the SIS of the IPI, is directed toward the analysis of firms‘ innovation performance. Scholars have analyzed and conceptualized the development of R&D capabilities and learning within Indian pharmaceutical firms (Chaturvedi & Chataway, 2006; Kale & Little, 2007; S. E. Smith, 2000)3, as well as the impact of the Agreement on Trade-Related Intellectual Property Rights (TRIPs) on pharmaceutical product and process innovations in India (Sudip Chaudhuri, 2005b; Horner, 2014b; Mehta, 2012; Rai, 2008; Schüren, 2013), the evolution of India’s expertise in generics and contract research manufacturing, and its implications for India’s knowledge base (Greene, 2007; Sariola, Ravindran, Kumar, & Jeffrey, 2015; Waning, Diedrichsen, & Moon, 2010). They have also analyzed the pharmaceutical global value chain and production network, considering their implications towards India’s integration into the global economy (Haakonsson, 2009a, 2009b; Haakonsson et al., 2013; Horner, 2014a).
In the studies referenced, the external information sourcing for improving innovation activities is viewed to be an important, yet under-explored, issue for the generation of innovative pharmaceuticals in Indian firms. This thesis thereby adopts an open innovation perspective and primarily investigates the benefits of collaboration to external partners in the drug development process of APIs. From the firm‘s perspective, the different forms of collaboration and knowledge sourcing that underpin the generation of ideas throughout the early stages of drug development are thought to contribute valuable insights into the benefits and challenges of global participation in the SIS.
Therefore, the following research questions have been formulated to accomplish the objective of the thesis:
1. How are the interdependencies between Indian pharmaceutical firms as well as between them and their external partners in the SIS, influencing the R&D activities for the development of APIs?
2. How, and to what extent, do Indian pharmaceutical firms engage in R&D collaboration in order to overcome possible constraints displayed by the SIS?
Theoretically, this contribution should advance emerging views of different forms of external knowledge sourcing and collaboration as upgrading the technological and scientific skills of Indian firms. Practically, it serves to channel the awareness of the people involved in inter-organisational R&D collaboration projects to the conducive factors. In this manner, it focuses primarily on the particularities of Indian firms.
The potential for improved innovation through a combination of internal and external knowledge sourcing is an important principle in open innovation processes (Chesbrough, 2003a, 2012a; Chesbrough & Bogers, 2014; Phil Cooke, 2005; Dahlander & Gann, 2010; Gassmann & Enkel, 2006; von Hippel, 2005).Chesbrough was a pioneer in conceptualizing open innovation, defining the term as “the purposive use of the inflows and outflows of knowledge” (Chesbrough, 2003a, p. 52). In the following years, the concept was further refined and in 2014, the author proposed the application of a slightly different definition: “open innovation ought to be conceptualized as a distributed innovation process that involves purposively managed knowledge flows across the organizational boundary“ (Chesbrough & Bogers, 2014, p. 3). However, congruently with this view, other definitions of open innovation have emerged.West, Vanhaverbeke and Chesbrough (2006, p. 286) , for instance, all describe open innovation as “both a set of practices for profiting from innovation and a cognitive model for creating, interpreting and researching those practices”.
Furthermore, this thesis examines cooperation between partners in the SIS of the pharmaceutical industry’s API sector. The definition of the system in the SIS approach is based on the sector or industry, and the approach focuses on a group of firms that develop, produce and sell products through market and non-market interaction (Breschi & Malerba, 1997). The pharmaceutical industry is responsible for the development, manufacture and marketing of drugs, medications, pesticides, etc., for both human and veterinary use. The pharmaceutical industry is committed to R&D in pharmacology and therapeutics, seeking new remedies and improved modifications to existing drugs against human and animal diseases (Last, 2007). The thesis’ focus on the API sector will be further refined in section 1.4. Together, the group of firms, whose interactions are influenced by institutional rules and regulations, generate and utilize certain degrees of technological knowledge in that sector by interacting through communication, exchange, co-operation, competition and command (Edquist, 2006; Malerba, 2002). The SIS can be distinguished from other IS approaches, as elaborated on in section 3.1.
The collaboration partners within the SIS represent its components. They can include firms, public or private research organizations, governmental or non-governmental organizations, suppliers, customers, as well as competitors, institutions or networks (section 3.1.). The differences among the people who form a team, department, or organization, foster diversity (Jackson, May, & Whitney, 1995) . Group or team diversity is viewed both as a potential resource and impediment to innovation and learning (Gibson & Gibbs, 2006; Jehn, Northcraft, & Neale, 1999; van Knippenberg, De Dreu, & Homan, 2004) .
This thesis concentrates primarily on collaborations in R&D activities. According to the OECD (2003), R&D is defined as “any creative systematic activity undertaken in order to increase the stock of knowledge […]. It includes fundamental research, applied research in such fields as agriculture, medicine, industrial chemistry, and experimental development work leading to new devices, products or processes.” The pharmaceutical product development process can be divided into several steps, which will be illustrated in chapter 3.
R&D activities are typically geared towards generating innovative ideas. There is no unified definition of innovation (Trott, 2012). However, many scholars base their definition on Schumpeter’s, who defined the concept “by means of the production function [...] this function describes the way in which quantity of product varies if quantities of factors vary. If, instead of factor-quantities, we vary the form of the function, we have an innovation” (Schumpeter, 1939, p. 84). Nelson and Rosenberg were the first to introduce technology and its diffusion to the concept of innovation. According to them, innovation is “the processes by which firms master and get into practice product designs and manufacturing processes that are new to them, if not to the universe or even to the nation” (Nelson & Rosenberg, 1993, p. 4). The OECD defines innovation as “the implementation of a new or significantly improved product (good or service), or process, a new marketing method, or a new organisational method in business practices, workplace organisation or external relations” (OECD & Eurostat, 2005, p. 46). Thus, analysts take different points of view when defining the term innovation. However, all of them seem to agree that innovation inherits technological, organizational and institutional change, and that innovation is the successful renewal of a certain domain through the adoption of new processes and the introduction of new technologies (cf. Kline & Rosenberg, 1986).
Moreover, innovation is targeted either towards products or processes (Table D 1). “Product innovations are new, or better, material goods as well as new intangible services. […] Process innovations are new ways of producing goods and services. They may be technological or organizational” (Edquist, 2006, p. 183).
This thesis takes these characteristics into account and focuses on the distinct needs and challenges of firms in India during their interaction with external partners for the purpose of generating drug innovations.
In order to narrow down the research question, this thesis adopts a firm-perspective, analyzing the collaborations within Indian firms, as well as between them and other actors, in the relevant SIS. Hence, it can be questioned whether the mixed method research approach, containing an online survey with open and closed questions, is complete with respect to the data, which is derived from all possible firm-partners. Moreover, as pharmaceutical MNCs have a central multifaceted role in the globalization of the product innovation process, the SIS is beneficial toward these industry actors. This shifted the focus away from the identification of the other actors, such as public and governmental agencies, research institutes, suppliers and customers. However, this delimitation was necessary due to the limited amount of time available to conduct the thesis’ research, and the major role of MNCs in the global generation of pharmaceuticals.
Secondly, the thesis concentrates on the study of product innovations. As mentioned in section 1.3., product innovation involves the development of new goods and services. With regard to pharmaceuticals, product innovations require the discovery and development of NCEs, which often require new chemical processes. Therefore, it is often difficult to distinguish between process and product innovations in this scientific field, as exemplified by the explanation of the terms NCEs and novel drug delivery systems (NDDS) (p. 18).
Thirdly, there are various quality dimensions of pharmaceutical products involving concerns over efficacy, safety and convenience. Innovations in pharmaceuticals can lead to enhancements of existing products, or new treatment options, new NCEs, NMEs, or active pharmaceutical ingredients (APIs). APIs are active chemical molecules, which have an effect on the target (Blau et al., 2004; BPI, 2016). The application of generic versions of previously approved innovator drugs usually has to prove the bioequivalence of the product and does not need to exhibit pre-clinical or clinical data to establish safety and efficacy (Blau, Pekny, Varma, & Bunch, 2004; BPI, 2016; USFDA, 2016a)4. Due to the fact that the development of products based on new APIs is typically more research intensive than the development of generics (Haakonsson, 2009b; Scherer, 2010), the focus of analysis in this thesis will be on the former. In order to outline this delimitation, the following table illustrates the different product sectors of the pharmaceutical industry. The product in focus, the API –or NCE/NME- has been framed.
Finally, the thesis is delimited to the analysis of the early stage development process of APIs, in which ideas for product innovation are generated (Hansen & Birkinshaw, 2007) . The early stage process comprises the discovery stage, the initial target identification and validation, lead optimization and the selection of a candidate molecule for clinical development (J. P. Hughes, Rees, Kalindjian, & Philpott, 2011).
Chapter 2 presents the methodology used in the thesis. In chapter 3, the theory for the analysis of the SIS of the API sector and inter-organizational R&D collaborations will be presented and discussed. The research context presented in chapter 4 provides the reader with the essential historical information needed to understand the research problem and its significance. Chapter 5 focuses on the empirical findings of the SIS analysis. Chapter 6 looks deeper into the empirical findings regarding external R&D collaborations firms engaged in the development of new drugs. Chapter 7 ends with a conclusion and the contribution of the thesis, as well as giving suggestions for further research.
In this chapter, the method for the research undertaken is presented. This includes the analytical framework and the philosophical and theoretical assumptions upon which the methodogical approach is based.
The thesis’ framework of analysis is based on the SIS approach, first introduced by Malerba (2004). The framework consists of three aspects: (i) knowledge and a technological domain, (ii) actors and their relationships, (iii) institutions. The development and diffusion of knowledge is crucial for innovation. As the key actors, firms have to absorb this knowledge through their competencies, which evolve over time. Other actors may be comprised of customers, competitors, or suppliers, all of whom have various relationships with the firms. Yet other actors include universities, government agencies, and industry associations, which facilitate the innovation and technological diffusion achieved by firms. Institutions greatly affect the rate of technological change, as well as the innovative activity and performance of a firm (Malerba, 2002, 2004; Malerba & Mani, 2009). Chapter 5 will consider how these three aspects have affected the innovative performance of the SIS of the Indian API sector during the last few decades.
The SIS approach is supplemented by the innovation value chain and open innovation framework presented by Chesbrough (2003) and Hansen and Birkinshaw (2007). These concepts allow for an analysis of external R&D collaborations’ impact on firm’s capabilities to develop new, enhanced drugs. The innovation value chain displays innovation as a sequential process, which involves the generation of ideas and the development, and diffusion of, new products. In chapter 6, the external sourcing dimension in the early idea generation stage of the new drug R&D process will be analyzed from a firm perspective.
The next sections will present the methodological approach used in this thesis, including the research philosophy, perspective and strategy.
In this thesis, the research philosophy is characterized by interpretivism, which represents a foundation for qualitative methodology approaches. “Interpretive researchers assume that access to reality (given or socially constructed) is only through social constructions such as language, consciousness, shared meanings, and instruments“ (Meyers, 2009, p. 38). Instead of predefining dependent and independent variables, interpretive researchers focus on the meaning in the context of a phenomenon, since the context represents the socially constructed reality of the studied individuals (Boland, 1991; Meyers, 2009; Orlikowski & Baroudi, 1991)5.
Interpretivism has been critized for leaving room for the researcher’s bias. The interviewee attributes a certain meaning to the questions asked and responds based on their subjective interpretations. Thus, generalizing primary data from interpretivist analysis is difficult, due to the influence of personal viewpoints and values (Bogner, Littig, & Menz, 2009). However, as Cicourel (1964) stated, humans always apply meanings to objects and base their social actions on common-sense rationalities. Consequently, researchers have to take into account the theorem of subjective interpretation.
The research in this thesis contains descriptive, explanatory and exploratory aspects. On one hand, it encompasses an empirical analysis of the components affecting the dynamics of the SIS. On the other hand, it considers the system’s inter-organizational R&D collaborations between firms and their external partners. The first part of the project has a descriptive approach: gathering data to construct an overview of the SIS of the Indian API sector. Section 5.1. covers this descriptive aspect. The approach to the research perspective was retroductive, as it involves a discourse between ideas and evidence and is best suited for inquiries due to its combination of elements from both the deductive and inductive approaches (Downward & Mearman, 2007; Ragin & Amoroso, 2011; Teddlie & Tashakkori, 2003). Figure D 1 illustrates the elements included in the retroductive approach.
The model shows that representations of social life are derived from four blocks, which are comprised of ideas, analytic frames, evidence, and images. These blocks, in turn, are built through three analytic loops. First, an analytic framework is developed deductively from primary ideas and theories. Second, images are derived from empirical evidence through an inductive process. Third, an interpretational phase occurs, where analytic frames and images are considered in relation to one another. Through this reciprocal procedure, the analytical framework can be confirmed or corrected, thereby creating a conclusive picture of social life (Ragin, 1994).
Research strategies can be divided into quantitative, qualitative, and mixed-method research (Table D 3, Appendix) (Johnson, Onwuegbuzie, and Turner 2007; Creswell 2014).
Quantitative research is based on the social science philosophy of positivism and is usually utilized to verify the theory by collecting primary numerical data through closed-ended questions in surveys. It allows statistic evaluations to test hypotheses or make inferences toward an overall population (generalizability). Quantitative studies are typically criticized for their neglect in gathering in-depth data due to the nature of closed-ended questions, as well as because the researcher’s comprehension differs from that of the participants’ in the study. Thus, complex questions or evolving constructs are less suited to be included in the analysis (ibid.).
In contrast, qualitative research is based on the social constructivist perspective, which is useful in investigating concepts or generating theory. This includes the gathering of observational and narrative data. Critical concepts can be discussed with, and explained by, the interviewee, increasing the potential of a mutual unterstanding. Hence, complex research topics are usually addressed via qualitative research designs (Yin, 2014).
The mixed method research strategy is a combination of the quantitative and qualitative research approaches and thus includes the possibility to both explain and explore (Creswell, 2014; DeCuir-Gunby, 2008; Teddlie & Tashakkori, 2003). This research method can be used to both generate and test theories, and is best suited when following a pragmatic perspective in social science research, especially when the aim is to answer complex research questions (Creswell, 2014). By combining quantitative and qualitative strategy approaches, the expectations from the theory can be tested statistically and explained qualitatively (Downward & Mearman, 2007). According to DeCuir-Gunby (2008), the combination of quantitative and qualitative methods results in the most complete and accurate depiction of the social phenomena under investigation.
Different instruments can be used in order to explore quantitative and qualitative data in a mixed method study (Creswell, 2014). Moreover, one commonly distinguishes intra-method from inter-method mixing. Intra-method mixing is defined as the use of a single method that includes both qualitative and quantitative components, e.g. the combination of open- and closed-ended items on a single questionnaire. Inter-method mixing refers to the use of different methods for data collection, such as a broad survey followed up by in-depth interviews (Johnson & Turner, 2003).
In general, primary and secondary data sources are differentiated from each other. Considering both the level of detail presented in the research questions and the central characteristics of the unit of observation – Indian API sector firms – secondary, detailed data are available but insufficient to fully answer the research questions. Thus, direct access to the unit of investigation for the purpose of primary data collection has been sought. Surveys, interviews, focus groups and observations were employed as alternative instruments for data collection (B. Johnson & Turner, 2003). However, the lack of observable innovation activities taking place within a firm inhibited the use of observations. Face-to-face or telephone interviews would have been a good alternative to collect data, particularly for qualitative evaluation. However, the response rate to interviews was very low. Hence, surveys emerged as the method of choice. Due to time restrictions and the geographical distance between the interviewer and the respondents, the questions were sent through e-mail6. One of the advantages of e-mail surveys and interviews is extended access to participants. Furthermore, e-mail surveys and interviews are cheaper than face-to-face or telephone-interviews as there are no associated travel costs. On the other hand, this technique takes a lot of time. Due to the nature of online communication, an interviewee might wait for days or weeks before choosing to answer the questions (Coomber, 1997). This leads to a risk of the interviewee losing interest in the research, or forgetting to reply to the questions (Kivits, 2005). Sending reminders after some time to the interviewee reduced this problem. Four reminders were sent in one to two week intervals following the initial e-mail. According to Bampton and Cowton (2002), the advantage of e-mail surveys and interviews is that they meet the needs of busy interviewees who might prefer to decide when to answer the questions for themselves. A delay in communication also permits the interviewee to construct a response to a particular question. Moreover, an e-mail-interview with both closed- and open-ended questions allows for both quantitative and qualitative data to be considered concurrently (inter-method mixing). Accordingly, a semi-structured interview guideline has been designed that includes open- and closed-ended elements in order to congruently raise numerical data for quantitiative analysis and verbal data for qualitative analysis (Mayring, 2002; Schnell, Hill, & Esser, 2011).
Two different interview guidelines for the surveys were created7. The longer version was targeted at firms who posessed knowledge on the IPI and API sector (Annex A 1.). The short version was targeted toward other industry experts with valuable knowledge (Annex A 2.). The latter version was created after the longer one had been sent out and a low response rate was observed. The longer interview guideline included questions about the characteristics of early stage projects, as this was regarded to be highly important for the analysis of early stage R&D collaborations (chapter 7).
In addition to primary data, the data collection method also consisted of qualitative and quantitative on secondary data. This consisted of information collected from academics on conceptual frameworks and perspectives, statistics from the databases Bloomberg, Orbis, and Money control, articles, and industry- and government reports. Despite the fact that the information from secondary data was originally collected for a different purpose than this thesis, this data often has a high degree of quality and is valuable when carrying out research in a specific field (Saunders, Lewis, & Thornhill, 2007).
The survey guidelines were pre-tested in 10 e-mail interviews in November, 2015 to increase their validity. As a result, some formulations were rewritten, and the survey was shortened. The interviews for the main field phase were conducted over a period of 14 weeks, starting with the first ones in November, 2015, with the last one being conducted in February, 2016. They were conducted by sending e-mails, or through posting links to the surveys on social media platforms. Over this period, the surveys were sent to 283 firms and 316 industry experts from the public sector, which resulted in 9 and 15 answers, respectively. Efforts were made to contact industry experts in order to get additional valuable insights about R&D collaborations for the development of new, enhanced drugs.
The empirical data was obtained from Indian firms, public and private research institutions and associations identified from complementary sources such as the internet, journals, and industry reports. Correspondence was addressed to executive employees, particularly R&D managers. Considering the research topic and the size and structure of the firms, these people were identified as knowledge experts, as they were regarded as the best suited to respond to the questions. All interviewees were granted anonymity by allocating a number between one and 24 to each interview partner (IP). In the following sections, quotes of the IPs are labeled as IPn, with n marking the number. Table B 1. and Table B 2. in the Annex give an overview of the firms and industry experts that participated in the field phase as well as their positions. A descriptive analysis of the firms and the case projects is presented in section 5.1. In order to increase the possibility of receiving consistent and decisive answers, the research design has to emphasize reliability and validity (Saunders et al., 2007).
According to Saunders et al. (2007, p. 149), “reliability refers to the extent to which [...] data collection methods or analysis procedures will yield consistent findings“. This means that other researchers have to be able to reach similar conclusions, or they have to be able to yield the same results with measures obtained on other occasions (Easterby-Smith, Thorpe, & Jackson, 2012). The reliability of this thesis’ research is ensured through the provision of the written answers sent by the respondents, which are included in Appendix C. Moreover, direct quotes from the interviews ensure that the interpretation of the data is correct. While the lack of standardization in semi-structured interviews may be problematic for the reliability of the data, the results of the interviews are not necessarily meant to be reproduced, as they reflect the specificities of the time and situation when the research was originally undertaken. The qualitative and quantitative data gathered through the 24 responses to surveys by representatives of the Indian IPI was combined with statistical data and theory.
“Validity is concerned with whether the findings are about what they appear to be about” (Saunders et al., 2007, p. 150). In semi-structured e-mail interviews and surveys, the interviewees are able to write about the issue in detail. As there is little direction from the interviewer, questioning different interviewees reveals different insights. This increases the level of validity.
This chapter presented the method for the research undertaken in this thesis. This included the analytical framework and philosophical and theoretical assumptions for the methodogical approach. The thesis’ framework of analysis is based on the SIS approach, which has three connotations relevant for the analysis of the Indian API sector. The SIS approach is extended by the innovation value chain and open innovation framework (section 2.1.). These concepts allow for an analysis of the firms’ engagement in R&D collaboration activities with external partners in order to acquire competencies for the development of NCEs.
In this thesis, the research philosophy is characterized by interpretivism, on which the qualitative methodology approaches are based on (section 2.2.1.). The approach to the research perspective was retroductive as it is best suited for inquiries by combining elements from the deductive and inductive methods (section 2.2.3.). Moreover, the mixed method approach as the strategy of research is used as it best addresses the twin task of probing the analytic framework and developing images from empirical data, which verify, disprove or expand the assumptions derived from the conceptual framework (section 2.2.4.).
E-mail surveys emerged as method of data collection. These were complemented with qualitative and quantitative secondary data from databases, market reports and scientific journals. The surveys were conducted over a period of 14 weeks in 2015 and 2016 and displayed a low response rate (section 2.2.). However, the results of the thesis are not meant to be reproduced but to serve as a stepping-stone for a systematic large quantitative survey of the API sector.
In the literature on technology and innovation, the market failure approach8 has almost entirely been rejected due to its insufficiency to justify policy intervention (Edquist, 2001; Malerba, 2002; K. Smith, 2000). The IS approach is viewed as a more suitable framework in order to analyze innovation processes and economic development. This approach has been applied by national governments and international organizations, such as the European Union (EU) and the Organization for Economic Co-operation and Development (OECD) (Edquist, 2006). This chapter starts with a description and evaluation of the theory of the SIS approach in order to legitimize its choice for the analysis of the innovative performance of the Indian API sector. Second, the SIS approach is extended with the innovation value chain framework as it allows for an application of an international dimension to the system. By looking at the early stages of the pharmaceutical R&D process, the innovation value chain enables to analyze changing firm-relationships to other actors in the SIS in order to identify challenges and possibilities for the development of APIs. To further refine the unit of analysis –the external relations between firms and other actors in the SIS- the open innovation concept is applied to the innovation value chain framework as an innovation perspective (Hansen & Birkinshaw, 2007). This extension of the SIS approach serves to accomplish relevant points and requirements that the analytical framework should address and include in order to answer the research questions.
The IS approach has existed since the 1980’s and has been introduced and analyzed in its earliest versions by Freeman (1987), Lundvall (1985, 1992), and Nelson (1993). The idea, however, goes back to Friedrich List’s conception of the The National System of Political Economy (List, 1841), which Freeman renamed to The National System of Innovation in his study on the success of the Japanese economy (Freeman, 1988). Since the 2000’s the approach has been analyzed in several academic contexts (Edquist et al., 2001). The IS approach is an analytical tool to capture the complex, interactive aspects of innovation processes between components in both formal and informal institutional setups (Bergek et al., 2008; Borrás, 2008; Carlsson et al., 2002). IS can either be defined in spatial terms, i.e. as NIS (Freeman, 1988; Galli & Teubal, 1997; List, 1841; Lundvall, 1992; Nelson, 1993; OECD, 1997; Patel & Pavitt, 1994), RIS (Asheim & Isaksen, 2002; Philip Cooke et al., 1997; Malerba, 1993), SIS (Bergek et al., 2005; Breschi & Malerba, 1997; Malerba, 2002; Malerba & Mani, 2009), and as TIS, which focus on the development, diffusion and use of a particular technology (Carlsson, 1997; Carlsson & Stankiewicz, 1991; Hekkert et al., 2007; T. P. Hughes, 2012; Rickne, 2000). The concepts differ in terms of the characteristics of their components and their interrelations (Hekkert et al., 2007)9.
In this thesis, the SIS approach is used for the analysis of the components of the Indian API sector, i.e. socio-economic systems, which focus on the structure, organizations, and dynamics of production and innovation in sectors (cf. section 1.3.). Malerba and Mani (2009, p. 5) define a sector as “a set of activities that are unified by some linked product groups for a given or emerging demand and that share some common knowledge”. This system consists of the following components and interrelations: (i) firms in the sector, (ii) other actors besides these firms, (iii) institutions, (iv) networks, (v) demand, (vi) processes of interaction (functions and activities), and (vii) the knowledge base.
In a SIS, firms are the central actors in innovation and production. They are characterized by their capabilities to acquire knowledge, learn, and to develop organizational structures, goals, and expectations (van Lente, 1993). A SIS is also composed of other actors, which can be organizations or individuals. Organizations mainly represent public or governmental agencies, industry organizations, trade unions, universities, or other research institutions. Individuals can be consumers, entrepreneurs or scientists (Carlsson & Stankiewicz, 1991). The relationships between actors are shaped by institutions. According to Borrás (2008), institutions are either formal or informal. Formal institutions represent formulated rules, while informal institutions can be norms, traditions, or routines that influence the structures within the boundaries of a system (North, 1990). All SIS have in common that institutions play a key role in affecting the degree of technological change, innovative activities, and performance. The relationship between the SIS and national institutions is essential as these institutions may constrain or provide an environment, which is more suitable for specific types of sectors in contrast to others (Malerba & Mani, 2009). Networks between the operating actors of the SIS can either be formal or informal market or non-market relationships (Carlsson et al., 2002). Some formal networks might relate to a specific task and can be classified (e.g. technology platform consortia, PPPs, or standardized customer-supplier relationships). Other formal networks develop in a less standardized form, such as industry-academia relationships. Informal networks can only be identified through a discussion with actors or an analysis of collaboration. They are often established through professional conferences, meetings, or publications (Bergek et al., 2008). In the pharmaceutical industry, relationships between firms and non-firm organizations, such as public research centres and universities, have been a source of innovation and change (Nelson & Rosenberg, 1993). According to Malerba and Mani (2009), the relationship structures and networks vary between sectoral systems as a result of different knowledge bases, learning processes, fundamental technologies, and demand. In a SIS, demand can either be domestical or international. It is shaped by heterogenous actors, who have certain relationships to customers, rather than driven by a set of similar buyers or customers. Hence, demand is shaped by different individual customers, firms and public organizations, which can be part of different countries and national IS (ibid.). As noted previously, the main function of a SIS, is to develop, diffuse, and utilize innovation (Edquist, 2006). The flow of knowledge, information and technology between the components of a system is a key function to innovation processes in any IS (OECD, 1997). The collaboration with external knowledge sources, which complement a firm’s own knowledge base (Nonaka, 1994), impact the function knowledge development and diffusion (Cohen & Levinthal, 1990). Kowledge creation and sharing has an important role within an organization’s R&D development, innovation and invention. This is further elaborated on in section 3.5. Figure D 2 illustrates the dimensions of the SIS.
The IS approach has been diffused and evolved into an essential framework for analyzing innovation within systems (Edquist, 2006). In this thesis, the SIS approach has been selected for the analysis of the API sector of the IPI in India. However, with the beginning of the 21st century, the rapid economic globalization has been considered as challenging the argumentation that spatially or technologically confined systems are conducive for innovation policies. Firms increasingly seek, and are forced to seek, ideas, knowledge, and new markets for their technologies abroad (Lichtenthaler & Ernst, 2007). This applies particularly for highly specialized knowledge bases, products and processes, which are becoming increasingly synthetic, based on inputs and the recombination of diverse disciplines and expertise in flexible organizations (Lam, 2000). Innovation in particularly dynamic industries, such as the pharmaceutical industry, therefore often requires that the firm opens up beyond its own organizational boundaries, and beyond the boundaries of its proximate value chain transaction partners (Noteboom, 2000). This means that a SIS needs to unfold as knowledge flows are created between actors and firms or industries with different levels of R&D intensity and knowledge bases (Herstad et al., 2008). Taking this into consideration and in the light of this thesis’ objective, the SIS approach is extended by the innovation value chain and open innovation concepts.
Against the background of the internationalization of knowledge and R&D activities during the last decades, the world’s interconnectedness has increased and its dynamics have changed dramatically (Kim et al., 2012). Organizations have to optimize their innovation process in order to maintain and gain competitive strategic advantages (Filippini, Güttel, & Nosella, 2012).
The innovation value chain concept, developed by Hansen and Birkinshaw (2007), presents a comprehensive framework, which facilitates companies to consider their existing processs for creating innovations, address unique challenges, and develop ways to approach them. The concept is based on findings of five large research projects, including more than 4130 interviews, which the authors conducted between 1997 and 2007. The concept presents innovation as a continuous, three-phase process, which encompasses idea generation, idea development, and the diffusion of developed ideas. Across these phases, managers have to undertake six essential tasks, which at the same time represent links of the innovation value chain: internal sourcing, cross-unit sourcing, external sourcing, selection, development, and companywide spread of the idea (Figure D 3).
The R&D process of pharmaceutical products represents a sequential flow of activities involved in the development and commercialization of a new drug. Developing a new drug from the idea to the launch of a finished product is a complex process which can take 12–15 years and costs approximately USD 1 billion (J. P. Hughes et al., 2011). The early drug development stages 10, which will be the unit of analysis in this thesis, comprise the discovery, target identification and validation, and lead promotion and optimization phases (Bianchi et al., 2011; Blau et al., 2004; Hughes et al., 2011). The first stage, the discovery of a new, active molecule, which has an effect on the target, includes fundamental research and the search for new technological possibilities. Once an active molecule is discovered, the target identification and validation phase is entered. It involves the testing of various molecule structure permutations in order to improve different properties that promise a molecule, which is successful as a drug. After that, the best molecule from these structure-activity relationships is tested for toxicological results in whole-body systems (Blau et al., 2004). If no particularly toxic effects are observed, the molecule is promoted to the status of lead molecule and it becomes a candidate for development (lead identification and optimization phase). The objective of this final drug discovery phase is to eliminate deficiencies in the lead structure while maintaining favorable properties in the lead compounds. All three phases of the early drug discovery process require collaboration with other partners, either inside the unit, across the company’s units or through the sourcing of external knowledge (Figure D 3, box idea generation) (Hughes et al., 2011). Therefore, they represent the idea generation phase of the innovation value chain proposed by Bianchi et al. (2011) and Hansen and Birkinshaw (2007).
After the early drug discovery activities, the pharmacutical compounds are further developed, tested, and validated in the following four development stages first human dose (FHD) preparation phase or pre-clinical trial phase, phase I, phase II, and phase III clinical trials. First, the FHD stage involves the preparation for administration to healthy volunteers. It includes various pharmacokinetic studies as well as research about adsorption, distribution, metabolism, and excretion from the body and adequate dose levels. It follows the phase I clinical trial phase, which includes the first clinical trials, in which the drug is administered to healthy human volunteers. At the same time, chronic and reproductive studies in mice and rats are conducted. Positive results signify acceptable absorption, distribution, or elimination patterns. Third, in the phase II clinical trial phase, the compound is administered to human patients, who have the disease, by using the results of the dosing analysis from phase I. Simultaneously, long-term oncogenic toxicological studies in animals are conducted as well as market research to get sales estimates. The last clinical trial phase III involves large-scale clinical studies on humans with the disease. The results should confirm the results from phase II. Once unacceptable behaviour in human or animal studies is observed in these four phases, if the compound fails to treat the disease or is inferior to competitive products, it is returned to the discovery phase for revision (Blau et al., 2004). As the pharmaceutical compounds in these four phases are screened and further developed, they correspond to the idea conversion phase of the innovation value chain.
The last stages of the drug development process include the submission and approval and market launch. The market launch stage involves the launch of a promotional campaign and the new drug in various markets over a period of years until market sales are realized. This phase can only be entered if the new drug has been approved by the US Food and Drug Administration (USFDA) during the submission and approval stage. At the launch period studies are conducted to measure the drug's effect in various populations and any side effects connected with long-term use (U.S. National Library of Medicine, 2008). The launch phase ends when mature sales decline after the patent has expired or competition leads to decreased margins (Blau et al., 2004). These two activities go hand in hand with the creation of a breeding ground inside the company in order to support, and launch the new product across locations, customers, and channels (idea diffusion of the innovation value chain) (Figure D 3).
As the objective of this thesis is to examine the external relationships between Indian firms and other actors in the SIS, which might leverage the firms toward the generation of knowledge for the production of new APIs, the focus of analysis will be placed on the blue framed activity of the innovation value chain, the early drug development R&D processes of APIs. Even though the combination and synthesis of all activities of the innovation value chain lead to an improved innovation performance, the idea generation stage plays a key role in the drug development process (Sudip Chaudhuri, 2015; Mani, 2009). Within novelty generation, the sourcing of external information is viewed as crucial for drug related R&D management (Bianchi et al., 2011; Hansen & Birkinshaw, 2007). The Indian SIS of the API sector, and of the pharmaceutical industry in general, relies on its openness, which implies interconnectedness to other systems, such as the biopharmaceutical and biotechnological IS, relationships to actors within and across national boundaries, and knowledge flows across the IS on the national and international level (Gassmann & Reepmeyer, 2005). Hence, the thesis particularly focuses on the external sourcing for idea generation as an innovation perspective within the innovation value chain framework (Figure D 3, box idea generation). The open innovation concept, framed by Chesbrough (2003), offers a suitable theoretical rationale for the analysis of such external relations between organizations.
The open innovation concept is based on the fact that organizations increased their external innovation sourcing activities in response to economic globalization. During most parts of the 20th century, MNCs mainly carried out closed innovation activities in-house due to costly and extensive R&D and heavy intellectual property (IP) protection. With the shift in the economic development paradigm, the increase in availability of skilled labour and solid infrastructural conditions in emerging markets, the preconditions for the sourcing of R&D activities changed and with it the dynamics of innovation (Haakonsson et al., 2013). The phenomenon of open innovation for new ideas emerged and complemented the traditional closed innovation model, in which innovation activities lead to internally developed products and services (Chesbrough, 2012a, Brunswicker and Hutschek, 2010).
Three key collaboration and co-operation activities have been identified in the open innovation concept. Outside-in (or inbound) activities encompass the integration of external knowledge. They enrich the company’s internal knowledge with external knowledge from partners, customers and suppliers and involve an active transfer of technologies from these external sources. Inside-out (or outbound) activities comprise the external commercialization of internal innovations through licensing out or selling of internal knowledge. The third main open innovation activity is the coupled-process, which combines outside-in and inside-out activities in order to co-develop, for example, strategic alliances or joint ventures (Gassmann & Enkel, 2004, 2006). For examples of the three open innovation modes, see Table D 4 in the Appendix.
Yet in the last decades, companies have started to link external knowledge and ideas to internal ones in order to benefit from higher levels of innovation (Brunswicker & Hutschek, 2010; Dahlander & Gann, 2010; Lichtenthaler, 2011). By utilizing the three open innovation activities, a company is able to increase revenue through leveraging on external R&D resources (Chesbrough, 2012b). Therefore, open innovation strategies at the industry sector level can be considered as endeavour to linking up with the SIS at the economy level (cf. Herstad et al., 2008).
Throughout this chapter, it has been emphasized that learning and knowledge sharing is a key activity inherent in R&D collaborations targeted toward idea generation. Consequently, this section addresses the term knowledge sharing and the conditions the partners have to fulfill in order to benefit from this mutual recognition.
As described the previous section, innovations are primarily based on the access to different sources of knowledge and capabilities. Davenport and Prusak (1998, p. 5) define knowledge as „[...] a fluid mix of framed experience, values, contextual information, and expert insight that provides a framework for evaluating and incorporating new experiences and information. It originates and is applied in the mind of knowers. In organizations, it often becomes embedded not only in documents and repositories but also in organizational routines, processes, practices, and norms.“ It becomes clear from this definition that knowledge is linked to personal perception of the truth and known. Knowledge sharing contributes to beneficial organizational results, for instance new product development and to competitive advantages for the firm (Hansen, 1999; Kogut & Zander, 1996). As knowledge sharing provides access to resources and capabilities, which may otherwise be unaccessible, it is an essential process within interfirm R&D collaborations (Bogers, 2011).
There is an ample literature about the conditions and challenges of knowledge sharing11. Two preconditions for the sharing of knowledge, ability and motivation, are essential for its success (Ardichvili, Page, & Wentling, 2003; Lin, 2007). The ability to share knowledge requires a cognitive preparedness of the individual partners (Cohen & Levinthal, 1990; Martin & Salomon, 2003; Minbaeva & Michailova, 2003). Motivation entails the commitment of both partners to share knowledge with each other. While the ability can be characterized as the cognitive foundation to share knowledge, the motivation involves a more active and questing state of mind. One dimension, which influences the motivation to a large extent, is trust (Hsu & Lin, 2008). Trust has been defined as “the mutual confidence that no party to an exchange will exploit anothers’ vulnerabilities” (Barney & Hansen, 1994, p. 176). Thus, trust originates from a certain risk associated to collaborations between two organizations. It is argued that trust facilitates commitment on both sides and convinces the parts to share their knowledge, which in turn promotes learning, and the development and dissemination of knowledge, especially in highly uncertain conditions (Johanson & Vahlne, 2009; Nielsen, 2007).
In contrast to the static neo-classical economic growth theory, the IS approach is able to explain the dynamics of innovations within a system. Correspondingly, the SIS approach displays a suitable theorem for the analysis of the components of the Indian API sector (section 3.1 and 3.2.). Section 3.3. showed that the approach recognizes learning and knowledge exchange as a central part of SIS, focuses on interdependence between the system’s components, encompasses product innovations, and adopts a holistic perspective by opening up to a wide range of disciplines.
To provide a framework for the analysis of interactions between firms and other actors in the SIS in order to facilitate early drug innovation, the SIS approach was extended by the concept of the innovation value chain and open innovation (section 3.4.). The concepts place the pharmaceutical SIS in a global perspective and emphasize the importance of creating external networks for generating ideas at the early drug development stage.
Section 3.5. explored the processes behind the sharing of knowledge, which is essential for the generation of novelty. It has been shown that R&D collaborations between actors is based on interactive processes of knowledge sharing. However, both partners have to show a certain degree of ability and motivation to disseminate and absorb knowledge. Trust has been determined as a key motivational dimension. In highly uncertain conditions, as R&D collaborations entail, trust is seen as a stabilizor of the willingness to share knowledge.
Different SIS vary in their science and technology base structure, innovation dynamics, and the importance of the local industries (Carlsson & Stankiewicz, 1991). Hence, the SIS in focus reveals certain challenges and opportunities for inter-organizational R&D strategies for new, enhanced drugs. In order to deliver meaningful results and implications, the thesis’ empirical analysis concentrates on one particular SIS of one industry sector in one country – the SIS of the Indian API sector. In this regard, it is useful to give an overview of the evolution of public policies in India as they have shaped the present SIS. In the literature, the history of the Indian pharmaceutical SIS has been divided into up to four epochs from 1850 to the present (Mazumdar, 2013). For reasons of clarity and limited number of pages, the evolution of the SIS will be divided into two epochs in this thesis. The first one lasts from India’s Declaration of Independence in 1947 to the early 1990s, while the second one lasts from the early 1990s to the present time.
Since India’s independence in 1947, the government focused on improving the institutional environment for the pharmaceutical industry through a self-reliance policy. The Industrial Policy Resolution of 1956 emphasized the role of the public sector by assigning it with the responsibility of encouraging the development of the industry through technology capacity building and the provision of management expertise. In this regard, the main priority of the Industrial Policy Statement of 1977 was the adaption of foreign technology as it was viewed as a key to facilitate indigenous R&D facilities (NCERT, 2006). As stated by the Pharmaceutical Enquiry Committee of 1954, the drug production of India witnessed a 3.5 times growth in the production from 1947 to 1952 (Mazumdar, 2013). This industry growth was supported by four initiatives.
First, the amended Patent Act 1970 recognized only short-term process patents and reduced the life of patents from 16 to 7 years from the date of filing a complete application or to 5 years from the date of sealing. Second, the Foreign Exchange Regulation Act (FERA) was implemented in 1973, which forced MNCs to manufacture high technology APIs. It was commanded by Section 29 of the FERA that foreign companies with an equity holding of more than 40 per cent and engaged in the manufacturing of only formulation products or APIs not developed by high-technology had to reduce their equity holding to 40 per cent or below (Lanjouw, 1997). Third, the Drug Prices Control Order (DPCO) 1970 was introduced, which for the first time reserved the government the right to fix the maximum selling prices of APIs. The government fixed the prices of 18 APIs and froze the prices of others, which implied a non-increase in price without the approval of the government (Sudip Chaudhuri, 2015; Sahu, 2014). Fourth, the New Drug Policy of 1978 restricted the equity holdings of foreign firms and reserved particular categories of drugs for the public-sector and domestically owned small-scale units (Horner, 2014b). These four initatives decreased the profitability of foreign MNCs as they became reluctant to invest in the Indian market. As a result, the share of foreign MNCs fell from 70 per cent to 50 per cent by the late 1980s (Mazumdar, 2013). At the same time, Indian firms adopted the provisions of the Patent Act, improved processes for the same product (reverse engineering) and began to market copies of patented products (Haakonsson et al., 2013).
Another significant development of this period was the beginning import of foreign knowledge and technology for the establishment of indigenous R&D facilities. For this, the government built five public sector units (PSUs) and research institutes, which were expected to assimilate foreign technologies. The first two PSUs, the Hindustan Antibiotics Ltd. (HAL) and the Indian Drugs and Pharmacueticals Ltd. (IDPL), were established in 1954 and 1961, respectively. The establishment of the IDPL was supported by the Union of Soviet Socialist Republics (USSR), while HAL was set up with technical assistance from the World Health Organization (WHO) and the United Nations International Children’s Emergency Fund (UNICEF) (Hindustan Antibiotics Ltd., 2015; Indian Drugs & Pharmaceuticals Ltd., 2015). These two PSUs played a key role in the initial development of technical competence and in facilitating the domestic API production (Joseph, 2011). In addition, government research institutes (GRIs) were established by the Indian Council of Medical Research (ICMR) and the Council of Scientific and Industrial Research (CSIR) to facilitate technological progress in India (Mazumdar, 2013). The CSIR system has over 20 laboratories engaged in pharmaceutical research (Chaudhuri, 2005b). Four other CSIR institutes – the Central Drug Research Institute (CDRI) of Lucknow, the Central Institute of Medicinal and Aromatic Plants (CIMAP) of Lucknow, the Indian Institute of Chemical Biology (IICB) of Kalkota, and the Indian Institute of Chemical Technology (IICT) of Hyderabad – account for a major part of both Indian and foreign patents, which signifies their vibrant drug research (Mani, 2009; Mazumdar, 2013)12. This will be analyzed in greater detail in section 5.2.2. According to Chaudhuri et al. (1997), some of the major Indian firms, such as Ranbaxy, Cipla, Wockhardt, Lupin, and Aurobindo Pharma Ltd., were supported by CSIRs, which reveals the laboratories’ success in promoting the technological conditions for the pharmaceutical SIS between 1950 and 1990.
It is widely acknowledged among scholars, industry analysts and policy makers that the provisions of the Indian Patents Act of 1970, the absence of product patents, and the establishment of PSUs and the CSIR system facilitated the development of the domestic pharmaceutical industry toward the pharmacy of the developing world (Horner, 2014b; Mazumdar, 2013; Sahu, 2014).
Although several reforms were initiated in the 1970s and 1980s, the liberalization of the Indian economy did not take place before the 1991 as part of a shift toward the Washington Consensus approach (Haakonsson et al., 2013; Horner, 2014a). The Statement of Industrial Policy 1991 demanded for a stronger promotion of the private sector through investments in technology development and manufacturing building. Instead of occupying a regulator role, the public sector had to change to a facilitator of the private sector (GoI, 1991). Subsequently, the Drug Policy of 1986 was modified and loosened the regulations for medicine prices and foreign ownership in the pharmaceutical industry was liberalized (Joseph, 2015; Mani, 2009). At the same time, foreign companies needed to expand their markets. The large Indian population as well as spreading disease patterns similar to those in the US and Europe, made India an attractive market for foreign MNCs. However, foreign MNCs did not begin to offshore outsource their R&D activities before 2005. By then, the Indian patent law had been amended to be compliant with the TRIPs Agreement (Haakonsson et al., 2013; Sahu, 2014).
Due to the necesssity for further expansion, the pharmaceutical industries in Europe and the US applied pressure on their governments to implement international minimum standards for the protection of patent rights. This led to negotiations about a global harmonization of intellectual property rights (IPR) at the 1986-94 Uruguay Round of trade negotiations establishing the World Trade Organization (WTO) in 199413. Of particular concern for European and American Chief Executive Officers (CEOs) was a sense of theft of IP through piracy, especially in developing countries with insufficient IPR protection, including India. It was argued that a country with no patent protection will enable actors to imitate new products without any R&D investment costs, which limits the opportunities of the innovators to regain their investments. Thus, patents represent the most effective instrument to protect product and process innovations in the pharmaceutical industry (Levin et al. 1987). Although developing countries opposed the harmonization of patents, because concerns arose that firms would lose the right to reverse engineer products, they acceeded to integrate IPR in the WTO in order to gain market access (Haakonsson, 2009b). As a result, the Government of India ratified the Final Act of the Uruguay Round at the Ministerial Conference held in Marrakesh in 1994 and agreed to accomplish the organization’s TRIPs Agreement by 2005.
Furthermore, the The Drugs and Cosmetics Act of 1940 and its subordinate legislation Drugs and Cosmetics Rules (DCR) of 1945 were amended in 2005 (GoI, 2005a). The government included stricter quality assurances at par with WHO standards through the incorporation of the Schedule M. It called for a legal binding to “design [...] and develop [...] [pharmaceutical products] in a way that takes account of the requirement of Good Manufacturing Practices [GMPs] and other associated codes such as those of Good Laboratory Practices [GLPs] and Good Clinical Practices [GCPs]“ (GoI, 2005a, p. 395). The aim of GMPs is to define methods of manufacture, control and material specifications and to provide a regulatory basis for the objective audit (GoI, 2005a). Test facilities looking for approval from regulatory authorities before marketing may apply to the National GLP Compliance Monitoring Authority to receive GLP certification (DST, 2015a). So far, there are only six pharmaceutical laboratories in India that have received the GLP-certification, although the number of test facilities in the National GLP Programme has increased from 13 in 2006 to 36 in 2015 (GoI, 2015e) (Table D 5, Appendix).
Moreover, the Government of India amended the Schedule Y of the Drugs and Cosmetics Rules, 1945, in 2005 “allowing pharmaceutical companies to start with clinical trials in phase II and in phase III at the same time with trials of the same phase carried out abroad “ (Maiti & Raghavendra, 2007, p. 4). Before its amendment, the schedule allowed clinical trials of drugs developed abroad with a phase lag only. This meant that phase II trials in India were permitted if phase III trials had been completed abroad (GoI, 2005a). Today, the amended rules allow parallel concurrent phase clinical trials in India, which reduces the clinical development time (Srinivasan & Nikarge, 2009). Consequently, the number of registered clinical trials at the Clinical Trials Register in India (CTRI) has increased to 6000 as on July 1, 2015 since its inception (Pandey, Aggarwal, & Gupta, 2014). Although today, trials are not allowed to be started without clearance from an ethic committee at each site, an increasing number of incidents have been reported during the last years where Indian patients have been exploited in clincial trials14. Within the last 3 years, India has become a global hub for outsourcing clinical trials. About 25 contract research Organisations (CROs) and almost all foreign pharmaceutical MNCs, such as Pfizer, GlaxoSmithKline, Sanofi-Aventi, Roche and Eli Lilly, have begun clinical trials in India. Several factors have led to the expansion of contract research and manufacturing services (CRAMS) in India. They mainly constitute an intensified competition in generics due to expected patent expiries until 202015, coupled with a decreasing number of new product launches, increasing pricing pressures16. In line with this development, many Indian firms have built state-of-the-art facilities and offer highly specialized CRAMS to pharmaceutical companies and other CROs (Maiti & Raghavendra, 2007).
In summary, a shift of public policy focus from a regime of control and the filing and granting of process patents to a regime of decontrol and filing and granting of product patents can be observed. During the era of self-reliance and the absence of product patents, Indian firms gained competences in reverse engineering, mainly supported by research-strong PSUs and GRIs. The liberalization of the Indian economy, the introduction of the amended Patents Act, 2005, and stricter quality restrictions resulted in an easing of foreign ownership and assimilation of foreign technologies. Hence, it can be assumed that India has become a location for drug innovation, leveraged by these changes in the institutional environment.
In this chapter, the key elements of India’s 17 SIS of the API sector are analyzed and discussed with the aim to evaluate their impact on the innovative performance of the sector and to answer the thesis’ first research question. Concurrently, the empirical findings of the surveys conducted with both employees of pharmaceutical firms and other industry experts in India are integrated where applicable. Before the thesis turns to the key components of the relevant SIS, a descriptive analysis of the sample’s firms and industry experts is presented.
This subsection offers a descriptive analysis of the pharmaceutical firms and other experts with knowledge about the API sector, which participated in the surveys. Figure D 9 shows the distribution of the respondents’ positions. 8 of the 9 respondents of the long survey, were middle or department managers, while 1 was managing director. Out of the 15 interviewees, who received the shorter industry expert questionnaire, 6 were managers of firms, 5 presidents of industry associations, and 4 (assistant) professors of universities in India. Accordingly, all of the 24 respondents were executives with significant experience in their field.
Turning to the firm’s R&D strategy, the interviewees were asked to indicate their R&D intensity, defined as R&D expenses as a share of annual revenues in the fiscal year 2014-15. Corresponding to the importance of R&D activities, a for the IPI relatively high share of the firm’s annual revenue is reinvested in R&D. Figure D 10 shows that a large share of the firms (44 per cent) reported an R&D intensity between 11 and 20 per cent, which is twice to four times as high as the domestic firms’ R&D intensity reported by the Indian Bulk and Drug Manufacturers Association (BDMA) (section 5.4.3.). According to the R&D intensity indicated by the respondents, one might assume that these firms are highly research intensive. But they may generate a large share of revenues by out-licensing their products to Contract Manufacturing Organizations (CMOs). None of the firms invested less than 5 per cent or more than 50 per cent of their revenue into R&D activities. Taken as a whole, the data presented in Figure D 10 suggests a relatively high relevance of R&D for India firms. The high share of R&D expenses on revenue is invested to advance the number of patents (Figure D 11). Nine firms answered the question about how many patents they had filed and granted between 2010 and 2015. It stands out that the majority (67 per cent) granted and filed more than 5 patents, 56 per cent of which stated that they had issued more than 10 patents. Thus, the data indicates that the firms interviewed produced a relatively high number of patents and reveal a somewhat high level of success of transferring their R&D into secured IP.
Now that the interviewees’ characteristics were presented, the thesis turns to the empirical analysis of the three main components of the SIS (Figure D 12): (i) the Government of India with its public policy and strategic direction managed by the Department of Pharmaceuticals (DoP), including the IPR based on the TRIPS-compliant Patents Act, 2005; (ii) the industry with private enterprises and subsidiaries of foreign MNCs, and (iii) the academia, including universities, pharmacy colleges, and National Institutes of Pharmaceutical Education and Research (NIPERs)18. Each of the component’s contribution to the innovative performance of the Indian API sector will be discussed and elaborated on in the following. If useful, the performance is compared to India’s main competitors, which have been labeled as pharmerging markets 19.
The government plays a key role in any SIS as it issues policies, which are conducive or impede the innovative business environment (Edquist & Johnson, 1997). In addition, the government constitutes an institutional framework, which facilitates R&D investment of all three SIS components. Although a number of policies were initiated in order to enhance the entire industry’s global competitiveness, policies, which have a significant impact on the innovational performance of the API sector, will be focused on in sections 5.2.1. to 5.2.4. They have been categorized into the overall policy framework, the patent regime, and the product and quality regime.
As previously mentioned, the key issue of the economic policy reforms in India since the beginning of the 1990s has been the different views about the public and the private sector’s functions. Prior to liberalization, the leadership role of the public sector was strengthened, whereas the private enterprises have been allocated a dominant role in the post-liberalization phase. The Indian Pharmaceutical Policy of 1994 has been the overall policy framework until today. Since the Pharmaceutical Policy of 2002 could not be implemented due to litigation involving it, the policy of 1994 remains valid. This policy framework set by the DoP is guided by the government’s overall vision “To make India the largest global provider of quality medicines at reasonable prices” (DoP, 2015), for which an upgrading of R&D potential for the development of APIs and associated drug discovery activities is viewed as essential (GoI, 2011).
The Make in India program, launched by the Prime Minister Narendra Moni on September 25, 2014, aims at encouraging MNCs and domestic firms within various sectors to manufacture their products in India. Part of the policies is the establishment of a National Center for R&D in Bulk Drugs (NCRDBD) affiliated with the NIPER, Hyderabad, for which a budget of USD 8.2 million (OANDA, 2015) has been drawn up by the DoP. This NCRDBD is sought to primarily promote innovative R&D in the API industry in India and aims to offer sustainable and competitive technologies in specified products and processes (GoI, 2012). Another objective of this initiative, according to Hansraj Gangaram Ahir, Minister of State, Ministry of Chemicals and Fertilizers, is to reduce India’s dependence on China by producing “100 per cent of bulk drugs domestically and stop the API imports from China in next two to three years“ (Chandna, 2015).
In order to formulate a long-term strategy to accomplish these goals, the Government of India constituted a High Level Committee headed by Dr. V.M. Katoch, former Secretary of the Health Ministry’s Department of Health Research. The Katoch Committee identified interventions and concessions to strengthen the domestic API production capabilities and examined cost implications. The committee’s report was published in September, 2015 and included recommendations for the development of the domestic API industry, such as the establishment of large manufacturing zones (LMZs) for the development of APIs with common testing facilities, assured power supply from state systems, treatment plants and common services and utilities and the expansion of financial and fiscal benefits to advance the API sector20 (GoI, 2015b). None of the Katoch Committee’s recommendations for the promotion of APIs and disocvery of NCEs have been realized so far. However, the Government of India has made considerable efforts toward API sector initiatives between 2012 and 2015 and is thus aware of the industry’s opportunities and threats from China.
The thesis now turns to the answers given by the interviewees in regard to the institutional hurdles, which impede the success of innovation facilitating initiatives (Figure D 13). Bureaucratic hurdles primarily range from extensive procedural delays and inefficient project management to the refusal of permissions for R&D projects and financial support21. The majority of the firms and industry experts (n=23) indicated that bureaucratic hurdles are a severe (39.13 per cent) or almost severe problem (26.09 per cent) for pharmaceutical R&D activities in India. Only 21.74 per cent stated that these hurdles represent minor problems for pharmaceutical R&D. Legal hurdles faced by Indian pharmaceutical institutions and firms involve, for instance, corruption, backlog of pending cases, or lack of transparancy. These hurdles are not viewed as problematic as bureaucratic hurdles. Only 17.4 per cent of indicated that these hurdles constitute severe (8.7 per cent) or almost severe problems (8.7 per cent). Moreover, the data connected to the legal hurdles showed a lower dispersion (standard deviation (std. dev.) 0.928) than the one associated to bureaucratic hurdles (std. dev. 1.167).
The most important change in the pharmaceutical policy in India after 1994 were the amendments of the patent regime in order to comply with the TRIPS Agreement. The Patents Act, 1970, was laid out for a process patent regime, which had transformed the Indian pharmaceutical industry into a strong global competitor. After the establishment of the WTO in 1994, it became obligatory for the country to make the existing IPR system TRIPs-compliant and to implement 20 years of patent protection on inventions, both of processes and products, in their national legislations. Developing countries, which had process patent regimes before 1995, were allowed an adjustment time of ten years to enforce product patents (WTO, 1994). But the TRIPs Agreement re-organized the industry immediately as countries were forced to grant special rights to market product and process inventions until their patent law were modified (Horner, 2014b).
The TRIPS Agreement covered IPR laws, which related to copyrights, trademarks, industrial designs, patents, and protection of undisclosed information. While all members of the WTO were obliged to implement minimum standards of IPR protection, they were allowed to frame their own IPR provision standards, such as the scope of patentability (WTO, 1994). Except from the laws related to patents, the laws on IPRs have been amended without substantial public protests or discussion in the Indian Parliament. The Amendment of the Patents Act, 1970, has been a crucial point of issue for the industry and public due to the fear that the IPI would no longer be able to reverse engineer and produce cheap generic medicines (Gujral, NWGPL & PILSRC, 2003). Hence, this amendment was the major hindrance in making the Indian IPR system compliant to TRIPs (Joseph, 2015).
India followed with its obligations under the TRIPs Agreement in three steps22, most importantly through the Patents (Amendment) Act, 2005, which introduced product patent rights in agro-chemicals and pharmaceuticals and India (GoI, 2005b). The act restricted the scope for evergreening of patents through the definition of pharmaceutical substance, of invention and inventive step. Evergreening implies an extension of patent rights beyond the specified 20 years by small changes of the original version of acquired patents (Chaudhuri, 2010). A new invention is defined as a “any invention or technology, which has not been anticipated by publication in any document or used in the country or elsewhere in the world before the date of filing of patent application with complete specification“ (GoI, 2005b, p. 4). An inventive step includes, per definition, technical progress compared to the existing technology and/or economic significance and means a feature that makes the invention not clear to a skilled person (ibid.). Section 3 (d) defines inventions, which are not patentable: “[…] the mere discovery of a new form of a known substance, which does not enhance the efficacy of that substance […] or a mere use of a known process, machine, or apparatus unless such known process results in a new product or employs at least one new treatment“ (ibid, p. 2).
On the one hand, the definitions stated in the Patents Act, 2005 enhanced the standards of patentable inventions and prevented trivial patents, as evident from the Novartis AG vs Union of India and Others dispute, after which Novartis’ patent application for the drug Gleevec was rejected (Table D 6). When Novartis had exclusive marketing rights of the drug sold under the name Gleevec for the treatment of multiple cancers, it had charged USD 2,50023 for a one-month course in 2001. After the rejection of Novartis’ patent application, Indian firms made a generic drug available at a cost of USD 165-200 for a one-month course (Kannan, 2013). Hence, the provisions of the Patents Act, 2005 ensured the delivery of low-price quality medicines to consumers. On the other hand, it is claimed that the more precise definitions of the standards as those given in the TRIPS reduce the number of patents, which otherwise would have been approved. According to Chaudhuri (2010), only a few drugs qualify for patents in India if the patent law is observed strictly. Of major concern is therefore whether the Patents Act, 2005 has proven as incentive for R&D activities for the development of enhanced drugs or whether the number of patents has been reduced.
1 In this thesis, the term API is used as a synonym for bulk drug.
2 In this thesis, the term firm is used as a synonym for pharmaceutical firm.
3 R&D collaboration activities have been investigated broadly in several streams of literature. In the Organizational Theory, R&D collaboration is viewed as a means to reduce opportunism and to create mutual trust between the partners in favor of the diffusion of knowledge (Belderbos, Carree, & Lokshin, 2004; Burt, 2004). In the Transaction Costs Economics, collaborations are viewed as a means for organizations to acquire new competencies and to reduce uncertainties connected to the development of new knowledge (Sampson, 2004). The Industrial Organization Theory, R&D collaborations are associated with an externality problem because organizations are not able to exploit the benefits of knowledge spillovers (Alcacer & Chung, 2007; d’Aspremont & Jacquemin, 1988). The Strategic Management literature has investigated R&D collaborations how they can be utilized by organizations to adapt to and acquire skills and competencies in order to gain a competitive advantage (Colombo, 2003; Mowery, Oxley, & Silverman, 1998). In this thesis, the theoretical framework has been chosen not to focus on these streams of literature but on the relationship between R&D collaborations and the innovation value chain concept since they together allow for a suitable analysis of early stage drug R&D collaborations.
4 “To successfully develop and manufacture a generic drug product, an applicant should consider that their product is expected to be: pharmaceutically equivalent to its reference listed drug (RLD), i.e., to have the same active ingredient, dosage form, strength, and route of administration under the same conditions of use, bioequivalent to the RLD, i.e., to show no significant difference in the rate and extent of absorption of the active pharmaceutical ingredient; and, consequently, therapeutically equivalent, i.e., to be substitutable for the RLD with the expectation that the generic product will have the same safety and efficacy as its reference listed drug” (USFDA, 2016a).
5 The interpretivist approach is significantly different from the positivist approach, whih derives from the epistomological tradition of objectivism, where objects have a meaning regardless of their subjective awareness (King & Horrocks, 2010).
6 SurveyXact, a professional tool for conducting surveys, was used (CBS, 2015).
7 The structure of the interview guideline follows the one used by Chandran, Sundram, & Santhidran (2014), Ermisch (2009) and Hansen and Birkinshaw (2007), which proved successful in exploring inter-organisational co-operation for product innovation in a structured and insightful way.
8 See Stiglitz (1998), Trott (2012), and Verspagen (1992) for more details on the neo-classical economic growth theory and the market failure approach.
9 For a detailed analysis on the concept of innovation systems in general, see Edquist, 2006, 2001, 1997; Lundvall, 1992; Nelson, 1993.
10 The early drug discovery process is a synonym for the pre-clinical development (J. P. Hughes, Rees, Kalindjian, & Philpott, 2011).
11 (Davenport & Prusak, 1998; Lam, 2000; Nonaka, 1994; Nonaka & Takeuchi, 1995; P. Smith, 2005; Stewart, 2012).
12 The IICT was established in 1944 under the name Central Laboratories for Scientific & Industrial Research (CLSIR) and renamed as IICT in 1989 (GoI, 2015c). The CDRI of Lucknow was inaugurated in 1951 (GoI, 2015i). The IICB was established in 1935 (GoI, 2015e) and the CIMAP was originally established as the Central Indian Medicinal Plants Organisation (CIMPO) in 1959 (GoI, 2015f).
13 The WTO was established and signed by 123 nations on 15 April 1994 and replaced the General Agreement on Tariffs and Trade (GATT), which commenced in 1948 (WTO, 2015).
14 In 2009, the US-based healthcare charity organization Path launched a project funded by the Bill and Melinda Gates Foundation to study the cost and feasibility of incorporating HPV vaccines, produced by Merck and GlaxoSmithKline, into India’s public sector immunization programme. HPV stands for human papillomaviruses, which cause cervical cancer. The case attracted attention because the volunteers’ parents were not told about the vaccinations. Other incidents were detected in 2003, 2006 and 2010 (Kuhrt, 2012).
15 Patent expiries of drug sales worth USD 99 billion are expected to materialize between 2015 and 2020, whereas between 2009 and 2014, USD 120 billion were lost (Evaluate Pharma Ltd, 2015).
16 India reveals lower manufacturing costs of 35-40 per cent of the costs in the US and 45-50 per cent of the costs in Europe. The costs of conducting clinical trials phase I are 50 per cent cheaper and the costs of conducting clinical trials phase II and III are 60 per cent cheaper (ICRA, 2011).
17 For an overview of the development of growth and revenue of the entire IPI, see Figures D 4 to D 8 in the Appendix D.
18 In his comparison of the SIS of the Indian pharmaceutical and telecommunications industry, Mani (2009) analyzes five components: (i) the policy direction, (ii) IPR regime, (iii) human resource development, (iv) technology generating sector; and (v) manufacturing sector. For reasons of clarity, three components will be looked at in this thesis.
19 In 2010, IMS Health redefined the pharmerging markets by identifying 17 key markets based on macroeconomic metrics. Today, 21 countries belong to these markets, which together are estimated to count for a rise in annual sales of USD 187 billion between 2012 and 2017. This accounts for two thirds of the global growth and is expected to increase Brazil’s, Russia’s, India’s and China’s global market share from 23 per cent in 2012 to 33 per cent in 2017 (Beck, 2013; Pineau & Rink, 2013).
20 Currently, the Indian government provides fiscal incentives for R&D for Indian firms in the form of tax breaks and tax-free zones. The Indian income tax law provides a benefit of a 200 per cent weighted tax deduction on the amount spent on in-house R&D expenditures (other than land and buildings) per year until 31 March 2017 (DSIR, 2014).
21 The importance of a functioning bureaucratic system for R&D collaborations is elaborated on in depth in chapter 7.
22 First, the Patent (Amendment) Act, 1999, provided for the receipt of patent applications (mailbox applications) and exclusive marketing rights. These rights implicate a patent-like monopoly for five years for products covered by product patent applications filed under the mailbox system. A company, which has secured such an exclusive marketing right is eligible to sell a substance covered by a patent application in the country (WTO, 1998). Second, the Patent (Amendment) Act, 2002 established 64 amendments, which brought provisions of the Patents Act, 1970 into conformity with the TRIPS Agreement. The third step to comply with TRIPS was the introduction of the Patents Act, 2005.
23 Calculated based on data provided by Joseph (2015, p. 149,152).
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