Alliances create a better economic perspective, create better utilization of competencies and market structure, create integration between market participants. The alliance strategy can also be adapted to the R&D based Indian pharma industry because the industry exhibits supply side as well as demand side economies of scale giving rise to possibilities of direct and indirect alliances. This paper presents the possibilities of alliances which pharma industry can have with biotech and other allied fields of specializations. It gives a lucid exposition and insights on how Indian pharma industry can create hybrid governance forms, combine planning and economies for fruitful holistic perspectives on network strategy.
Though breakthrough innovations are difficult to create, they are critical to long-term competitive advantage. This highlights the considerable opportunities and risks that face corporate entrepreneur. A successful track record in breakthrough innovation significantly increases the likelihood of a current breakthrough, while achievements in non-generic incremental innovation do not have a significant effect. A strong foundation in generic incremental innovation hinders breakthrough performance. Thus, incremental innovation processes appear to be heterogeneous. Products that emerge from joint ventures and alliances are more likely to be breakthroughs. Foreign subsidiary participation in innovation processes do not significantly inhibit breakthroughs.
Innovation2 (the introduction of a new product, service) and entrepreneurship (the founding of a business) are virtually one and the same. The history of innovation research is vast and due to the continual rising of new challenges there remains a call for new theorizing. Future research should be linked to strategic entrepreneurship allowing for a better understanding of firm opportunity-seeking and advantage-seeking activities. While there is currently no dominant theory on innovation, there is agreement that innovation is a complex, difficult-to-measure construct that involves newness to some degree to the adopting unit or the marketplace, sector or industry and has a positive effect on firm performance. The impact on performance can be profoundly long-term. Pharmaceutical firms in their study maintained relatively stable company leadership positions for new product introductions and innovative output over a thirty-five time span.
Scholars and practitioners have argued that entrepreneurs must not just innovate occasionally, but often, quickly and efficiently to ensure future growth from revenues generated from customers purchasing new and improved products and services.
The behaviour of entrepreneurs and the influences upon that behaviour are clearly at the heart of strategic entrepreneurship. To this end, academics have determined that there are core elements such as firm-differences, competitive environment, strategy, task complexity and management style that affect the entrepreneurial processes and innovative outcomes across firms. A number of theoretical perspectives have been used to examine the innovation process including cognitive theory, dynamic capabilities, institutional theory, market orientation, resource-based view, socio-technical approaches, transaction cost economics, and so on.
Scholars of corporate entrepreneurship research traditionally have focused on ways in which firms can create positive changes within the organization involving new businesses and new product development. The two key phenomena that best define the processes surrounding corporate entrepreneurship are: (1) the birth of new businesses or internal venturing and 2) the transformation of organizations through renewed patterns of resource deployment. Within the wider context of corporate entrepreneurship, corporate venturing focuses on the firms which use both internally (i.e. new innovative businesses) and externally (i.e. licensing and strategic alliances) to create new opportunities within existing firm portfolios. Most of the research in this domain has focused on the parent organization rather than the venture unit or the new venture itself.
Strategic entrepreneurship research is becoming increasingly important as firms that were once not thought of as being entrepreneurial must become so if they want to prosper in the global marketplace. One of the significant challenges facing scholars in the field is that there needs to be a better understanding of the heterogeneity of corporate entrepreneurship activities (markets, products, established versus start-ups) from a broader life-cycle perspespective.
As a consequence, the announcement of novel innovations may not only push the firm out of its established knowledge platform, but also may have a profound impact on its ability to generate significant future profits. Given the magnitude that breakthrough innovations have on the economic growth of a nation and the long-term survival of a firm in its industry, it is crucial to understand the key factors that underpin successful corporate entrepreneurship. Our study focuses on the global pharmaceutical industry where the discovery, development and commercialization of new knowledge are particularly important for the delivery of innovative new products to the marketplace.
Three network formation factors--- network economics, competency and market structure influence the biotechnology-pharma industries, but they do so in differing ways, depending on the sub-segment of the industry. The preponderance of biotech alliances pertain most directly to the competencies category, where firms ally to leverage complementary competencies, such as a small firm’s new target drug discovery platform and an established pharma company’s clinical trials competency.
Most of these biotech- pharma alliances fall into the interface between competencies and market structure, due to the additional value provided by major pharma companies’ established distribution channels. Depending on perspective, a purely distribution alliance could fit either on the interface between competencies and market structure, as suggested in this example, or only as part of the market structure category. However, in portions of the biotech value chain where information plays a central role, such as in bio-informatics, genomics and proteomics, network economics factors help incentivize a network strategy . To illustrate how each incentive might impact the evolution of firm networks within an industry, we only need to trace the early history of the American biotech-pharma industries in view of its pioneering leadership and precursor in worldwide evolutionary industry development.
Previous alternative explanations of alliance formation such as asymmetry of investment markets or intellectual property flows seem to support this comprehensive incentive structure . Also the link to innovations could be part of a network strategy as it will generate dynamic efficiencies in R&D intensive industries giving rise to pharma-biotech increasing returns.
Evolution of alliances
The evolution of networks of firms within and between the pharma and biotech industries over the past 40 years illustrates not only the transformative power of the factors addressed by the Network Formation Dimension (NFD), but also their changing nature over time. NFD factors play varying roles, one dominating over a period, to be superseded and/or complemented by other factors as events unfold. Surveying the history of the pharma and biotech industries since World War II uncovers four primary inflection points in the evolution of network strategy in these industries, as in the Table.
The first factor, the US government contracted large-- scale production of drugs for the War effort, underscores the government’s role in disseminating knowledge and enabling investment in capabilities, encouraging the emergence of the contemporary pharmaceuticals industry. While this event did not necessarily engender corporate alliance formation, it exhibits the importance of the public/private partnership that led to the birth of one of our most important industries. The Thalidomide Crisis of the early 1960s led to the rapid expansion of government regulation of all aspects of the pharmaceuticals industry, reinforcing regulatory scrutiny, impacting the market structure . The success of early biotech products in the early 1980s initiated strong incentives for the formation of pharma-biotech alliances based on the need for firms to share complementary competencies. The advent of the Human Genome Project initiated a strong network economic influence to the evolution of these industries. Each of the four factors influenced the nature of governance decisions within the pharma and biotech industries.
During and following World War II, the expansion of pharmaceutical research and production capabilities arose as a result of the US government’s efforts to provide antibiotic production for the military. These defense expenditures vastly expanded the resources available for research, development and production of new drugs. Concurrently, early life sciences technologies, such as chemistry, biochemistry, microbiology and fermentation, began to emerge as viable development and production processes for a wide variety of products. By the late 1950s, early pharmaceutical research was characterized by extensive university efforts, funded in large part by the US, European and, later, Japanese governments. The early pharmaceutical companies such as Merck and Pfizer provided further resources to commercialize the results of laboratory research, scale-up production processes and market this new therapeutics. These early private sector/academic collaborations look primitive compared with arrangements of the late 1990s.
Until the early 1960s, it was still possible for a small pharmaceutical firm to emerge from the university or government lab research and successfully develop and market products as a stand-alone firm. Alliances were very rare, normally existing in the form of intellectual property licenses and manufacturing contracts, where larger producers would provide scaled-up production capabilities and access to distribution and marketing channels. These alliances between emerging and more established pharma companies tended to be less integrated than those of the late 1990s. Moreover, it was possible for small and mid-sized pharmaceutical companies to succeed in developing and marketing therapeutics as independent firms. By the 1990s, it was virtually impossible for any firm, beyond the most established and well capitalized, to bring a drug from research to market on its own.
The Thalidomide crisis and industry consolidation
Between 1957 and 1961, three German, British and American firms introduced a new drug, Thalidomide, for approval to the authorities in the three major pharmaceutical markets - the US, Europe and Japan. Thalidomide had been shown to be highly effective in the treatment of morning sickness in pregnant women. While European and Japanese regulators approved the drug, US regulators withheld approval. Frances O. Kelsey, at the time a new FDA medical officer, led the team that rejected the drug’s application. When the FDA received the application in 1961, as Kelsey explained in a conference on thalidomide held by the FDA in 1997, the new drug application (NDA) process was quite different than after the crisis:
‘Many of the studies in support of new drugs were written really more as promotions than as scientific studies. The ground rules in those days were that after an application had been submitted and filed with the agency, the agency had 60 days in which to decide that the drug was safe for the proposed use or uses. There was no requirement for efficacy, and this of course was one reason why the applications were so much smaller.
After a few years of successful sale of the drug, in some cases over the counter in Britain, the healthcare community began to recognize a substantial increase in birth defects correlated with the use of thalidomide. Soon after, the drug was pulled from the market. Aside from the devastating impact on the families who endured the crippling effects, the most significant long-term impact of this crisis was to pressure government regulators to increase the rigour of the therapeutics approval process by orders of magnitude. The Kefauver-Harris Act, passed in October, 1962, required both proof of safety and proof of efficacy for NDAs. The FDA dramatically changed its procedures and requirements for applications as a result. Other developed nations followed suit over the following years, and because of recent concerns on drug safety the issues have re-emerged for the FDA. By the mid 1960s, only large firms could afford the animal and human testing required by the FDA to bring new drugs to market. As a result of this expansion and deepening of regulatory control, the pharmaceutical industry underwent a period of steady consolidation between 1963 and the late 1970s as firms merged were acquired or went bankrupt. The Incidence of alliances or cooperative agreements between large and small Pharma firms also decreased to near insignificance. The remaining pharmaceutical firms found that they required substantial control of the drug R&D process, in order to pass the stringent, time consuming and costly requirements of federal regulations. Effectively, the smaller players had been regulated out of the market. Between 1965 and 1970, not a single small pharmaceutical firm emerged as a major or even mid-sized player as a result of its own internal growth.
M&A activity remained rapid until the late 1970s, when the pace slowed. This process of marketplace consolidation through firm integration occurred as a result of the market structure factor of regulatory change. The regulatory change triggered by the thalidomide crisis led to a fundamental shift in the network structure of the industry. Firms that failed to drive consolidation were merged, acquired or forced out of business. By the 1970s, accepted industry wisdom asserted that the development of new pharmaceutical firms was highly unlikely, because of high barriers to entry, due to the massive investment and long lead-time required for success.. Nonetheless, radically new technologies developed throughout the 1970s would eventually lead to the emergence of new pharmaceutical players enabled by a new collaborative model of competition.
Coincidentally, as the pharma industry continued to coalesce around fewer, more massive firms, substantially new technologies began to emerge from university laboratories. Since the discovery of the double helix structure of DNA by Watson and Crick in the 1950s, and the explosion in basic life science research during the 1960s and 1970s, a number of new DNA-focused technologies arose from within government and university research labs. Despite significant progress in the lab, by the mid 1970s none of these new DNA-based technologies had yet produced marketable products. Researchers required assistance from established pharmaceutical firms in order to fulfil FDA regulatory requirements, develop scalable manufacturing capabilities, and market and distribute new therapeutics. Unfortunately, established pharmaceutical firms were sceptical, and few extended the capital or expertise necessary to help commercialize any of the new DNA-based technologies. The industry continued to focus on the established, ‘hit-and-miss’ approach of the chemical manipulation of molecules as the primary source for new drug candidates, a sort of ‘trial-and-error innovation’.
R&D path of the pharma industry during this time much of research in drug discovery was empirical, not systematic, i.e. drug discovery ‘arising from a search, more or less informed., among many possibilities’, a process much akin to new discoveries in the chemical industry but with new tools originating from ‘computational explorations’ . The research, development and manufacturing requirements of the “new” biotech required a very new approach, and none of the established players were willing to take the risk. In retrospect, this decision appears short-sighted, but we must recognize the significant time-to-market predicted at the time for most of these opportunities. In many cases, industry experts did not even consider many of the new technologies likely to succeed commercially, if at all. Nonetheless, had pharma companies allocated even a small portion of their R&D budgets to a portfolio of these forward thinking projects, they might not have encountered the “catch-up” condition in which many firms found themselves by the mid-1980s.
Genomics and network economics
The competencies and market structure dimensions have played the predominant role in explaining the transformation of the pharma and biotech industries’ network structure and behaviour. Network economics will add a leading role in this discussion. After the point where an academic-like openness to basic research is no longer essential, research into new therapeutics becomes highly proprietary. Researchers become much less willing to share information, patents are dominant and intellectual property strategy restricts information flow between researchers. This not only applies to research conducted in for-profit settings, but extends too many academic settings as well. As suggested in the introductory discussion of the social nature of knowledge creation, this lack of openness retards intellectual and technological progress. Nevertheless, individuals and firms must be provided an incentive to innovate, which in almost all cases requires proprietary ownership of intellectual property in some form.
This issue presents fewer problems in the identification and creation of new drugs under the traditional R&D model. Traditional molecular chemistry offers the ability to create a vast number of compounds that firms can investigate and develop as marketable drugs. The fact that another firm owns a patent on a particular compound has limited impact on another firm’s efforts. If one firm is aware of the patent, it might decide to pursue an alternative direction. Moreover, once a firm achieves a patent on a particular compound for a specific condition, that firm is reasonably assured of proprietary rights to profit from the sale of the drug, assuming the drug passes FDA muster.
The situation became much more complicated with the introduction of genomics, proteomics, its more complex sibling, and the broader field of bioinformatics and systems biology. As the application of information technology increasingly transforms the drug discovery process from primarily a matter of chemistry and biology to an information-intensive pursuit, as IBM’s ‘Blue Gene Project’ appears to indicate, network economics plays an increasing role. A shift toward ‘priority review drugs’ against ‘standard review drugs’ showed an increasing share of new molecular entities (NMEs) at the expense of new chemical entities (NCEs),and reflects the paradigm shift toward biopharmaceuticals. This fact presents crucial implications for the nature of network strategy in the industry.
The United States Government began funding for the Human Genome Project (HGP) in the 1980s, coordinated through the National Institutes of Health (NIH) after years of lobbying by the scientific community. Many sources, academic and popular, provide extensive coverage of the detailed background of the project, as well as the much - publicized controversies surrounding the competition between public and private efforts to map the genome. Using genes as targets for new therapeutics existed well before the HGP; however, prior to the availability of an effective gene map, researchers would start from a particular observed pathological condition and attempt to work backwards to identify the culpable gene or genes. This represented an unacceptably slow, cumbersome process. Since the introduction of technologies capable of accelerating the mapping of the genome and the identification of specific genes related to diseases or pathologies in subjects, the pace of progress has intensified by orders of magnitude.
Information and drug discovery
Despite the hype and the value of a complete genomics database, the human genome map alone provides an insufficient platform with which to create the next generation of highly targeted and valuable therapeutics. A proprietary understanding of the proteome could arm a competitor with a substantial competitive advantage; however, the task presents a challenge orders of magnitude greater than mapping the genome. Rather than simply representing the order of nucleotides, as in the genome, understanding the proteome requires mapping the three-dimensional structure of proteins and the behaviour of their structuration with respect to functions and activity.
Proteins consist of 20 naturally occurring amino acids. The sequence of these amino acids partly determines the shape and behaviour of the proteins they create. Mapping each human protein independently requires such a long time as to be impractical; however, local structures within proteins, known as domains, reflect consistent behaviour between different proteins. Much like the root structures of ideographic written languages, such as Chinese, these root structures manifest in a relatively consistent manner. Once a domain is identified, that part of the protein structure is considered understood. Moreover, proteins group into families as a result of common ancestry. As a result, biochemists can predict protein structures of subject proteins based on resemblance to known protein families.
Here is where demand side economies of scale, or network economics, become important., not the least to reduce the uncertainty on scale and dimension of drug discovery . As further explained by The Economist, ‘Since knowing the structure of one member of a protein family lets researchers guess what others will look like, the most efficient strategy for choosing protein targets should cover as wide a diversity as possible. That is not, unfortunately, what is happening. At the moment, laboratories are competing to work out the same protein structures, rather than collaborating in the way they did to produce the human genome’.
The Human Genome Project began as a worldwide, publicly-funded collaborative effort. Mapping the human genome resolved as a competition between proprietary and public rights to genes that offer targets for therapeutics. In the case of the proteome, “the days of happy collaboration are gone, not least because a lot of money is now at stake. Proteins are drug targets, and some may become drugs in their own right”. As a consequence, many researchers jealously guard the results and methodologies of their protein research.
In the June, 2001 issue of Nature and Structural Biology, a team from MIT, Harvard, the University of Maryland and Millennium Pharmaceuticals reported on its efforts to understand the costs associated with this lack of cooperation among researchers in this proteome effort. They estimate that 16,000 targets would provide enough information to survey 90 percent of all protein domains, if all were widely available. Lacking a coordinated approach, the team reckons an equivalent survey would require “around 50,000 experimental determination of structure.
The co-ordinated approach achieves higher efficiency by allowing researchers to target domains for study based on more complete information. The non-collaborative model requires a substantial amount of random target selection. Assuming the ability to define ten structures per week, the going rate, an independent research team could expect to work nearly a century. Even though technology will continue to improve throughput, ‘a bit of collaboration would speed things up to end’. Here we see the conflict between proprietary ownership of knowledge and cooperation for the common benefit.
There would clearly be substantial common benefit from a coordinated mapping effort, while the identification of protein function relative to diseases or disorders, and the development of targeted drugs, could be kept proprietary. As by then, open collaboration appeared unlikely, largely as a result of the competition over the results of the human genome map. Barring broad collaboration, co-operation between specific firms and research organizations could present a more effective solution than operating as insulated actors, while maintaining proprietary benefits. The co-operative efforts of the HGP and the associated competition that ensued provide a precedent for building a viable strategy around proteomics. Succeeding in the genomics and proteomics space requires a network specific strategy built around a strong core of firm specific resources. All of the major genomics firms by market valuation employ an extensive network strategy, leveraging their proprietary firm-specific resources across multiple firms. The value accrued to all increases substantially with the breadth and diversity of minds addressing the application of the new knowledge; nonetheless, all organizations involved must be able to appropriate enough value to justify co-operation.
A complete widely available map of the genome increases the likelihood of the development of new therapeutics, consumer well being and the overall profitability of the pharmaceutical industry. The actions of pharmaceutical firms to block genomics firms’ attempts to convert the human genome map into a firm specific resource evidence the industry’s concern over ceding control of a crucial resource to a single firm. The compelling network economics implications of the genome database, allied with the combined market structure influences of the major pharmaceutical firms, government regulators and the scientific research community compels a pharma company to make many substantial strategic changes in course. A robust network strategy might provide the only viable way to profit from the genome database, for which the company has invest to hundreds of millions of dollars. The same might prove true of the proteomics database. The nature of knowledge compels cooperation.
As evidenced by the contrasts between the strategies of major genomics players, there is no single solution to understanding the proper balance between network specific and firm specific resources. The objective should be to achieve the most advantageous sustainable, profitable balance. Firms can co-exist and compete, applying contrasting strategies, as in the case of VISA and American Express in the bank card industry. Nonetheless, any case where network economics exerts a strong influence requires a careful consideration of inter-firm cooperation.
Conspicuously, the introduction of genomics and proteomics to the drug discovery and development process further encourages large firms to seek biotech partners. According to the Industry Standard,’ pharmaceutical companies have begun to realize that matching the breadth and technological sophistication of genetic research ongoing at biotech firms would require a massive, time-consuming internal investment. Machines to decode, classify and interpret genetic information often cost well into the millions of dollars, and recruiting people to run them can be a challenge. Instead of doing it all themselves, large pharmaceutical companies that once fiercely guarded their privacy have begun crafting long-term and largely equal partnerships with biotech companies.
By the late 1990s and early 2000s, biotech firms perceived likely to enjoy success were able to pursue agreements with pharmaceutical companies on much more advantageous terms than had been previously possible. The introduction of information intensive technologies to drug discovery proved different enough from traditional methods that the large drug makers were compelled to seek partnerships rather than build the competency internally.
To the future, it will be important to monitor the extent to which Big Pharma successfully acquires genomics and proteomics players and competencies, as opposed to remaining allied with independent genomics firms, as well as the extent to which the industry creates information sharing capabilities. Traditionally, the pharmaceutical industry has been averse to sharing information between companies. The collaborative nature of knowledge creation has compelled the industry to place more emphasis on R&D efforts outside the boundaries of the individual firm.
(Note : The second part of this article is on biotechnology and drug development) The author is faculty Veerayatan Institute of Pharmacy, Mandvi, Kutch, Gujarat