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.