Proceedings of the 12th European Conference on Knowledge ...

The Symbolic Innovation <strong>of</strong> <strong>the</strong> Bio-informatics Discipline:
A Political Networks Approach to IT development
Alexander K. K<strong>of</strong>inas and Abdallah Al-Shawakbeh
Department <strong>of</strong> Business Information Technology and Enterprise, Engineering
School, Central Avenue, Chatham Maritime, Kent, UK
a.k.k<strong>of</strong>inas@gre.ac.uk
Abstract: In knowledge intensive firms IT is viewed as a means <strong>of</strong> cutting across bureaucratic barriers,
organisational complexity, and a tool for enhancing knowledge-related activities. In <strong>the</strong> pharmaceutical industry
this IT-led transformation coincided with o<strong>the</strong>r socio-technological phenomena such as biotechnology and <strong>the</strong>
Human Genome Project. The organisational uncertainty arising from <strong>the</strong> challenges <strong>of</strong> absorbing <strong>the</strong> new
knowledge created an organisational vacuum. This vacuum was filled by entrepreneurial scientists
knowledgeable in both bio-science and IT and dubbed <strong>the</strong>mselves as bio-informaticians. In a romantic sense
<strong>the</strong>se corporate entrepreneurs were allowed to explore <strong>the</strong> “wild frontiers” <strong>of</strong> pharmaceutical R&D research. This
paper relies on actor-network <strong>the</strong>ory (ANT) as an interpretation lens for clarifying <strong>the</strong> diverse elements that
enabled <strong>the</strong> successful creation <strong>of</strong> that organisational space. An in-depth exploratory case study is used here
with a framework based on ANT used for coding, organising and interpreting <strong>the</strong> qualitative data. The findings
highlight <strong>the</strong> importance and challenges an established company faces in absorbing new knowledge and
technology and <strong>the</strong> importance <strong>of</strong> leveraging <strong>the</strong> entrepreneurial instincts <strong>of</strong> its employees in order to create and
absorb new knowledge.
Keywords: R&D, pharmaceutical industry, drug discovery, actor-network <strong>the</strong>ory, knowledge, action, social
networks
1. Introduction: Bio-informatics and Symbolism
Traditionally <strong>the</strong> pharmaceutical industry has been very conservative. The reasons are numerous;
some are industry-specific such as <strong>the</strong> long product development cycles (drug discovery and
development can take 8-12 years), or <strong>the</strong> high pr<strong>of</strong>it margins that <strong>the</strong> top innovators enjoy (that could
lead to innovative complacency) while o<strong>the</strong>rs are socio-political such as <strong>the</strong> tight controls by
governmental bodies and regulations, or <strong>the</strong> sensitive nature <strong>of</strong> <strong>the</strong> health needs <strong>of</strong> <strong>the</strong> public that
drugs are to meet (Lerer and Piper, 2003, Denning, 2005). The large pharmaceutical firms in <strong>the</strong> early
1990’s, populated mainly by chemists ra<strong>the</strong>r than bio-scientists or computational biologists (Hulse,
2004, Quere, 2003) were unsure about <strong>the</strong> potential <strong>of</strong> <strong>the</strong> Information Technology (IT). As a
consequence, <strong>the</strong> pharmaceutical industry has been notorious for its hesitance to embrace IT for its
operations and research processes (Lerer and Piper, 2003). It was <strong>the</strong> Human Genome Project data
that finally shook <strong>the</strong> pharmaceutical industry into a spur <strong>of</strong> innovation and <strong>the</strong> formation <strong>of</strong> an IT
discipline peculiar to this industry called Bioinformatics.
1.1 Human Genome Project
When HGP was completed in 2000 it finished ahead <strong>of</strong> schedule mainly because <strong>the</strong>re was a vast
improvement in computer technology and <strong>the</strong> techniques for DNA sequencing. New technologies,
such as high throughput screening, DNA blasting, and genomic databases, were first applied during
<strong>the</strong> HGP (Elrod-Erickson and Ford, 2000, Griffith, 2000). The vast data provided by HGP was
unstructured and uninformed. The tools for generating DNA sequences <strong>of</strong> <strong>the</strong> human genome were
formidable but <strong>the</strong> analytical ability to gain knowledge and understanding from this data was lacking. It
soon became paramount for <strong>the</strong> pharmaceutical industry to find new tools and knowledge to absorb
and usefully utilise this data (McMeekin and Harvey, 2002). As a result during <strong>the</strong> 1990’s many <strong>of</strong> <strong>the</strong>
top pharmaceutical innovators made strategic alliances with or strategic acquisitions <strong>of</strong> biotechnology
firms in a bid to acquire <strong>the</strong> domain knowledge that would assist <strong>the</strong>m in using bio-sciences and bioinformatics
successfully to discover potential <strong>the</strong>rapeutic drugs (Quere, 2003). Despite <strong>the</strong>se efforts,
from <strong>the</strong> mid-1990s up until <strong>the</strong> present <strong>the</strong> pharmaceutical corporate R&D has been producing fewer
and fewer drugs that would gain governmental approval (Arlington, 2000, Gassmann and Reepmeyer,
2005). At <strong>the</strong> same period <strong>the</strong> biotechnology industry maintained its innovativeness and has been
involved in an increasing proportion <strong>of</strong> <strong>the</strong> newer blockbuster drugs.
The uncertainty around IT adoption existed in o<strong>the</strong>r industries such as accounting, law, engineering
but what makes <strong>the</strong> pharmaceutical industry unique is <strong>the</strong> creation <strong>of</strong> bio-informatics as a wholly new
discipline. This new discipline is interdisciplinary; it required a bio-science researcher who was
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