knowledge development method (epistemology) was changing significantly,
particularly in biosciences. This in turn, it can be shown related to technological
changes consequent upon precisely the rapid diversification in cognitive skills brought
about by the demands of such activities as gene sequencing and the eventual decoding
of the human genome that ushered in the post-genomic era.
Thus, in a regional ‘megacentre’ to be discussed in more detail in Section 6, that of
Northern California, it is clear that the biomedical industry relies crucially on
information and communication technologies (ICT) to decode and synthesise
bioscientific information. This is drawn from the knowledge-intensive ICT base in
Silicon Valley, and includes sequencing and screening workstations, photonics and
optical networking, low-level electrical energy instrumentation, and software among
many others. This convergence between ICT and bioscience has contributed to
discoveries in genomics, proteomics, therapeutic cloning and stem cell research, and
these in turn enable improved treatments for high ranking disease targets like cancer,
cardiovascular, AIDS, diabetes, and respiratory diseases. But the transdisciplinarity
also operates within and between specific sub-fields like molecular biology,
combinatorial chemistry, high throughput screening, genomics and bioinformatics. In
conducting knowledge exploration multidisciplinary teams of researchers are more
prominent than before. In conducting knowledge exploitation DBFs in the distinctive
sub-fields form project-based networks interacting also with ‘star’ scientists and their
teams.
As Zucker et al. (1999) see it, such projects involve no or few ‘untraded
interdependencies’, they are strictly business transactions, with contracts,
confidentiality agreements, time-limits and agreed actions (writing a patent or a paper,
for example) and outcomes. Other actors will also enter this mise-en-scène at various
points, as ‘knowledgeable attorneys’, consultants or venture capitalists (Suchman,
2000). So we may conclude that bioscientific megacentres are realised in the presence
of a nurturing ‘economic business environment’ consisting of: (1) the quality of the
inputs available to firms (e.g. human resources, physical infrastructure, availability of
information); (2) the availability and sophistication of local suppliers of components,
machinery and services, and the presence of clusters of related firms; (3) the
sophistication of local demand for advanced products and processes, including the