NEED FOR COLLABORATIVE TECHNOLOGIES IN DRUG DISCOVERY - Collaborative Computational Technologies for Biomedical Research - page 8

$160,000,000,000 200

180
160
140
120
100
80
60
40
20
0

$140,000,000,000

$120,000,000,000

$100,000,000,000

$80,000,000,000

Deal Size
Number of Deals

$60,000,000,000

$40,000,000,000

$20,000,000,000

$0

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Figure 1.2 Pharmaceutical M & A activity, 2000 - 2009. ( Source: http://www.
marketwatch.com/story/ten- year - data - on - pharmaceutical - mergers - and - acquisitions -
from - dealsearchonlinecom - reveals - top - deals - and - key - companies - 2010 - 03 - 25 .
MarketWatch data based on original content from DealSearchOnline.com.)

patent searching, and pharmaceutics are all experiencing revolutions in their
processes. The related systems are thus also reacting to this process volatility.
This upheaval in the requirements and specifi cations of R&D IT systems is
causing IT budgets to increase, exactly at the moment when all budgets across
R & D are sharply decreasing.
We face an unprecedented era of rising process upheaval and constantly
evolving business requirements coupled with a cost-conscious environment
where chief information offi cers (CIOs) and R&D executives are looking to
simplify their IT architectures and their cost basis. If this trend continues,
informatics systems may become a bottleneck to the productivity of pharma-
ceutical scientists.

1.2.2 Externalization of Research: Collaboration with Partners

The area of greatest process upheaval is the externalization of research pro-
cesses and the growing collaborations between life science partners through-
out the R&D cycle. Originally CROs had been outsource partners, but currently
there are outsourcing partners for every phase of the R&D process, from
target identifi cation to chemical synthesis to pharmacokinetic studies to clini-
cal supplies, and so on. With this increased opportunity and necessity for
outsourcing, samples are constantly getting shipped to and from pharmaceuti-
cal laboratories. Every time a sample changes hands, there is a related data
exchange as well. Often, for a pharmaceutical company, several CRO partners
will be used for a single research project. Also, the CRO will likely have several
pharmaceutical clients. In this emerging net-centric industry model, there is a
complex graph of data exchange that must be supported (Fig. 1.3).