Biomedical Engineering Reference
In-Depth Information
28.1
INTRODUCTION
Drug discovery and development is largely considered a linear process pro-
gressing through many steps such as from target discovery through registration
and post approval, at which point the drug is on the market (Fig. 28.1). It is
obviously not as straightforward as such simple graphical representations
suggest. Through each of the steps there may be feedback subloops, blurring
of the boundaries, and much fi ner levels of detail could be added. Needless to
say it is a long and very expensive process and is clearly unsustainable for
many, other than the very big pharmaceutical companies. It is widely recog-
nized that the way drug discovery and development are carried out has to
change. We have seen in recent years pharmaceutical companies signifi cantly
reduce their research and development (R&D) footprint to the point where
most chemistry is performed relatively cheaply in Asia while clinical develop-
ment is increasingly outsourced to contract research organizations (CROs).
The big companies are splintering, and those scientists no longer employed by
these multinational companies will reform new companies (micropharma) or
loosely linked collaborative groups whether as consultants or virtual CROs.
The now smaller “big” pharma can achieve their goals through leverage of a
growing number of external relationships whether collaborative, precompe-
tivive, partnerships, and so on.
This topic has brought together the collective observations of a number of
specialists who are engaged in supporting the paradigm change that is occur-
ring as biomedical research rapidly moves toward a collaborative network of
chemists and biologists. In the process, it will make both data and knowledge
available to the masses, thereby enabling rapid sharing of information [1-4].
This new paradigm will present many opportunities for collaborative software
and data-sharing tools to be further developed and is likely to result in new
technologies to overhaul the drug discovery R&D process (Fig. 28.1). But
there are many questions still to answer, such as how people need to be trained
to collaborate and whether collaborations will truly replace the “great man
theory” of science in which major discoveries are often attributed to one or
more fi gurehead men or women rather than teams of scientists. Also many
companies have iron fi rewalls which prevent linkage to common collaborative
tools like GoogleDocs and therefore directly impede potential for collabora-
tion. Such issues will need discussion but may be outside the scope of this
chapter and book.
28.1.1
Gap Analysis for Drug Discovery and Development
One way to look for the opportunities for collaborative approaches is to
understand the process and perform a gap analysis. The well-known drug
discovery and development process is a good example onto which we have
mapped those areas in the process that may be addressed with collaborative
software and mobile computing efforts (Fig. 28.1 and Section 28.7). Mobile
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