Principles and Practice of Pharmaceutical Medicine

to integrate these with observable (pharmaco)
epidemiology. This demands computational
expense that would have been unimaginable even
in the mid-1990s. Many phenotype databases are
now online and in the public domain, including
those for popular nonhuman experimental models,
such as for worms (e.g.C. elegans), yeast, maize
and mouse. There is also a human rare metabolic
disease phenotypic database available (http://
http://www.ramedis.de)..) These allow a reverse approach,
namely using phenotypes (or translated proteins)
as a marker for gene function, with the hope that
the latter can be influenced by novel therapies
in the future. These sorts of approaches can also
be used to develop ontologies, and thus identify
novel appropriate animal models for pharmacolo-
gical testing in preclinical drug development.
Pharmacoenomics is now awell-populated subspe-
cialty among statisticians, engineers and mathe-
maticians.
While unlikely to be directly involved in this
type of molecular biology research, it will become
the task of the typical practitioner of pharmaceu-
tical medicine to develop drug candidates gener-
ated by pharmaco- or proteonomic research.Vice
versa, those conducting this specialized form
of research are unlikely to regard themselves as

practitioners of pharmaceutical medicine. Thus,

we cannot offer a comprehensive discussion of

this field in this chapter, nor shall that be the case

in the rest of this book. The interested reader is

encouraged to consult the huge literature on this

subject, which now includes some useful general

textbooks (see below).

Acknowledgments

and Further reading

The authors thank David Feigal, MD, MPH, Med-

ical Deputy Director of the Center for Biologics

Evaluation and Research of the US FDA for pro-

viding us with information relating to the regula-

tions of drugs and biologics and the current

regulatory issues. For a comprehensive description

of the science of pharmacogenomics, the authors

recommend:

Auaje F, Dopazo J (eds.). 2005.Data analysis and

Visualization in Genomics and Proteomics. John

Wiley & Sons Ltd.: Chichester, UK and New York

(ISBN 0-470-09439-7).

Holm L, Sander C. 1996. Mapping the protein universe.

Science 273 : 595–603; and many of the excellent

general textbooks that are now available.

Appendix Useful Internet Links:Biotechnology product statistics ($ in billions)

2004 2000 Percent growth (%)

Number of companies 1444 1379 4.7
Number of employees 187 500 174 000 7.8
R&D expenses $19.8 billion $14.4 billion 1.3
Product sales $33.3 billion $19.3 billion 73
Revenues $46 billion $26.7 billion 72
Market capitalization $311 billion $331 billion  6
Net loss $6.4 billion $5.6 billion 14

A US billion is one thousand millions.

290 CH22 BIOTECHNOLOGY PRODUCTS AND DEVELOPMENT