Drug Discovery7

Though rooted in the basic principles of molecular biology, advances in both technology and biostatistical methods continue to yield an ever-evolving array of tools 8.

for the examination of DNA, RNA, and protein (Table 4.4). Though population studies are of interest to the pain research community as a means of identifying common genetic risk factors for pain sensitivity, a useful tool for 9.

the discovery and characterization of genetic risk factors continues to involve studies of gene and protein expression (Table 4.2). Common uses of expression analyses include causal and susceptibility gene discovery, drug 10.

development, drug response, and therapy development. The study of gene expression requires obtaining RNA from specific tissues (e.g. neurons, sensory ganglia, central nervous system, brain). To date, because of this 11. need for target tissue, the majority of expression micro-array pain research is limited to animal models. However, novel minimally invasive methods (e.g. laser capture microdissection) may increase the opportunity to study gene expression in human tissues that are readily accessible.48

Though lagging behind the study of the human gen- 12.

ome (i.e. DNA) and transcriptome (i.e. RNA), the proteome (i.e. protein) is a frontier of great interest. Whereas individual proteins can be readily studied given sufficient quantities and purity, more high-throughput approaches 13.

(i.e. analogous to gene expression arrays) is still cost-prohibitive. This approach suffers from the same limitations as RNA-based methods (i.e. access to tissue); however, recent proteomic analysis of spinal protein expression in rats exposed to morphine suggests that this * 14. approach will provide a novel tool in pain research.49

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