After its emergence as a discipline akin to both pharmacology and genetics, pharmacogenetics focused on determining the relationships between variations in single genes and variations in the response of individuals to drugs and other exogenous substances. The intent of pioneer investigators was firmly rooted in learning how human responsiveness to these agents was linked to the molecular processes of cells and tissues. After biologists deciphered the mechanisms by which cells read information encoded in the human genome and invented ge-nomics technologies, the switch from pharmacogenetics to pharmacogenomics began, bringing about dramatic changes in the pace and scope of pharmacoge-netics from the mid-1980s to the present time.
Going from genetics to genomics resulted in a flood of new gene discoveries and new approaches to the identification of drug susceptibility loci; applications of genomics principles led to the discovery of many gene-based drug targets and to incremental advances in the development of new therapeutic agents. Today, the composition and function of hundreds or thousands of human genes spanning large fractions of the genome in many individuals and populations can be examined efficiently as a result ot advances in high-throughput genomic technologies combined with new methods to store, access, and analyze genomic data. A plethora of conferences, workshops, and educational programs focusing on a wide variety of themes helped everyone keep pace, while academic and industrial scientists, including many whose skills and immediate interests lay outside biology, lent their expertise to pharmacogenomic initiatives.
The traits that we use to illustrate the principles and consequences of phar-macogenetics throughout this book typically fall into three groups: those associated with the altered transport, distribution, and elimination of therapeutic agents, those resulting from the adverse effects of such agents, and those associated with genetic variations of the targets for these agents. These traits are representative of dozens of other genetic markers of human drug responses not specifically mentioned. Although the means of detecting and characterizing any specific trait are likely to change in the future, the vital characteristics of the trait—that is, its genetics (inheritance, allelic frequencies, and population variation), molecular basis (genes responsible and their mutation spectrum), and medical or biological significance—are not.
By the year 2000, as the Human Genome Project approached maturation, a strong case could be made for the structural and functional analyses of genomic diversity aimed at producing a complete catalog of human pharmacogenomic diversity [single-nucleotide polymorphisms (SNPs), copy number variation, deletions, insertions, repeats, rearrangements, and mobile elements]. By establishing associations between the unique genetic makeup of individuals and their responsiveness to specific drugs, foods, and other exogenous substances, the discovery of better therapies and improved prospects for individualized medicine were anticipated.
As a consequence of decades of detailed studies on the biochemical and molecular basis of physiological and pharmacological cell functions in humans and model systems and the development of analytical and computational technologies, pharmacogenetics has been transformed from a descriptive to a predictive science. The field has reached a point at which many of the complexities of the human drug response are understood and some can be predicted. It is also evident that we are just beginning to appreciate the extreme complexity of biological systems and that the biological landscape will continue to change rapidly, delivering new insights that must be considered as the genetics and genomics of human drug responses advance. As in most other biological fields, pharmaco-genetics is primarily a data-driven science without which attempts at prediction are likely to fail. This chapter considers a number of areas and topics, derived mainly from the recent literature, that are likely to aid prediction and to be important to the future of pharmacogenetics and pharmacogenomics.
Was this article helpful?