Abstract: The development of new drugs today is a hugely expensive process, with estimated costs of up to $1 billion to take a drug through to market. However, despite this seemingly massive expenditure, statistics show that the great majority of prescription drugs on the market today are only effective for around 40 % of the patients to whom they are administered. Worse still, recently there have been a series of high-profile instances where potentially block-busting FDA-approved drugs have subsequently been withdrawn due to unanticipated side effects that were only revealed when the drug entered use in the general population. A variety of factors are at play in underpinning such statistics, but at the heart of the problem is the fact that, despite the extensive knowledge being generated in the postgenomic era about the genetic differences between individuals, Western medicine still today largely ignores such differences. The hope therefore is that by gaining a greater understanding of the individual nature of disease progression and of drug response, we might move toward a new era of personalized medicine in which the right drug is prescribed at the right dose to treat the precise disease afflicting the specific patient. As a step along this road, this review will discuss new approaches in the pharmacogenomics field to understanding in a quantitative manner the molecular consequence of polymorphic variation and mutation, both on encoded protein function and on protein-drug interactions. Keywords: proteomics; protein-drug interactions; polymorphic variation; kinase; P450; p53.