Response to medication is highly variable, unpredictable and, at times, may be fatal. All drugs are more effective in certain groups of the population while showing no or minimal benefit in other groups. Although the current data on the subject are piecemeal, anecdotal evidence suggests that, in line with other common multifactorial traits, a myriad of genomic as well as environmental factors underpin population variability in drug response. Pharmacogenomics is the study of how variations in the human genome affect the variability in response to medication. Efforts to personalize treatment based on results from pharmacogenomics studies have the potential to increase efficacy, lower the overall cost of treatment, and decrease the incidence of adverse drug reactions, and are one of the major challenges of the modern era. The classical twin design has traditionally been used to assess the relative contribution of genetic and environmental factors to population variation in common, complex phenotypes, including drug response. Twins are not commonly regarded as providing the optimal design in genomic studies. However, we argue that, through their precise 'matching' for confounding variables (age, sex, cohort and common environmental effects), their amenability to numerous nonclassical study designs (genome-wide association studies or the role of epigenetic factors), and the availability of large, established registries worldwide, the twin model represents a flexible study design for systems-biology studies of drug response in humans. In this review, we describe the 'classical twin model' and its application in traditional pharmacogenetics studies, discuss the value of the twin design in the modern systems biology era, and highlight the potential of existing twin registries in formulating future strategies in pharmacogenomics research. We argue that the usefulness of this design goes beyond its traditional applications. Moreover, the flexibility of the model in concert with the amenability of large, established registries of twins worldwide to the collecting of new phenotypes will mean that the study of identical and nonidentical twins will play a considerable role in shaping our understanding of the important factors that underpin population variability in common, complex phenotypes, including response to medication.