Alzheimer's disease (AD) is a complex disorder associated with multiple genetic defects either mutational or of susceptibility. Information available on AD genetics does not explain in full the etiopathogenesis of AD, suggesting that environmental factors and/or epigenetic phenomena may also contribute to AD pathology and phenotypic expression of dementia. The genomics of AD is still in its infancy, but is helping to understand novel aspects of the disease including genetic epidemiology, multifactorial risk factors, pathogenic mechanisms associated with genetic networks and genetically-regulated metabolic cascades. AD genomics is also helping to develop new strategies in pharmacogenomic research and prevention. Functional genomics, proteomics, pharmacogenomics, high-throughput methods, combinatorial chemistry and modern bioinformatics will greatly contribute to accelerate drug development for AD and other complex disorders. Main genes involved in AD include mutational loci (APP, PS1, PS2, TAU) and multiple susceptibility loci (APOE, A2M, AACT, LRP1, IL1A, TNF, ACE, BACE, BCHE, CST3, MTHFR, GSK3B, NOS) distributed across the human genome. Genomic associations integrate bigenic, trigenic, tetragenic or polygenic matrix models to investigate the genomic organization of AD in comparison to the control population. Similar genetic models are used in pharmacogenomics to elucidate genotype-specific responses of AD patients to a particular drug or combination of drugs. Using APOE-related monogenic models it has been demonstrated that the therapeutic response to drugs in AD is genotype-specific. A multifactorial therapy combining 3 different drugs yielded positive results during the 6-12 months in approximately 60% of the patients. With this therapeutic strategy, APOE-4/4 carriers were the worst responders, and patients with the APOE-3/4 genotype were the best responders. In bigenic and trigenic models it was possible to differentiate the influencial effect of PS1 and PS2 polymorphic variants on mental performance in response to multifactorial therapy. The application of functional genomics to AD can be a suitable strategy for harmonization in molecular diagnosis and drug clinical trials. Furthermore, the pharmacogenomics of AD may contribute in the future to optimise drug development and therapeutics, increasing efficacy and safety, and reducing side-effects and unnecessary costs.