A great deal of recent attention has been given to the concepts of 'personalized' or 'individualized' medicine and nutrition. This attention is rooted in the belief that high-throughput molecular technologies such as DNA sequencing, transcriptome assessment, proteomics, metabolomics, and microbiome profiling can identify an individual's unique molecular profile (i.e. Garrod's 'chemical individuality') in a way that could reveal very specific ways in which interventions or treatments could be deployed in order to optimize that individual's health. However, as justified as the attention to individualized medicine might be, there are some very thorny issues surrounding how one can identify and validate the individual-specific profiles that might be used to optimize interventions and health. In this talk, I discuss how one can design 'N-of-1' or single subject trials that can be used to test the influence of a specific, tailor-made intervention strategy. Such trials can focus on the influence of diet and nutrition on the microbiome and can be designed with an individual's baseline microbiome profile in mind, knowing that such baseline profiles might vary from person to person. In addition, ancillary resources, such as appropriate databases to house the results of N-of-1 trials and the profile information of the subjects, are discussed. Finally, appropriate statistical methods, for not only conducting the studies, but also identifying microbiome profile and related profile differences between individuals and groups of individuals, are discussed in non-mathematical terms.