Precision medicine typically refers to the use of genomic signatures of patients to assign more effective therapies to treat patients, or, for improved diagnosis of the early onset of a disease so that interventions can be delivered to prevent or delay the disease progression. Because the aim is to provide individualized patient treatment, such single-person trials are called N-of-1 trials. This chapter reviews fundamental ideas, models, and construction of optimal designs for N-of-1 trials, which are invariably constructed from crossover trials, where each patient receives a random sequence of trial treatments over time. We construct examples of universally optimal N-of-1 designs for comparing two treatments under various correlation structure assumptions and discuss how N-of-1 trials may be combined to form optimal aggregated N-of-1 trials for assessing average treatment effects for two or more treatments.
Part of the book: Recent Advances in Medical Statistics