Optimal N-of-1 Clinical Trials for Individualized Patient Care and Aggregated N-of-1 Designs

Abstract

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.