Averaged versus individualized: pragmatic N-of-1 design as a method to investigate individual treatment response

Heterogeneous treatment effects represent a major issue for medicine as they undermine reliable inference and clinical decision-making. To overcome the issue, the current vision of precision and personalized medicine acknowledges the need to control individual variability in response to treatment. In this paper, we argue that gene-treatment-environment interactions (G × T × E) undermine inferences about individual treatment effects from the results of both genomics-based methodologies—such as genome-wide association studies (GWAS) and genome-wide interaction studies (GWIS)—and randomized controlled trials (RCTs). Then, we argue that N-of-1 trials can be a solution to overcome difficulties in handling individual variability in treatment response. Although this type of trial has been suggested as a promising strategy to assess individual treatment effects, it nonetheless has limitations that limit its use in everyday clinical practice. We analyze the existing variability within the designs of N-of-1 trials in terms of a continuum where each design prioritizes epistemic and pragmatic considerations. We then support wider use of the designs located at the pragmatic end of the explanatory-pragmatic continuum.