The parallel-group design is the most common clinical trial architecture, in which participants are randomized to receive a single treatment for the duration of their participation while other groups concurrently receive alternative treatments or placebo. Each participant contributes data to only one treatment group, and comparisons are made between the groups rather than within individual participants. This straightforward design is applicable to virtually any therapeutic context and can accommodate any number of treatment arms.

The primary advantage of parallel designs lies in their broad applicability. Unlike crossover studies, parallel trials do not require that participants return to baseline between treatments, making them suitable for diseases that progress, for treatments with lasting effects, and for acute conditions. They avoid the complications of carryover effects and do not require extended study duration to accommodate multiple treatment periods. The design is conceptually simple and well-understood by regulators, clinicians, and statisticians.

The parallel design does require larger sample sizes compared to crossover studies because between-subject variability contributes to the overall variance in treatment comparisons. This limitation can be partially addressed through stratified randomization, which ensures balance on key prognostic factors, or through covariate adjustment in the analysis. The design is also susceptible to differential dropout if participants in one treatment group discontinue at higher rates, potentially introducing bias. Nevertheless, the parallel design remains the workhorse of clinical development, suitable for most Phase II and Phase III trials across therapeutic areas.