Changes to the initial sample size required to address research questions are made based on accrued information in response to incorrect assumptions or guesses made at the planning stage about study design parameters. Sample size can be increased or reduced accordingly.

Offers opportunities to stop the trial early as soon as there is sufficient evidence to make reliable conclusions about the effects of a treatment by analysing accumulating data at interim analyses. Researches can stop a trial early because they found enough evidence of benefit or lack of benefit. The criteria for early stopping are pre-specified.

Several competing treatments are evaluated simultaneously. Based on accrued outcome data, treatment arms showing promising benefit are chosen for further testing, those unlikely to show benefit are dropped, or trial stopped early for benefit. The criteria for selecting/dropping arms or early stopping at interim analyses are pre-specified.

Researchers can evaluate whether treatments benefit heterogeneous target patients or only patients with specific characteristics (subpopulations) in a single trial . Using predefined selection rules, subpopulations showing promising benefits are selected at interim analyses and eligibility modified to focus recruitment to selected subpopulations.

Offers researchers opportunities to change how patients are allocated to treatments based on some pre-specified rules capturing the emerging signals of treatment benefits. More patients can be allocated to treatments that are indicating more benefits away from those that are less efficacious or unsafe.