Justification of Sample Size

Justification of Sample Size refers to the statistical rationale determining how many subjects or samples are needed to achieve reliable study conclusions. This justification considers expected effect size, variability, significance level, and desired statistical power. Sample size planning ensures studies can detect meaningful differences while minimising unnecessary exposure of participants and efficient use of resources.

The biopharmaceutical industry applies sample size justification across preclinical studies, clinical trials, and analytical validation programmes. Underpowered studies risk false negatives leading to erroneous conclusions about therapeutic potential, while excessively large studies may be unethical or wasteful. Regulatory submissions require clear sample size rationale supporting trial design credibility and demonstrating adequate statistical power. Adaptive designs may adjust sample size based on interim results under predefined rules, enabling more efficient development. As Bayesian and simulation-based approaches complement traditional power calculations, and as complex adaptive trial designs become more common, robust sample size justification remains essential for scientific and regulatory confidence in study outcomes.