From a regulatory standpoint, evaluating the consistency of drug quality requires consideration of the various manufacturing processes for the same product. This study proposes a strategy grounded in quality by design (QbD) for assessing pharmaceutical quality at the population level. Initially, a descriptive analysis framework based on QbD principles was established to define processes through critical evaluation attributes (CEAs). Subsequently, a quantitative analysis approach, employing an enhanced statistical process control (SPC) method, was developed to examine process indicators (PIs) across the population, including mean distribution, batch-to-batch variability, and the probability of quality deviations. Risk assessment criteria were then formulated based on the constraints and parameters of SPC. Both the SPC metrics for CEAs and the risk associated with PIs were visualized using interaction testing to provide a clearer insight into population-level pharmaceutical quality. Ultimately, this assessment strategy was applied to evaluate the consistency of generic drugs, assess process risks, and monitor quality trends. The findings indicate that this approach can illuminate quality consistency through the lens of process control and risk assessment, reflecting the current state of domestic pharmaceutical manufacturing. Moreover, process risk evaluation and population-level quality trend monitoring generate evidence-based information that supports regulatory decision-making, including early warning measures, while potentially reducing preventable adverse reactions. With ongoing data accumulation, dynamic tracking of pharmaceutical quality at the population level becomes a valuable tool for emergency response and informed regulatory decisions.
