Use of measurement uncertainty in conformity assessment and process capability indices in quality evaluation of pharmaceutical manufacturing processes

Abstract

The pharmaceutical industry operates under strict regulatory standards to ensure high-quality, safe, and effective products. Several key indices and metrics are employed to ensure that the pharmaceutical industry operates according to these standards, with process capability indices ($Cp$ and $Cpk$) being the most widely utilized. Regular monitoring and analysis of this metric helps organizations maintain compliance, improve processes, and ultimately safeguard public health. Since the traditional conformity assessment approach (i.e., the simple acceptance rule) does not explicitly consider measurement uncertainty, this study proposes measurement capability indices, $Cm$ and $Cmk$ analogous to the process capability indices $Cp$ and $Cpk$, but based on the measurement uncertainty. The $Cmk$ index was applied to evaluate the conformity of 750 mg paracetamol tablets. The results indicated that while 99.9 % of the reference drug product lots were compliant, only 68.02 % of the generic drug product lots met these specifications. Furthermore, Monte Carlo simulations estimated a consumer risk of 4.76 % for accepting non-compliant lots and a producer risk of 6.82 % for incorrectly rejecting compliant lots. By combining $Cmk$ and $Cpk$ strengthens quality control by enabling more conservative acceptance limits and providing a robust statistical basis for conformity decisions, thereby minimizing the risk of erroneous lot acceptance or rejection. This approach reduces risks for consumers and producers, enhances reliability in pharmaceutical production, and provides a precise tool to ensure product quality and safety.