(W0930-08-50) Formulation Process Development of a Novel Combination Analgesic Based on Risk Assessment (RA) and Design of Experiments (DoE)

Purpose: The combination tablet of pelubiprofen and tramadol is a novel combination analgesic containing an ionic compound of pelubiprofen, a nonsteroidal anti-inflammatory drug (NSAID), and tramadol, an opioid analgesic, which is currently undergoing clinical trials. This study aimed to characterize the manufacturing process using a Quality by Design (QbD) approach. A response surface methodology (RSM) was applied to the granulation step, which involved one or more critical process parameters (CPPs) requiring multivariate experimentation. The objective was to evaluate the effects of key variables, define the design space, and establish a Proven Acceptable Range (PAR) suitable for practical implementation.

Methods: A risk analysis tool, Risk Ranking and Filtering (RRF), was used to evaluate process variables across each unit operation of the manufacturing process. Based on high risk level—assessed by impact and uncertainty—the granulation step, which included key process variables, was selected for further DoE analysis. A lab-scale granulation model, qualified via scale-down modeling, was employed to reflect actual production conditions. Agitator speed (X1), chopper speed (X2), and granulation time (X3) were chosen as input variables. Output variables included flowability indicators such as Carr’s Index (Y1) and Flow Function (Y2), as well as dissolution rates (Y3–Y6). A Central Composite Face-Centered (CCF) design was used, incorporating six center points and a total of 20 experimental runs. Statistically significant responses were analyzed using surface profiler and contour plots to define the design space and establish a Proven Acceptable Range (PAR) for practical application.

Results: Initial risk assessment using the RRF method confirmed the granulation step as a multivariate process requiring optimization. The identified CPPs were agitator speed, chopper speed, and granulation time. DoE analysis showed that Carr’s Index (Y1) and Flow Function (Y2) were significantly influenced by input variables. Y1 ranged from 12.5 % to 25.2%, and Y2 from 4.1 to 9.8, with multiple conditions meeting the target criteria (CI ≤ 20%, FF ≥ 4). The derived design space supported a practical PAR of X1 (230–430 rpm), X2 (1,400–2,400 rpm), and X3 (4–10 min). The formulation study condition (X1 = 350 rpm, X2 = 2,000 rpm, X3 = 6 min) was confirmed to fall within the established PAR.

Conclusion: This study confirmed the CPPs of the granulation process through risk assessment and quantified the effects of input variables on key response parameters via DoE. Based on the derived PAR, a Normal Operating Range (NOR) will be established, and a control strategy will be developed for commercial production to ensure consistent product quality.

References: [1] ICH Q8(R2) Pharmaceutical Development
[2] ICH Q9 Quality Risk Management
[3] A-mAb: A Case Study in Bioprocess Development, v2.1, CMC Biotech Working Group

Acknowledgements: This work was supported by the Daewon pharmaceutical Co., Ltd (Republic of Korea)