In this study, we developed a control strategy for a drug product prepared by high-shear wet granulation and roller compaction using integrated quality by design (QbD). During the first and second stages, we optimized the process parameters through the design of experiments and identified the intermediate quality attributes (IQAs) and critical quality attributes (CQAs) relationship, respectively. In the first stage, we conducted an initial risk assessment by selecting critical process parameters with high impact on IQAs and CQAs and confirmed the correlation between control and response factors. Additionally, we performed Monte Carlo simulations by optimizing the process parameters to deriving and building a robust design space. In the second stage, we identified the IQAs and CQAs relationship for the control strategy, using multivariate analysis (MVA). Based on MVA, in the metformin layer, dissolution at 1 h was significantly correlated with intrinsic dissolution rate and granule size, and dissolution at 3 h was significantly correlated with bulk density and granule size. In dapagliflozin layer, dissolution at 10 min and 15 min was significantly correlated with granule size. Our results suggest that the desired drug quality may result through IQAs monitoring during the process and that the integrated QbD approach utilizing MVA can be used to develop a control strategy for producing high-quality drug products.

Although various quality by design (QbD) approaches have been used to establish a design space to obtain robust drug formulation and process parameters, the effect of excipient variability on the design space and drug product quality is unclear. In this study, the effect of microcrystalline cellulose (MCC) variability on drug product quality was examined using a design space for immediate-release tablets of amlodipine besylate. MCC variability was assessed by altering the manufacturer and grade. The formulation was developed by employing the QbD approach, which was optimized using a D-optimal mixture design. Using 36 different MCCs, the effect of MCC variability on the design space was assessed. The design space was shifted by different manufacturers and grades of MCC, which resulted in associations between the physicochemical properties of MCC and critical quality attributes (CQAs). The correlation between the physicochemical properties of MCCs and CQAs was assessed through a statistical analysis. A predictive model correlating the physicochemical properties of MCCs with dissolution was established using an artificial neural network (ANN). The ANN model accurately predicted dissolution with low absolute and relative errors. The present study described a comprehensive QbD approach, statistical analysis, and ANN to comprehend and manage the effect of excipient variability on the design space.

Control strategy and quality by design (QbD) are widely used to develop pharmaceutical products and improve drug quality; however, studies on fixed-dose combination (FDC) bilayer tablets are limited. In this study, the bilayer tablet consisted of high-dose metformin HCl in a sustained-release layer and low-dose dapagliflozin l-proline in an immediate-release layer. The formulation and process of each layer were optimized using the QbD approach. A d-optimal mixture design and response surface design were applied to optimize critical material attributes and critical process parameters, respectively. The robust design space was developed using Monte Carlo simulations by evaluating the risk of uncertainty in the model predictions. Multivariate analysis showed that there were significant correlations among impeller speed, massing time, granule bulk density, and dissolution in the metformin HCl layer, and among roller pressure, ribbon density, and dissolution in the dapagliflozin l-proline layer. Process analytical technology (PAT) was used with in-line transmittance near-infrared spectroscopy to confirm the bulk and ribbon densities of the optimized bilayer tablet. Moreover, the in vitro drug release and in vivo pharmacokinetic studies showed that the optimized test drug was bioequivalent to the reference drug. This study suggested that integrated QbD, statistical, and PAT approaches can develop a robust control strategy for FDC bilayer tablets by implementing real-time release testing based on the relationships among various variables.