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. 2021 Sep 10;13(9):1443.
doi: 10.3390/pharmaceutics13091443.

Development of a Robust Control Strategy for Fixed-Dose Combination Bilayer Tablets with Integrated Quality by Design, Statistical, and Process Analytical Technology Approach

Myung-Hee Chun  1 , Ji Yeon Kim  2 , Eun-Seok Park  1 , Du Hyung Choi  2
Affiliations

Development of a Robust Control Strategy for Fixed-Dose Combination Bilayer Tablets with Integrated Quality by Design, Statistical, and Process Analytical Technology Approach

Myung-Hee Chun et al. Pharmaceutics. .

Abstract

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.

Keywords: control strategy; fixed-dose combination drug; manufacturing process; multivariate analysis; process analytical technology; quality by design.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Robust design space of formulation development for metformin HCl layer with an optimal setting. Since the design space explorer function of the mixture design does not appear as a triangular area, the design space function of MODDE was used, and the optimal setting was displayed on the basis of the analysis result.
Figure 2
Figure 2
Robust design space of high-shear wet granulation process for metformin HCl layer with an optimal setting. The massing time was fixed at 2.305 min.
Figure 3
Figure 3
Robust design space of formulation development for dapagliflozin l-proline layer with an optimal setting. Since the design space explorer function of the mixture design did not appear as a triangular area, the design space function of MODDE was used, and the optimal setting was displayed on the basis of the analysis result.
Figure 4
Figure 4
Robust design space of roller compaction process development for dapagliflozin l-proline layer with an optimal setting. The roller gap was fixed at 1.6 mm.
Figure 5
Figure 5
Result of MVA for metformin HCl layer formulation development: (a) loading plot with PC1 and PC2; (b) Pearson correlation coefficient. The blue lines and yellow boxes indicate the variables having a high correlation with dissolution. SWP, tablet swelling property; W.G., tablet weight gain; M.L., tablet mass loss; Gel, tablet gel strength; Diss, dissolution; Contact, tablet contact angle; IDR, intrinsic dissolution rate; Carr’s, Carr’s index; G.S, granule strength; AOR, angle of repose; True, true density; Bulk, bulk density.
Figure 6
Figure 6
Result of MVA for metformin HCl layer process development: (a) loading plot with PC1 and PC2; (b) Pearson correlation coefficient. The blue lines and yellow boxes indicate the variables having a high correlation with dissolution. Impeller, impeller speed; Massing, massing time; Binder, binder solvent amount; SWP, swelling property; W.G., weight gain; M.L., mass loss; Gel., gel strength; Diss., dissolution; Contact, contact angle; IDR, intrinsic dissolution rate; Carr’s, Carr’s index; G.S., granule strength; AOR, angle of repose; True, true density; Bulk, bulk density.
Figure 7
Figure 7
Result of MVA for dapagliflozin l-proline layer formulation development: (a) loading plot with PC1 and PC2; (b) Pearson correlation coefficient. The blue lines and yellow boxes indicate the variables having a high correlation with dissolution. IDR, intrinsic dissolution rate; AOR, angle of repose; Bulk, bulk density; G.S., granule strength; C.U., content uniformity; Diss., dissolution; Contact, contact angle; Ribbon, ribbon density; Tapped, tapped density.
Figure 8
Figure 8
Result of MVA for dapagliflozin l-proline layer process development: (a) loading plot with PC1 and PC2; (b) Pearson correlation coefficient. The blue lines and yellow boxes indicate the variables having a high correlation with dissolution. IDR, intrinsic dissolution rate; AOR, angle of repose; Bulk, bulk density; G.S., granule strength; C.U., content uniformity; Diss., dissolution; Contact, contact angle; Ribbon, ribbon density; Tapped, tapped density.
Figure 9
Figure 9
PLS calibration model for metformin HCl bulk density: (a) raw spectra; (b) preprocessed spectra with SNV; (c) calibration model curve. The black dotted line indicates the 95% confidence interval (CI) range.
Figure 10
Figure 10
Granule bulk density in scaled-up high-shear wet granulation process monitored by NIR.
Figure 11
Figure 11
PLS calibration model for dapagliflozin l-proline ribbon density: (a) raw spectra; (b) preprocessed spectra with SNV; (c) calibration model curve. The black dotted line indicates the 95% confidence interval (CI) range.
Figure 12
Figure 12
Ribbon density for scaled-up roller compaction process monitored by NIR.
Figure 13
Figure 13
In vitro dissolution profile of an optimal bilayer drug compares with the reference drug: (a) metformin HCl layer; (b) dapagliflozin l-proline layer.
Figure 14
Figure 14
Mean plasma concentration–time profiles obtained after oral administrations of reference and test formulations to healthy volunteers (n = 32): (a) metformin HCl; (b) dapagliflozin l-proline.
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