Continuous high-shear granulation: Mechanistic understanding of the influence of process parameters on critical quality attributes via elucidating the internal physical and chemical microstructure

2019 ◽  
Vol 30 (9) ◽  
pp. 1765-1781 ◽  
Author(s):  
Wei Meng ◽  
Jakub Dvořák ◽  
Ravish Kumar ◽  
Rudy Hofmeister ◽  
František Štěpánek ◽  
...  
Keyword(s):  
Process Parameters ◽  
Quality Attributes ◽  
High Shear ◽  
Influence Of Process Parameters ◽  
Critical Quality Attributes ◽  
Mechanistic Understanding ◽  
Physical And Chemical

scholarly journals Comprehensive Study of Intermediate and Critical Quality Attributes for Process Control of High-Shear Wet Granulation Using Multivariate Analysis and the Quality by Design Approach

Pharmaceutics ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 252 ◽  
Author(s):  
Jong Kwon Han ◽  
Beom Soo Shin ◽  
Du Hyung Choi
Keyword(s):  
Multivariate Analysis ◽  
Process Parameters ◽  
Scale Up ◽  
Pilot Scale ◽  
Quality Attributes ◽  
Wet Granulation ◽  
High Shear ◽  
Critical Quality Attributes ◽  
High Shear Wet Granulation ◽  
The Relationship

A robust manufacturing process and the relationship between intermediate quality attributes (IQAs), critical quality attributes (CQAs), and critical process parameters (CPPs) for high-shear wet granulation was determined in this study. Based on quality by the design (QbD) approach, IQAs, CQAs, and CPPs of a telmisartan tablet prepared by high-shear wet granulation were determined and then analyzed with multivariate analysis (MVA) to evaluate mutual interactions between IQAs, CQAs, and CPPs. The effects of the CPPs on the IQAs and CQAs were quantitatively predicted with empirical models of best fit. The models were used to define operating space, and an evaluation of the risk of uncertainty in model prediction was performed using Monte Carlo simulation. MVA showed that granule size and granule hardness were significantly related to % dissolution. In addition, granule FE (Flow Energy) and Carr’s index had effects on tablet tensile strength. Using the manufacture of a clinical batch and robustness testing, a scale-up from lab to pilot scale was performed using geometric similarity, agitator torque profile, and agitator tip speed. The absolute biases and relative bias percentages of the IQAs and CQAs generated by the lab and pilot scale process exhibited small differences. Therefore, the results suggest that a risk reduction in the manufacturing process can be obtained with integrated process parameters as a result of the QbD approach, and the relationship between IQAs, CQAs, and CPPs can be used to predict CQAs for a control strategy and SUPAC (Scale-Up and Post-Approval Guidance).

scholarly journals Design Space Approach in Optimization of Fluid Bed Granulation and Tablets Compression Process

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Jelena Djuriš ◽  
Djordje Medarević ◽  
Marko Krstić ◽  
Ivana Vasiljević ◽  
Ivana Mašić ◽  
...  
Keyword(s):  
Process Parameters ◽  
Design Space ◽  
Quality Attributes ◽  
Dissolution Profile ◽  
Compression Force ◽  
Critical Quality Attributes ◽  
Fluid Bed ◽  
Fluid Bed Granulation ◽  
Atomization Pressure ◽  
Space Approach

The aim of this study was to optimize fluid bed granulation and tablets compression processes using design space approach. Type of diluent, binder concentration, temperature during mixing, granulation and drying, spray rate, and atomization pressure were recognized as critical formulation and process parameters. They were varied in the first set of experiments in order to estimate their influences on critical quality attributes, that is, granules characteristics (size distribution, flowability, bulk density, tapped density, Carr's index, Hausner's ratio, and moisture content) using Plackett-Burman experimental design. Type of diluent and atomization pressure were selected as the most important parameters. In the second set of experiments, design space for process parameters (atomization pressure and compression force) and its influence on tablets characteristics was developed. Percent of paracetamol released and tablets hardness were determined as critical quality attributes. Artificial neural networks (ANNs) were applied in order to determine design space. ANNs models showed that atomization pressure influences mostly on the dissolution profile, whereas compression force affects mainly the tablets hardness. Based on the obtained ANNs models, it is possible to predict tablet hardness and paracetamol release profile for any combination of analyzed factors.

Revisiting MSC expansion from critical quality attributes to critical culture process parameters

2017 ◽  
Vol 59 ◽  
pp. 231-243 ◽  
Author(s):  
Céline Martin ◽  
Éric Olmos ◽  
Marie-Laure Collignon ◽  
Natalia De Isla ◽  
Fabrice Blanchard ◽  
...  
Keyword(s):  
Process Parameters ◽  
Quality Attributes ◽  
Critical Quality Attributes ◽  
Culture Process

Mechanistic basis for the effects of process parameters on quality attributes in high shear wet granulation

2012 ◽  
Vol 439 (1-2) ◽  
pp. 324-333 ◽  
Author(s):  
Sherif I.F. Badawy ◽  
Ajit S. Narang ◽  
Keirnan LaMarche ◽  
Ganeshkumar Subramanian ◽  
Sailesh A. Varia
Keyword(s):  
Process Parameters ◽  
Quality Attributes ◽  
Wet Granulation ◽  
High Shear ◽  
Mechanistic Basis ◽  
High Shear Wet Granulation

scholarly journals Systematic Study of the Effects of High Shear Granulation Parameters on Process Yield, Granule Size, and Shape by Dynamic Image Analysis

Pharmaceutics ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1894
Author(s):  
Oliver Macho ◽  
Ľudmila Gabrišová ◽  
Peter Peciar ◽  
Martin Juriga ◽  
Róbert Kubinec ◽  
...  
Keyword(s):  
Image Analysis ◽  
Process Parameters ◽  
Impeller Speed ◽  
Equivalent Diameter ◽  
High Shear ◽  
Influence Of Process Parameters ◽  
Process Yield ◽  
Shape Factors ◽  
Dynamic Image ◽  
Dynamic Image Analysis

The aim of the work was to analyze the influence of process parameters of high shear granulation on the process yield and on the morphology of granules on the basis of dynamic image analysis. The amount of added granulation liquid had a significant effect on all monitored granulometric parameters and caused significant changes in the yield of the process. In regard of the shape, the most spherical granules with the smoothest surface were formed at a liquid to solid ratio of ≈1. The smallest granules were formed at an impeller speed of 700 rpm, but the granules formed at 500 rpm showed both the most desirable shape and the highest process yield. Variation in the shape factors relied not only on the process parameters, but also on the area equivalent diameter of the individual granules in the batch. A linear relationship was found between the amount of granulation liquid and the compressibility of the granules. Using response surface methodology, models for predicting the size of granules and process yield related to the amount of added liquid and the impeller speed were generated, on the basis of which the size of granules and yield can be determined with great accuracy.

scholarly journals Control Strategy for Process Development of High-Shear Wet Granulation and Roller Compaction to Prepare a Combination Drug Using Integrated Quality by Design

Pharmaceutics ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 80
Author(s):  
Ji Yeon Kim ◽  
Myung Hee Chun ◽  
Du Hyung Choi
Keyword(s):  
Process Parameters ◽  
Control Strategy ◽  
Quality By Design ◽  
Quality Attributes ◽  
Granule Size ◽  
Wet Granulation ◽  
Roller Compaction ◽  
High Shear ◽  
Intrinsic Dissolution ◽  
High Shear Wet Granulation

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.

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