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.

Context. This paper presents a method for solving the problem of product’s quality assurance at the stage of the initial manufacture process design in accordance with the process-analytical technology for the design of modern certified manufacturing – QbD. The method uses the information technologies of multivariate statistical analysis (MSA) to evaluate the influence of time multivariate critical process parameters (CPPs) on the time product critical quality attributes (CQAs). Preparatory transformation of clusters of critical process (manufacture process) parameters into factors of product critical quality attributes was carried out. Objective. To disclose the method of multivariate statistical analysis for assessing the character and features of the influence of time multivariate critical process parameters on time multivariate critical quality attributes at the design stage of the manufacture process. Method. The method consistently uses: statistical procedures of exploratory multivariate data analysis; transformation the homogeneous observed values matrices of CPPs and product CQAs into data frame (table) with factorized data; construction the regression trees of multivariate CPPs with a multivariate responses (CQAs). The method is implemented the R language packages software. Results. Factorized time multivariate CPPs make it possible to use methods of multivariate statistical analysis for evaluating the influence of CPPs factors on the time multivariate CQAs. Conclusions. This method of statistical analysis, together with statistical multivariate canonical analysis, represents an up-to-date information technology for detailed estimation the influence of time multivariate CPPs objects and some CPPs components on CQAs.

Chapter 28 - Design, Development, and Scale-Up of the High-Shear Wet Granulation Process

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.

Natural killer (NK) cells make only a small fraction of immune cells in the human body, however, play a pivotal role in the fight against cancer by the immune system. They are capable of eliminating abnormal cells via several direct or indirect cytotoxicity pathways in a self-regulating manner, which makes them a favorable choice as a cellular therapy against cancer. Additionally, allogeneic NK cells, unlike other lymphocytes, do not or only minimally cause graft-versus-host diseases opening the door for an off-the-shelf therapy. However, to date, the production of NK cells faces several difficulties, especially because the critical process parameters (CPPs) influencing the critical quality attributes (CQAs) are difficult to identify or correlate. There are numerous different cultivation platforms available, all with own characteristics, benefits and disadvantages that add further difficulty to define CPPs and relate them to CQAs. Our goal in this contribution was to summarize the current knowledge about NK cell expansion CPPs and CQAs, therefore we analyzed the available literature of both dynamic and static culture format experiments in a systematic manner. We present a list of the identified CQAs and CPPs and discuss the role of each CPP in the regulation of the CQAs. Furthermore, we could identify potential relationships between certain CPPs and CQAs. The findings based on this systematic literature research can be the foundation for meaningful experiments leading to better process understanding and eventually control.

High shear wet granulation: Improved understanding of the effects of process variables on granule and tablet properties of a high-dose, high-hydrophobicity API based on quality by design and multivariate analysis approaches

This paper presented a combinatorial application of quality by design (QbD) and quality risk management (QRM) tools with the goal of managing process risk and achieving high level of quality control during the development of the high shear wet granulation (HSWG) process. The microcrystalline cellulose and deionized water system was taken as the research object. By defining the critical quality attributes (CQAs) for the granules product, the probabilistic failure modes effects analysis (PFMEA) was innovatively used to assess the potential risks associated with the HSWG process on product quality and prioritize the potential critical process parameters (pCPPs) that must be controlled. Then, the Plackett-Burman design was used to screen critical process parameters (CPPs) from pCPPs. As a result, three operating parameters, i.e. the liquid to solid ratio, the wet massing time and the wet mixing impeller speed were identified as CPPs, and their quantitative relationship with CQAs were further investigated by using the Box-Behnken design. The design space which remained safely away from the edge of failure was built and validated. Retrospective risk analysis results demonstrated that the established process control strategies were efficient to ensure the granules consistently meet the specifications.

Implementation of a quality by design approach in the potato chips frying process

The aim of this study was to optimize the process of tablets compression and identification of film-coating critical process parameters (CPPs) affecting critical quality attributes (CQAs) using quality by design (QbD) approach. Design of experiment (DOE) and regression methods were employed to investigate hardness, disintegration time, and thickness of uncoated tablets depending on slugging and tableting compression force (CPPs). Plackett–Burman experimental design was applied to identify critical coating process parameters among selected ones that is: drying and preheating time, atomization air pressure, spray rate, air volume, inlet air temperature, and drum pressure that may influence the hardness and disintegration time of coated tablets. As a result of the research, design space was established to facilitate an in-depth understanding of existing relationship between CPPs and CQAs of intermediate product (uncoated tablets). Screening revealed that spray rate and inlet air temperature are two most important factors that affect the hardness of coated tablets. Simultaneously, none of the tested coating factors have influence on disintegration time. The observation was confirmed by conducting film coating of pilot size batches.

Objective Over the last few decades, there have been advancements in our comprehension of the design and development of topical semisolid formulations; however, they still follow an empirical development. Our study focuses on building a framework for designing and developing topical semisolid products using ‘Quality by Design’ (QbD) approach. Methods A literature review was conducted to identify and list the factors related to the design and development of topical semi-solid dosage forms using Quality by Design approach. The information extracted from the relevant articles was used to build a QbD framework based on four main pillars: Define the Quality Target Product Profile (QTPP); identify Critical Quality Attributes (CQAs); identify Critical Material Attributes (CMAs) and Critical Process Parameters (CPPs); understand how CMAs and CPPs affect CQAs and establish a control strategy. Results Some typical elements of the QTPP for topical products include dosage form, route of administration, shelf life, critical quality attributes of the final formulation. Critical material attributes such as characteristics of API (molecular weight, lipophilicity, solubility, metamorphosis events, and polymorphism), characteristics of excipients, and critical process parameters (temperature, heating and cooling rates, mixing speed, pumping speed, order of addition) are identified and explained for their impact on CQAs. Conclusions Proper characterization of the API and drug delivery system will increase the likelihood of developing a stable, pleasing, and tolerable topical formulation and minimize the risk of failure.

Investigation of the effects of materials and dry granulation process on the mirabegron tablet by integrated QbD approach with multivariate analysis

Objective: The objective of this study was to develop a polymeric composite of the poorly soluble antidepressant drug felodipine with help of PVP K-30 and PEG 6000, using a Quality by Design (QbD) approach to enhance its solubility and, consequently, its bioavailability. Methods: In this work, the quality target product profile (QTTP) was defined and Critical Quality Attributes (CQAs) were identified. Additionally, risk assessment analyses were carried out using the Ishikawa fishbone diagram to identify the Critical Material Attributes (CMAs) and/or Critical Process Parameters (CPPs) associated with the development of polymeric composite that could influence the Critical Quality Attributes (CQAs) of the drug product. The solubility of felodipine hydrochloride was improved by creating various polymeric composites with various concentrations of Poly Vinyl Pyrrolidone K30 (PVP-K 30) and Poly Ethylene Glycol 600 (PEG 600) by solvent evaporation method as Critical material attribute (CMA) as identified by risk assessment study and the and CQAs viz drug solubility, drug content and drug release. These composites were designed using a 32 Face Central composite Design (FCCD) with a face-centered approach implemented in Design Expert software. Results: After defining QTTP and CQA, risk assessment analysis was successfully used to identify CMA as well as CPPs. A total of thirteen PVP-PEG polymeric composites were developed and evaluated for FTIR spectra, Differential Scanning Colorimetry (DSC), X-Ray diffraction (XRD), and Scanning electron Microscopy (SEM). Data optimization was performed using response surface methodology, including contour and overlay plots. Solubility, drug content, and drug release of the optimized batch were found to be 21.55 mg/ml, 100%, and 78.314%, respectively. Three Validation Check batches (VC1-VC3) were developed and validated. Percent error for solubility ranges between-0.0019 to 0.0061, drug content ranges between 0.0005 to 0.0031 and solubility ranges between 0.0005 to 0.0011 that were very close to the predicted value, hence verifying the optimized data. Thus, by carefully using the QbD technique, the solubility of felodipine was enhanced by the effective development of a PVP-PEG polymeric composite. Conclusion: The QbD approach was to be an effective tool to develop an optimized polymeric composite of PVP 30K and PEG 6000 of felodipine with improved solubility without exhaustive research.

In this paper, a design space approach was applied to optimize the dropping process of Ginkgo biloba dropping pills. Firstly, potential critical process parameters and potential process critical quality attributes were determined through literature research and pre-experiments. Secondly, experiments were carried out according to Box-Behnken design. Then the critical process parameters and critical quality attributes were determined based on the experimental results. Thirdly, second-order polynomial models were used to describe the quantitative relationships between critical process parameters and critical quality attributes. Finally, a probability-based design space was calculated and verified. The verification results showed that efficient production of Ginkgo biloba dropping pills can be guaranteed by operating within the design space parameters. The recommended operation ranges for the critical dropping process parameters of Ginkgo biloba dropping pills were as follows: dropping distance of 5.5-6.7 cm, and dropping speed of 59-60 drops per minute, providing a reference for industrial production of Ginkgo biloba dropping pills.

In this paper, under the guidance of quality by design (QbD) concept, the control strategy of the high shear wet granulation process of the ginkgo leaf tablet based on the design space was established to improve the process controllability and product quality consistency. The median granule size (D50) and bulk density (Da) of granules were identified as critical quality attributes (CQAs) and potential critical process parameters (pCPPs) were determined by the failure modes and effect analysis (FMEA). The Plackeet-Burmann experimental design was used to screen pCPPs and the results demonstrated that the binder amount, the wet massing time and the wet mixing impeller speed were critical process parameters (CPPs). The design space of the high shear wet granulation process was developed within pCPPs range based on the Box-Behnken design and quadratic polynomial regression models. ANOVA analysis showed that the P-values of model were less than 0.05 and the values of lack of fit test were more than 0.1, indicating that the relationship between CQAs and CPPs could be well described by the mathematical models. D₅₀ could be controlled within 170 to 500 μm, and the bulk density could be controlled within 0.30 to 0.44 g•cm⁻³ by using any CPPs combination within the scope of design space. Besides, granules produced by process parameters within the design space region could also meet the requirement of tensile strength of the ginkgo leaf tablet..

The traditional drug manufacturing process involves numerous qualitative attributes that directly impact product quality. The Process Analytical Technology approach considers that to enhance process control, identifying critical process parameters and critical quality attributes that affect the manufacturing process is very much necessary. The Ayurvedic drug manufacturing process is more driven by fuzzy qualitative attributes. The present study was executed to identify the Critical Process Parameters and Critical Quality Attributes in the manufacturing process of a herbo-mineral formulation, viz. Arogyavardhini Rasa. Fuzzy set Qualitative Comparative Analysis (fsQCA) methodology was adopted to observe and identify the critical parameters. The study was executed in three steps, viz. Data collection, Data arrangement, and Analysis. The raw data collected was arranged and analyzed in the software R studio using the package QCA in four steps, viz. Calibration, Analysis of Necessity and Sufficiency, Truth Table construction, and Minimization. The results obtained show that Size reduction, Mardana, and Drying are the identified Critical Process Parameters that, in combination, lead to the outcome, i.e., good product quality. Thus, this study proves that Fuzzy Set Qualitative Comparative Analysis can be used as an efficient tool for the identification and measurement of the Critical Process Parameters that affect the Critical Quality Attributes and, thereby, the product quality in the manufacturing of Arogyavardhini Rasa.

The pharmaceutical industry continues to face challenges in the seamless manufacturing of ibuprofen tablets, despite decades of commercial production. Key issues include the drug’s inherent properties—such as its low melting point (70°C), which causes sticking during compression—as well as solubility and in vitro release challenges due to its BCS Class II classification. Additionally, modifying API properties and approved formulations involves significant regulatory and cost constraints under SUPAC Level 2 changes. While Quality by Design (QbD) approaches have primarily focused on Critical Material Attributes (CMAs) and formulation-based Design of Experiments (DOE), understanding the impact of process variability on Critical Process Parameters (CPPs) remains crucial for ensuring consistent product quality. The integration of Artificial Intelligence and Machine Learning (AIML) in Pharma 4.0 offers transformative potential by enabling predictive analytics, real-time monitoring, and automated decision-making for CPP optimization. Key benefits include precise process control, predictive deviation management, and continuous improvement through data-driven insights. A structured approach involving statistical analysis, machine learning, and process rationalization is essential to minimize variability and align with quality attributes. By leveraging AIML, pharmaceutical manufacturers can enhance efficiency, reduce downtime, and ensure consistent production of high-quality ibuprofen tablets, paving the way for advanced, data-driven pharmaceutical manufacturing. Objective: Identify the optimal Critical Process Parameters (CPPs) for the manufacture of ibuprofen tablets (600mg). Determine the point of control within the specification and control limits to ensure process capability and reliability. Methods: PubMed and Embase databases have been searched, and related studies are compiled and summarized. Results: A designed experiment evaluated critical process parameters (CPPs)—granulation time (3–12 min), drying temperature (45–60°C), compaction force (6–18 kN), and compression speed (10–25 RPM) on tablet quality. Physical, disintegration, and dissolution tests were conducted. Statistical analysis (Jupiter Notebook) revealed correlations between CPPs and critical quality attributes (CQAs), particularly disintegration time (DT) and dissolution %. Conclusion: This study established key correlations between critical process parameters (CPPs) and quality attributes: compression speed/force and granulation/drying times significantly affect disintegration time (DT), while DT shows an inverse relationship with dissolution%. Regression analysis revealed limitations in predictive modeling, emphasizing the need for comprehensive CPP evaluation combined with physical testing. The identified CPP control ranges (9 min granulation, 50°C drying, 14 kN compaction, 16 RPM speed) enable targeted optimization of DT and dissolution%, ensuring therapeutic efficacy. These findings provide a science-based framework for quality-by-design in tablet manufacturing, though continued validation through physical testing remains essential for robust quality assurance.