Quality-by-Design Concepts to Improve Nanotechnology-Based Drug Development.

A cross-industry forum on benchmarking critical quality attribute identification and linkage to process characterization studies

Optimization of the quality by design approach for gene therapy products: A case study for adeno-associated viral vectors

The quality of traditional Chinese medicine(TCM) is a critical foundation for ensuring the stability of its efficacy, as well as the safety and effectiveness of its clinical use. The identification of critical quality attributes(CQAs) is one of the core components of TCM preparation quality control. This study focuses on Jianwei Xiaoshi Tablets and explores their CQAs related to property and flavor from the perspective of taste receptor proteins. Three taste receptor proteins, T1R2, T1R3, and TRPV1, were selected, and a biosensor based on high-electron-mobility transistor(HEMT) was constructed to detect the interactions between Jianwei Xiaoshi Tablets and taste receptor proteins. Simultaneously, liquid chromatography-mass spectrometry(LC-MS) technology was used to analyze the chemical composition of Jianwei Xiaoshi Tablets. In examining the interaction strength, the results indicated that the interaction between Jianwei Xiaoshi Tablets and TRPV1 protein was the strongest, followed by T1R3, with the interaction with T1R2 being relatively weaker. By combining biosensing technology with LC-MS, 16 chemical components were identified from Jianwei Xiaoshi Tablets, among which six were selected as CQAs for sweetness and seven for pungency. Further validation experiments demonstrated that CQAs such as hesperidin and hesperetin had strong interactions with their corresponding taste receptor proteins. Through the combined use of multiple technological approaches, this study successfully determined the property and flavor-related CQAs of Jianwei Xiaoshi Tablets. It provides novel ideas and approach for the identification of CQAs in TCM preparations and offers comprehensive theoretical support for TCM quality control, contributing to the improvement and development of TCM preparation quality control systems.

A quality by design approach to investigate the effect of mannitol and dicalcium phosphate qualities on roll compaction

BackgroundAnalytical Quality by Design (AQbD) has emerged as a pivotal paradigm in the realm of analytical chemistry, revolutionizing the approach to method development and validation. This innovative strategy integrates principles of Quality by Design (QbD) into analytical procedures, aiming to ensure the quality and robustness of analytical methods. The traditional approach to method development often involves a trial-and-error process, where parameters are adjusted until satisfactory results are obtained. However, this approach can be time-consuming, resource-intensive, and may lack reproducibility. AQbD addresses these challenges by providing a systematic framework for method development that emphasizes understanding the relationship between critical process parameters (CPPs) and critical quality attributes (CQAs).DiscussionAnalytical Quality by design (AQbD) presents an innovative approach to creating and validating analytical procedures, aimed at achieving quality measurements within the method operable design region (MODR). The QbD approach to analytical development is proactive, methodical, and risk-based significantly helps in acquiring an in-depth knowledge of how critical process parameters (CPPs) affect analytical performances, measured by critical quality attributes (CQAs). Experiment design (DoE) is an essential part of QbD, functioning to carry out the response surface analysis and screening process, and ultimately to enable the definition of the multidimensional region of the successful operating ranges of the CPPs, known as the design space (DS). The purpose of this article is to offer a thorough description of the QbD approach's method development process and its implementation in analytical procedure validation, to produce high-quality output, employing statistical analysis in conjunction with other designing tools.ConclusionAnalytical Quality by design (AQbD) offers a systematic and proactive approach to method development in analytical procedures. By focusing on method resilience and incorporating statistical analysis and experiment design (DoE), AQbD enables the production of high-quality outputs, while minimizing out of trend (OOT) and out of specification (OOS) results. This innovative strategy enhances the reliability and reproducibility of analytical methods, ultimately leading to improved outcomes across various industries.

Background/Objectives: Quality by Design (QbD) has revolutionized pharmaceutical development by transitioning from reactive quality testing to proactive, science-driven methodologies. Rooted in ICH Q8-Q11 guidelines, QbD emphasizes defining Critical Quality Attributes (CQAs), establishing design spaces, and integrating risk management to enhance product robustness and regulatory flexibility. This review critically examines QbD's theoretical frameworks, implementation workflows, and industrial applications, aiming to bridge academic research and commercial practices while addressing emerging challenges in biologics, advanced therapies, and personalized medicine. Methods: The review synthesizes regulatory guidelines, case studies, and multidisciplinary tools, including Design of Experiments (DoE), Failure Mode Effects Analysis (FMEA), Process Analytical Technology (PAT), and multivariate modeling. It evaluates QbD workflows-from Quality Target Product Profile (QTPP) definition to control strategies-and explores advanced technologies like AI-driven predictive modeling, digital twins, and continuous manufacturing. Results: QbD implementation reduces batch failures by 40%, optimizes dissolution profiles, and enhances process robustness through real-time monitoring (PAT) and adaptive control. However, technical barriers, such as nonlinear parameter interactions in complex systems, and regulatory disparities between agencies hinder broader adoption. Conclusions: QbD significantly advances pharmaceutical quality and efficiency, yet requires harmonized regulatory standards, lifecycle validation protocols, and cultural shifts toward interdisciplinary collaboration. Emerging trends, including AI-integrated design space exploration and 3D-printed personalized medicines, promise to address scalability and patient-centric needs. By fostering innovation and compliance, QbD remains pivotal in achieving sustainable, patient-focused drug development.

The Impact of Product and Process Related Critical Quality Attributes on Immunogenicity and Adverse Immunological Effects of Biotherapeutics.

Quality by design (QbD) is an essential part of the modern advance to pharmaceutical quality. QbD is best key to build a quality in all pharmaceutical products. Under this concepts of be throughout design and growth of product, it is important to identify desire product performance report [Target product profile (TPP), Quality Target product profile (QTPP)] and identify critical quality attributes (CQA). To recognize the impact of raw material [critical material attributes (CAM)], critical process parameters (CPP) on the CQAs and identification and control sources of changeability. The plan of pharmaceutical development is to design a quality products and its manufacturing process always deliver the future performance of the product. The base of Quality by design is ICH Guidelines Q8 for Pharmaceutical for development, Q9 quality risk management, Q10 for pharmaceutical quality systems.

Quality by design (QbD) refers to a new approach to product development that could increase efficiencies, provide regulatory relief and flexibility, and offer important business benefits throughout the product life cycle. QbD is increasingly becoming an important and widely used technique in the pharmaceutical industry. QbD can be considered to be system-based approach to the design, development, and delivery of any product or service to a consumer. It is an approach to pharmaceutical development that begins with predefined objectives and emphasizes product and process understanding and process control. Process parameters and quality attributes are identified for each unit operation. Benefits, opportunities, and steps involved in QbD of pharmaceutical products are described. The aim of pharmaceutical development is to design a quality product and its manufacturing process to consistently deliver the intended performance of the product. Quality cannot be tested into products, but quality should be built in by design. It includes the quality target product profile, critical quality attributes, and key aspects of QbD. It also gives comparison between product quality by end product testing and product quality by QbD. The foundation of QbD is ICH guidelines. Hence, if we identify the cause and effect relationship between the various inputs and responses by carefully designed experiments, we can control the quality of the product by simply controlling the inputs such as raw material specifications or process parameters.

The integration of artificial intelligence (AI) into QbD frameworks has further revolutionized this process, enabling enhanced efficiency, precision, and innovation in formulation development. This review explores the role of AI in advancing QbD for pharmaceutical formulations, highlighting its applications, benefits, challenges, and future potential. By analyzing recent advancements, Our goal is to present a thorough grasp of how AI-driven QbD is influencing medication development going forward. Quality by Design (QbD) frameworks that incorporate artificial intelligence (AI) offer a revolutionary method for developing pharmaceutical formulations..This review explores how AI-driven tools enhance the QbD process by optimizing formulation design, predicting critical quality attributes (CQAs), and streamlining risk assessment. By utilizing machine learning models, AI enables accurate determination of essential material characteristics (EMCs) and vital process parameters (VPPs), reducing experimental trial-and-error. The abstract highlights case studies where AI has improved formulation stability, bioavailability, and manufacturing efficiency. Furthermore, it discusses the potential of AI to integrate real-time data analytics for continuous process verification, ensuring robust quality control. The authors emphasize that AI-augmented QbD accelerates development timelines.

To formulate and optimize Ozenoxacin nano-emulsion using Quality by Design (QbD) concept by means of Box-Behnken Design (BBD) and converting it to a gel to form Ozenoxacin nano-emulgel followed by physico-chemical, in-vitro, ex-vivo and in-vivo evaluation. This study demonstrates the application of QbD methodology for the development and optimization of an effective topical nanoemulgel formulation for the treatment of Impetigo focusing on the selection of appropriate excipients, optimization of formulation and process variables, and characterization of critical quality attributes. BBD was used to study the effect of "% of oil, % of Smix and homogenization speed" on critical quality attributes "globule size and % entrapment efficiency" for the optimisation of Ozenoxacin Nano-emulsion. Ozenoxacin loaded nano-emulgel was characterized for "description, identification, pH, specific gravity, amplitude sweep, viscosity, assay, organic impurities, antimicrobial effectiveness testing, in-vitro release testing, ex-vivo permeation testing, skin retention and in-vivo anti-bacterial activity". In-vitro release and ex-vivo permeation, skin retention and in-vivo anti-bacterial activity were found to be significantly (p < 0.01) higher for the nano-emulgel formulation compared to the innovator formulation (OZANEX™). Antimicrobial effectiveness testing was performed and found that even at 70% label claim of benzoic acid is effective to inhibit microbial growth in the drug product. The systematic application of QbD principles facilitated the successful development and optimization of a Ozenoxacin Nano-Emulsion. Optimised Ozenoxacin Nano-Emulgel can be considered as an effective alternative and found to be stable at least for 6months at 40°C / 75% RH and 30°C / 75% RH.

Integrated Application of Quality-by-Design Principles to Drug Product Development: A Case Study of Brivanib Alaninate Film–Coated Tablets

This paper gives idea about the Pharmaceutical Quality by Design (QbD) and describes use of Quality by Design to ensure quality of Pharmaceuticals. Quality cannot be tested into products but quality should be built in by design. The concept of QbD can be extended to analytical methods. The emphasis of AQbD approach is on understanding of the operation and the variables affecting Analytical Methods employed in product development. The variables which affect the output are identified and subjected to thorough risk assessment employing various tools and techniques discussed in the article, after which the variables are optimized. The final method is validated and a control strategy is put in place. Pharmaceutical firms increased the number of product development by using scientific tools such as QbD (Quality by Design). ICH Q11 guidelines clearly discussed QbD approach for API synthesis with examples. It is a current trend among pharmaceutical industry to implement analytical quality by design (AQbD) in method development process as a part of risk management, pharmaceutical development, and pharmaceutical quality system (ICH Q10). QbD has its perspectives to contribute the drug design, development, and manufacture of high-quality drug products.

Aim. To determine the potential risk factors associated with the critical quality indicators of the combined medicine “Neuronucleos” in the capsule dosage form for the treatment of polyneuropathies using the general risk assessment methodology while planning the drug quality at the stage of pharmaceutical development (PD). Materials and methods. The series of the combined medicine “Neuronucleos” in the capsule dosage form, critical indicators of the drug quality, the flowchart of the drug production, critical control points of the drug manufacturing process were developed. The method of causality was used. The quantitative assessment of risk factors was carriedout using the FMECA methodology. Results and discussion. The main objective of this study was to apply the Quality-by-Design (QbD) approach to PD of the combined medicine in the capsule dosage form based on uridine-5 monophosphate disodium salt (UMP), cytidine-5-monophosphate disodium salt (CMF), vitamin B6, thioctic acid and magnesium lactate dihydrate. For better patient compliance and the product quality, a target quality profile as a base for PD planning, as well as critical quality attributes (CQA) related to the product safety and efficacy were determined. The criticality of each CQA was assessed using a special scale. It was shown that “Quantitative content”, “Uniformity of dosage units”, “Dissolution”, “Impurities” were defined as the most CQA due to the minimum amount of UMF and CMF in the capsule and the possibility of their decomposition and increase in the quantity of impurities. The critical attributes of materials (CMA) were identified, and the characteristics required to control them were determined in order to ensure the expected product quality. The primary assessment of the quality indicator risks of the active ingredients was performed. It was found that the particle size affected the homogeneity, the quantitative content of API and dissolution in FPP, and it was shown that the solubility of active substances had a high risk when performing the “Dissolution” test. To determine the potential factors with a significant impact on the drug quality the maximum number of factors was found, and the Ishikawa diagram was constructed. The risk factors associated with the quality and compatibility of active substances and excipients, the quality of primary packaging, production conditions, the drug quality control and the technological process were identified. These factors are the causes of risk and can lead to a situation with negative consequences for the quality of a medicinal product. The FMECA process assessment allowed us to determine the impact of the manufacturing process on the CQA. Conclusions. At the stage of PD for the combined medicine in the capsule dosage form the potential critical indicators of the drug quality have been determined. The critical parameters of the quality of the initial components and the properties of the product have been assessed; the most probable risks for the drug quality have been identified, analyzed and assessed. Further research is advisable to focus on studying the effect of process parameters on critical parameters of the product quality and assessing risks for quality and creating a validation plan and its implementation.

A Fully Integrated Online Platform For Real Time Monitoring Of Multiple Product Quality Attributes In Biopharmaceutical Processes For Monoclonal Antibody Therapeutics