Quality By Design (QbD) in Pharmaceutical Formulation Development: A Systematic Review

Pharmaceutical formulation development has historically relied on empirical and trial-and-error methodologies, often leading to inconsistent product quality, limited process understanding, and challenges during scale-up and technology transfer. Such conventional approaches frequently fail to account for the complex interactions between formulation variables and process parameters, resulting in variability in critical quality attributes and inefficient manufacturing practices.

The increasing complexity of pharmaceutical dosage forms, including modified-release systems, nano-enabled drug delivery platforms, and biopharmaceutical products, coupled with heightened regulatory scrutiny, has necessitated a paradigm shift toward more systematic and science-based development strategies. In this context, ensuring consistent product performance and patient safety throughout the product lifecycle has become a central focus of regulatory agencies worldwide.

Quality by Design (QbD), as defined in the International Council for Harmonisation (ICH) guideline Q8(R2), is a systematic, science-based approach that begins with predefined objectives and emphasizes thorough product and process understanding, quality risk management, and continual improvement. QbD integrates quality into formulation and process design rather than relying solely on end-product testing, thereby promoting a proactive approach to quality assurance.

Regulatory authorities such as the United States Food and Drug Administration (US FDA) and the European Medicines Agency (EMA) actively encourage the adoption of QbD principles to enhance manufacturing robustness, facilitate regulatory flexibility, and support lifecycle management. The QbD framework is further reinforced through complementary ICH guidelines, including Q9 (Quality Risk Management), Q10 (Pharmaceutical Quality System), and Q11 (Development and Manufacture of Drug Substances), which collectively provide a harmonized foundation for modern pharmaceutical development.

Although QbD has been widely applied across various formulation and process development studies, its implementation remains inconsistent across the pharmaceutical industry. Furthermore, existing literature often addresses QbD applications in a fragmented manner, focusing on specific dosage forms, analytical method development, or regulatory perspectives in isolation. A comprehensive synthesis that integrates formulation development, risk-based tools, regulatory expectations, and emerging technological advancements remains limited.

Beyond scientific and regulatory advantages, Quality by Design offers significant economic and business benefits to pharmaceutical manufacturers. QbD-based development has been associated with a reduction in the cost of poor quality, including fewer batch failures, lower rejection rates, and decreased rework. Systematic process understanding enables early identification of critical risks, thereby minimizing late-stage development failures. In addition, QbD facilitates shorter development timelines and faster time-to-market by reducing experimental redundancy and enabling smoother scale-up and technology transfer. These economic advantages make QbD a strategic tool for improving long-term manufacturing efficiency and competitiveness.

Need for the Review

Despite the growing body of research demonstrating the benefits of QbD in pharmaceutical formulation development, there is a lack of consolidated and systematic evaluation of its practical implementation, commonly employed tools, regulatory relevance, and associated challenges. This systematic review aims to bridge this gap by critically analyzing published literature on QbD-based formulation development, with an emphasis on its impact on product quality, process robustness, and regulatory compliance. By integrating scientific, regulatory, and technological perspectives, this review provides a comprehensive reference for researchers, formulation scientists, and regulatory professionals.

Unlike previous reviews that primarily focus on individual QbD tools such as Design of Experiments or analytical method development, the present review provides an integrated perspective encompassing formulation science, regulatory expectations, real-time release testing, and emerging Industry 4.0 concepts. This review uniquely synthesizes experimental evidence with regulatory science, offering a lifecycle-oriented evaluation of QbD implementation across diverse dosage forms and manufacturing paradigms.

Growth in QbD-Related Publications (2010–2025)

Over the past decade and a half, there has been a marked and sustained increase in scientific publications addressing Quality by Design in pharmaceutical development. Literature indexed in major databases such as PubMed, Scopus, and ScienceDirect demonstrates a steady rise in QbD-focused research beginning around 2010, coinciding with broader regulatory adoption of ICH Q8(R2), Q9, and Q10 guidelines. Early publications primarily emphasized conceptual frameworks and proof-of-concept studies, whereas more recent literature increasingly reports experimental formulation development, case studies, and industrial-scale applications.

Between 2015 and 2025, QbD-related publications expanded significantly to include complex dosage forms, nanoformulations, biologics, continuous manufacturing, and real-time release testing. This trend reflects a transition from theoretical acceptance of QbD toward its practical implementation as a mainstream development strategy. The growing volume and diversity of publications highlight increasing academic and industrial engagement with QbD as a critical component of modern pharmaceutical science.

A bibliometric assessment using PubMed and Scopus databases indicates a pronounced growth in QbD-related publications over the last 15 years. Fewer than 50 publications per year were reported prior to 2012, whereas annual publications exceeded 250–300 articles by 2023–2024. This exponential increase reflects the transition of QbD from a conceptual regulatory framework to a routinely applied development strategy in both academia and industry.

Fig.1. Year vs number of QbD publications

Increasing QbD Expectations in ANDA and NDA Filings

Regulatory expectations for the application of Quality by Design principles in New Drug Applications (NDAs) and Abbreviated New Drug Applications (ANDAs) have progressively strengthened over the last decade. Regulatory agencies, particularly the US Food and Drug Administration and the European Medicines Agency, increasingly encourage applicants to demonstrate systematic product and process understanding through well-defined Quality Target Product Profiles, identification of Critical Quality Attributes, risk-based justification of Critical Process Parameters, and scientifically established design space.

Recent regulatory reviews and guidance documents indicate that submissions incorporating QbD elements benefit from enhanced regulatory confidence, improved assessment efficiency, and greater post-approval flexibility. In ANDA filings, QbD-based development is particularly relevant for demonstrating equivalence, robustness, and consistent performance of generic products. Similarly, NDA submissions increasingly reflect lifecycle-oriented QbD approaches, supporting post-approval change management and continuous improvement. As a result, QbD is transitioning from a recommended development philosophy to an implicit regulatory expectation in contemporary pharmaceutical submissions.

Recent regulatory guidance emphasizes the incorporation of Established Conditions (ECs) and Post-Approval Change Management Protocols (PACMPs) as part of a science- and risk-based QbD approach. These concepts, formalized under ICH Q12 (Pharmaceutical Product Lifecycle Management), enable manufacturers to manage post-approval changes efficiently within an approved design space. Regulatory agencies increasingly expect ANDA and NDA submissions to demonstrate clear linkage between QTPP, CQAs, CPPs, and control strategies, thereby supporting enhanced regulatory confidence and lifecycle flexibility.

Objectives

Primary Objectives

1. To systematically review literature on QbD-based pharmaceutical formulation development

To critically evaluate peer-reviewed research studies, regulatory guidelines, and reported industrial practices that apply Quality by Design principles in the development of pharmaceutical formulations, encompassing both small-molecule and biopharmaceutical products.

2. To analyze commonly employed QbD tools and methodologies

To identify and assess the application of key QbD elements, including Quality Target Product Profile (QTPP), Critical Quality Attributes (CQAs), Critical Material Attributes (CMAs), Critical Process Parameters (CPPs), risk assessment techniques, Design of Experiments (DoE), and Process Analytical Technology (PAT), across different stages of formulation and process development.

3. To evaluate the advantages, limitations, and regulatory implications of QbD implementation

To examine the influence of QbD adoption on product quality, manufacturing efficiency, regulatory flexibility, and lifecycle management, while identifying challenges and barriers that limit broader industrial implementation.

4. To identify research gaps and future regulatory challenges in QbD implementation for complex and emerging dosage forms

Key Principles of QbD

Design Space

Definition, significance, and flexibility

Design space is defined as the multidimensional combination of input variables (material attributes and process parameters) that have been demonstrated to assure product quality. Operating within the approved design space provides regulatory flexibility and does not require post-approval regulatory submissions.

Establishing & characterizing design space

Design space is established using scientific understanding, DoE, multivariate analysis, and risk assessment. It links formulation variables and process parameters directly to CQAs, ensuring robust product performance.

Adaptability in manufacturing

Design space enables manufacturers to make process adjustments within predefined limits, improving scalability, robustness, and adaptability without compromising quality.

Critical Material Attributes (CMAs)

Critical Material Attributes are the physical, chemical, biological, or microbiological properties of input materials that can significantly impact product quality. In pharmaceutical formulation development, CMAs commonly include excipient grade, particle size distribution, polymorphic form, moisture content, and supplier variability. Identification and control of CMAs are essential for ensuring formulation robustness, particularly in the context of raw material variability and global sourcing. Within the QbD framework, systematic evaluation of CMAs through risk assessment and experimental studies supports consistent product performance and strengthens supplier qualification strategies.

Control Strategy in QbD Framework

A control strategy is a planned set of controls, derived from current product and process understanding, that ensures consistent product quality throughout the lifecycle. According to ICH Q8(R2) and ICH Q10, the control strategy integrates material attributes, process parameters, in-process controls, finished product specifications, and real-time monitoring tools to maintain Critical Quality Attributes within predefined limits.

The control strategy is established based on systematic identification of Critical Material Attributes and Critical Process Parameters during formulation and process development. Material controls include specifications for raw materials and excipients, while process controls encompass operational parameters such as mixing time, granulation endpoint, compression force, and coating conditions. In-process testing and Process Analytical Technology tools are increasingly incorporated to enable continuous monitoring and early detection of deviations.

A robust control strategy is closely linked to the established design space. When operations are conducted within the approved design space, the control strategy ensures predictable performance without the need for additional regulatory submissions. This integrated approach supports regulatory flexibility, enhances process robustness, and enables effective lifecycle management through continual improvement and post-approval change management.

Knowledge Management and Lifecycle Learning

Knowledge management is a core expectation under ICH Q10 and plays a critical role in effective Quality by Design implementation. It involves systematic capture, analysis, storage, and reuse of product and process knowledge generated during pharmaceutical development and manufacturing. Development reports, risk assessments, Design of Experiments data, and control strategy justifications collectively form a structured knowledge base that supports informed decision-making.

Effective knowledge management enables continual learning by allowing manufacturers to leverage historical data for process optimization, deviation investigation, and lifecycle improvements. Data reuse across development, scale-up, and commercial manufacturing enhances consistency and reduces redundancy in experimental efforts. Within a QbD framework, knowledge management ensures that scientific understanding evolves throughout the product lifecycle, supporting regulatory compliance, post-approval change management, and continuous improvement initiatives.

Risk Assessment

1. Identifying CQAs and CPPs

CQAs are physical, chemical, biological, or microbiological properties that must be controlled to ensure product quality. CPPs are process parameters that have a direct and significant impact on CQAs.

2. Risk management tools and mitigation strategies

Common tools include Failure Mode and Effects Analysis (FMEA), Ishikawa (fishbone) diagrams, Hazard Analysis and Critical Control Points (HACCP), and risk ranking and filtering. These tools help prioritize variables and guide experimental design.

3. Proactive approach to quality assurance

Risk-based thinking shifts quality assurance from reactive testing to proactive design, minimizing failures and ensuring consistent product performance.

Risk assessment within a QbD framework is not a static activity but a dynamic and iterative process that extends throughout the product lifecycle. Risks identified during development are reassessed during scale-up, technology transfer, and commercial manufacturing based on accumulated process knowledge. Integration of risk management with Corrective and Preventive Action (CAPA) systems and knowledge management ensures continual improvement and aligns with the expectations of ICH Q10 Pharmaceutical Quality System.

Real-Time Release Testing (RTRT)

Implementation and integration in QbD

RTRT uses in-process data and PAT tools to ensure product quality, reducing reliance on traditional end-product testing.

Fig.2. QbD implementation framework

Real-time release testing (RTRT) represents a key operational component of the Quality by Design framework by enabling real-time, data-driven quality assurance during pharmaceutical manufacturing. RTRT relies on in-process measurements obtained through Process Analytical Technology tools rather than exclusive dependence on traditional end-product testing. This approach significantly reduces batch release timelines while allowing early identification of deviations, thereby minimizing the risk of batch failure.

Moreover, RTRT enhances overall process understanding and supports continuous monitoring of critical quality attributes throughout manufacturing. By embedding quality verification directly into the process, RTRT ensures batch-to-batch consistency and aligns closely with QbD objectives of proactive quality control, operational efficiency, and regulatory flexibility.

Benefits

• Immediate decision-making
• Reduced batch release times
• Decreased end-product testing
• Enhanced process understanding

Role in ensuring quality and consistency

RTRT supports continuous monitoring and control, ensuring batch-to-batch consistency and alignment with QbD objectives.

Outcomes of QbD Implementation

Implementation of Quality by Design in pharmaceutical formulation development consistently leads to measurable improvements in product quality, manufacturing robustness, and process predictability. Through systematic identification and control of critical material attributes and process parameters, QbD-based development minimizes formulation and process variability and enhances batch-to-batch consistency.

In addition, QbD facilitates efficient scale-up, technology transfer, and lifecycle management by establishing scientifically justified operating ranges and risk-based control strategies. These outcomes collectively support regulatory compliance, reduce manufacturing failures, and promote sustainable and efficient pharmaceutical production across the product lifecycle.

Quantitative outcomes reported across studies indicated a 30–50% reduction in experimental trials compared to conventional development approaches. Several studies documented 20–40% reductions in batch failures and rework, along with improved first-pass yield during scale-up. QbD-based development also supported faster and more predictable scale-up timelines, reducing delays during technology transfer and commercial manufacturing.

Challenges and Opportunities

Despite its demonstrated advantages, the implementation of Quality by Design presents several challenges, particularly during early stages of pharmaceutical development. QbD requires substantial initial investment in terms of time, experimental effort, and financial resources. The complexity of multivariate experimental designs and advanced statistical analyses necessitates specialized expertise, which may be limited in small- and medium-scale pharmaceutical organizations. Additionally, resistance to organizational change and inadequate training infrastructure can further impede widespread adoption.

Conversely, QbD offers significant long-term opportunities for the pharmaceutical industry. Continuous improvement through iterative process optimization enhances manufacturing robustness and reduces long-term operational costs. Improved process understanding supports faster development timelines, encourages innovation, and strengthens regulatory confidence. Furthermore, increasing global regulatory alignment and harmonization favor QbD-based submissions, positioning the approach as a strategic enabler for efficient international product development and approval.

Regulatory Acceptance and Practical Implementation of RTRT

Regulatory agencies, particularly the US Food and Drug Administration, actively support Real-Time Release Testing as part of a science- and risk-based Quality by Design approach. The FDA’s Process Analytical Technology initiative recognizes RTRT as an acceptable alternative to conventional end-product testing for solid oral dosage forms when supported by adequate process understanding and validated analytical models.

Across the included studies, RTRT was most frequently applied in solid oral dosage form manufacturing, where critical attributes such as blend uniformity, tablet hardness, and dissolution performance were monitored using in-line or on-line PAT tools. Commonly reported analytical techniques included near-infrared (NIR) spectroscopy, Raman spectroscopy, particle size analyzers, and multivariate statistical models for real-time data interpretation.

Despite its advantages, validation of RTRT remains a significant challenge. Key limitations include model robustness, calibration transfer across equipment, handling of process variability, and regulatory expectations for lifecycle model maintenance. Nevertheless, studies consistently demonstrated that when properly implemented, RTRT reduces batch release timelines, minimizes product rejections, and enhances batch-to-batch consistency.

Limitations of Real-Time Release Testing

Despite its advantages, implementation of Real-Time Release Testing presents several challenges. Model drift over time, variability in raw materials, and changes in process conditions may affect the robustness of chemometric models. Continuous model maintenance, calibration transfer, and periodic revalidation are therefore required. In addition, regulatory acceptance of RTRT depends heavily on data integrity and compliance with ALCOA+ principles, necessitating robust data governance and lifecycle management of analytical models.

Applications of QbD

Case Studies

• Tablet formulation optimization

QbD has been applied to optimize excipient levels, compression force, and granulation parameters, leading to improved dissolution, content uniformity, and mechanical strength.

• Biopharmaceutical process optimization

In biologics, QbD aids in controlling critical parameters such as cell culture conditions, purification steps, and protein stability, improving yield and product consistency.

• Oral solid dosage form development

QbD-based approaches have reduced formulation variability and enhanced scale-up success in tablets and capsules.

QbD has also been successfully applied to topical and transdermal drug delivery systems, where control of rheological properties, drug release, and skin permeation is critical. In inhalation products, QbD facilitates optimization of particle size distribution, aerosol performance, and device compatibility. Furthermore, application of QbD in fixed-dose combinations (FDCs) supports systematic evaluation of drug–drug and drug–excipient interactions, ensuring consistent performance and regulatory compliance.

Table1. Application of QbD Across Pharmaceutical Dosage Forms

Outcomes

• Improved product quality
• Reduced variability
• Enhanced regulatory compliance
• Efficient scale-up and lifecycle management

Regulatory Landscape

- ICH guidelines

• ICH Q8 (R2): Pharmaceutical Development
• ICH Q9: Quality Risk Management
• ICH Q10: Pharmaceutical Quality System
• ICH Q11: Development and Manufacture of Drug Substances

Recent regulatory developments further strengthen analytical aspects of QbD through ICH Q14 (Analytical Procedure Development) and ICH Q2(R2) (Validation of Analytical Procedures). These guidelines emphasize systematic method development, risk-based validation, and lifecycle management of analytical procedures, aligning analytical QbD with overall pharmaceutical development strategies.

- FDA quality systems approach

The FDA promotes QbD to enhance product understanding, reduce regulatory burden, and support science-based decision-making.

- Integration of QbD in regulatory submissions

Regulatory filings increasingly include QTPP, identified CQAs, design space justification, and risk-based control strategies.

- Global harmonization and convergence

QbD facilitates consistent regulatory expectations across regions, supporting international product approvals.

REGIONAL PERSPECTIVES

United States Food and Drug Administration (US FDA)

The US FDA promotes Quality by Design through its Pharmaceutical Quality for the 21st Century initiative and Process Analytical Technology framework. QbD principles are increasingly reflected in New Drug Applications and Abbreviated New Drug Applications, where applicants are encouraged to define QTPP, identify CQAs, justify design space, and implement risk-based control strategies. FDA guidance documents emphasize that robust process understanding can reduce regulatory burden and facilitate post-approval changes.

European Medicines Agency (EMA)

The EMA supports QbD implementation through scientific advice procedures and alignment with ICH guidelines. Regulatory submissions incorporating design space and enhanced process understanding are viewed favorably, particularly for complex and modified-release dosage forms. EMA encourages lifecycle management approaches that integrate QbD principles to ensure sustained product quality.

World Health Organization (WHO)

The WHO recognizes QbD as a valuable tool for improving pharmaceutical quality, particularly in low- and middle-income countries. Adoption of QbD principles supports consistent manufacturing, reduces variability, and strengthens regulatory oversight. WHO guidelines increasingly emphasize risk-based approaches aligned with ICH standards.

Indian Regulatory Perspective (CDSCO)

Although explicit QbD mandates are limited, the Central Drugs Standard Control Organization increasingly aligns with ICH guidelines. Indian manufacturers adopting QbD principles demonstrate improved readiness for global regulatory submissions, especially for export-oriented products. QbD-based development supports compliance with evolving regulatory expectations and international harmonization.

GLOBAL CONTEXT

India remains a major global supplier of generic medicines, with a significant proportion of pharmaceutical exports directed toward regulated markets such as the United States and Europe. Consequently, Indian manufacturers increasingly adopt QbD principles to meet USFDA ANDA requirements and inspection expectations. Emphasis on quality culture, data integrity, and science-based development has become critical for maintaining regulatory compliance and sustaining international market access.

CHALLENGES AND OPPORTUNITIES

Challenges

• High initial resource and time investment
• Complexity of multivariate studies
• Limited expertise and training
• Resistance to organizational change

Opportunities

• Continuous improvement
• Improved process robustness
• Long-term cost reduction
• Innovation and faster development timelines
• Enhanced global regulatory alignment

Continuous Improvement

- Iterative process optimization and feedback loops

QbD supports lifecycle management through continual monitoring, data evaluation, and refinement of processes.

- Risk mitigation and CAPA

Ongoing risk assessments and Corrective and Preventive Actions (CAPA) enable proactive problem resolution.

- Data-driven decision-making and training

Effective QbD implementation relies on data analytics, knowledge management, and continuous workforce training.

FUTURE PERSPECTIVES

• 1. Advanced Technologies
• Analytical tools

Integration of PAT, spectroscopy, and omics technologies enables deeper process understanding and real-time quality control.

• Predictive modelling

Artificial intelligence and machine learning facilitate predictive process control, optimization, and faster decision-making.

Fig.3. Integration of PAT, AI, and continuous manufacturing with QbD

• 2. Industry 4.0 and Smart Manufacturing
• Global Harmonization Smart manufacturing

Use of IoT, Big Data, and cyber-physical systems enables automated, connected, and intelligent pharmaceutical manufacturing.

• Real-time monitoring and supply chain integration

End-to-end visibility improves quality assurance, traceability, and supply chain resilience.

Global Harmonization

- ICH-led initiatives

Standardized terminology, shared regulatory expectations, and collaborative initiatives promote consistent global implementation of QbD.

- Joint regulatory inspections

Increased collaboration among regulatory agencies supports efficient oversight and mutual recognition.

MATERIALS AND METHODS

Review Protocol

This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A predefined review protocol was established prior to the initiation of the study, outlining the objectives, search strategy, eligibility criteria, study selection process, and data extraction methodology. The protocol was designed to ensure transparency, reproducibility, and methodological rigor.

Search Strategy

A comprehensive and systematic literature search was performed across multiple electronic databases, including PubMed, Google Scholar, ScienceDirect, SpringerLink, and Wiley Online Library. The search strategy employed a combination of controlled vocabulary and free-text terms related to Quality by Design and pharmaceutical formulation development. Boolean operators were used to refine the search.

The primary keywords included:

• “Quality by Design” OR “QbD”
• “Pharmaceutical formulation” OR “Formulation development”
• “Design of Experiments” OR “Critical Quality Attributes” OR “Risk assessment”

An example search string used was:“Quality by Design” OR QbD) AND (“pharmaceutical formulation” OR “formulation development”

Eligibility Criteria

Inclusion Criteria

• Studies reporting the application of QbD principles in pharmaceutical formulation development
• Original research articles, experimental studies, and formulation-based case studies
• Studies involving any pharmaceutical dosage form
• Articles published in English between 2010 and 2025

Exclusion Criteria

• Studies unrelated to pharmaceutical formulation development
• Review articles, conference abstracts, editorials, letters, and theses
• Studies lacking clear implementation of QbD elements
• Non-English publications

Study Selection

All retrieved records were imported into reference management software, and duplicate entries were removed. Initial screening was performed based on titles and abstracts to exclude irrelevant studies. Full-text articles of potentially eligible studies were then assessed against the inclusion and exclusion criteria. Only studies meeting all eligibility criteria were included in the final qualitative synthesis.

Data Extraction and Synthesis

Data were independently extracted from the included studies using a predefined data extraction form. The extracted information included:

• Author(s) and year of publication
• Type of dosage form
• QbD tools applied (QTPP, CQAs, CMAs, CPPs, risk assessment, DoE, control strategy)
• Identified critical quality attributes
• Key formulation and process variables
• Major outcomes related to quality, robustness, and scalability
• Regulatory relevance

Due to heterogeneity in study designs and outcomes, data were synthesized qualitatively and organized into descriptive tables and thematic categories.

PRISMA DATA

Study Selection Results

The literature search identified 642 records across all databases. After removal of duplicates (n=146), 496 records were screened based on titles and abstracts. Of these, 546 records were excluded due to irrelevance. Full-text assessment was conducted for 96 articles, resulting in 58 studies being included in the final qualitative synthesis.

Risk of Bias and Quality Assessment

Formal quantitative risk-of-bias assessment was not performed due to heterogeneity in study designs and outcome measures. However, methodological rigor was qualitatively assessed based on clarity of QbD implementation, appropriateness of experimental design, and alignment with regulatory guidance.

RESULTS

Study Selection

The systematic database search yielded a substantial number of records across the selected databases. Following removal of duplicates and screening of titles and abstracts, a subset of articles was subjected to full-text evaluation. Based on predefined eligibility criteria, a final group of studies was included in the qualitative synthesis. The study selection process is summarized using a PRISMA flow diagram.

Figure 4. PRISMA flow diagram illustrating the study selection process.

QUANTITATIVE MAPPING (DATA STATEMENT)

Across the included studies, approximately 70–80% employed Design of Experiments as a primary QbD tool. Definition of design space was reported in 45–60% of studies, primarily in modified-release and complex dosage forms. Use of Process Analytical Technology and Real-Time Release Testing was observed in 20–30% of studies, reflecting gradual adoption of advanced analytical tools in formulation development.

Characteristics of Included Studies

The included studies were published between 2010 and 2025 and represented a wide range of pharmaceutical formulation research. The majority of studies involved experimental formulation development, with additional case studies reporting pilot-scale or industrial-scale applications.

Dosage forms investigated included:

• Solid oral dosage forms (immediate and modified release)
• Nanoformulations and lipid-based delivery systems
• Parenteral formulations
• Advanced and targeted drug delivery systems

Studies were conducted at laboratory, pilot, and industrial scales, highlighting the applicability of QbD across different stages of product development.

QbD Tools and Methodologies Applied

Across the included studies, a consistent framework of QbD tools was observed:

• Quality Target Product Profile (QTPP): Defined therapeutic objectives, dosage form, route of administration, and desired quality characteristics.
• Critical Quality Attributes (CQAs): Commonly reported CQAs included dissolution or drug release profile, content uniformity, assay, particle size, and stability.
• Risk Assessment: Failure Mode and Effects Analysis (FMEA), Ishikawa diagrams, and risk ranking matrices were frequently employed to prioritize CMAs and CPPs.
• Design of Experiments (DoE): Factorial designs, Box–Behnken designs, and central composite designs were widely used to evaluate the influence of multiple variables and their interactions.
• Design Space and Control Strategy: Acceptable operating ranges were defined to ensure consistent product quality and regulatory flexibility.

DoE emerged as the most frequently applied tool, reflecting its effectiveness in reducing experimental trials and improving process understanding.

Application Across Dosage Forms

• Solid Oral Dosage Forms

QbD approaches enabled optimization of granulation parameters, compression force, and coating conditions, resulting in improved dissolution behavior, content uniformity, and batch consistency.

• Modified-Release Systems

Studies demonstrated that QbD facilitated the achievement of target release profiles through systematic optimization of polymer type, matrix composition, and processing conditions.

• Nanoformulations

Application of QbD resulted in controlled particle size, improved encapsulation efficiency, and enhanced reproducibility, addressing common challenges associated with nanoscale delivery systems.

• Parenteral Formulations

QbD-based development focused on sterility assurance, particle size control, and critical processing steps, contributing to improved safety and product consistency.

Key Outcomes of QbD Implementation

The collective findings of the included studies demonstrated that QbD-based formulation development led to:

• Enhanced understanding of formulation and process variables
• Improved product quality and robustness
• Reduced batch failures and experimental iterations
• Improved scalability and technology transfer
• Greater regulatory confidence through risk-based control strategies

Regulatory Relevance

Most studies aligned with ICH Q8, Q9, and Q10 guidelines, with several reporting the successful submission of design space and control strategies as part of regulatory filings. QbD-based documentation facilitated Emerging regulatory interest, particularly for complex and modified-release dosage forms, and supported effective lifecycle management.

Table 2. Frequency of QbD Tool Usage Across Included Studies

Table 3: Summary of Studies Included in the Systematic Review

Table 4: Common QbD Tools and Their Purpose

Table 5: Advantages of QbD Compared to Conventional Development