This review clarifies the concept of pharmaceutical quality by design (QbD) and describes its objectives. QbD is a systematic approach to development that begins with predefined objectives and emphasizes product and process understanding and control based on sound science and quality risk management. The goals of QbD include achieving meaningful product quality specifications based on clinical performance, increasing process capability and reducing product variability, increasing product development and manufacturing efficiencies, and enhancing root cause analysis and postapproval change management. QbD elements include a quality target product profile (QTPP) that identifies critical quality attributes (CQAs), product design and understanding including identification of critical material attributes (CMAs), process design and understanding including identification of critical process parameters (CPPs), a control strategy that includes specifications for the drug substance, excipient, and drug product, and process capability and continual improvement. QbD tools and studies include prior knowledge, risk assessment, mechanistic models, design of experiments (DoE), and data analysis, as well as process analytical technology (PAT). The FDA encourages risk-based approaches and the adoption of QbD principles in drug product development, manufacturing, and regulation. QbD has evolved with the issuance of ICH Q8 (R2), ICH Q9, and ICH Q10. These documents provide high-level directions regarding the scope and definition of QbD in the pharmaceutical industry. QbD aims to ensure that drug products meet the desired quality, taking into account safety and efficacy. It involves identifying CQAs, which are properties or characteristics of an output material that should be within an appropriate limit to ensure the desired product quality. CQAs may include identity, assay, content uniformity, degradation products, residual solvents, drug release or dissolution, moisture content, microbial limits, and physical attributes. Product design and understanding involve the physical, chemical, and biological characterization of the drug substance, identification and selection of excipient type and grade, and knowledge of intrinsic excipient variability. Formulation optimization studies are essential in developing a robust formulation that is not on the edge of failure. These studies provide important information on the robustness of the formulation, identification of CMAs, and development of control strategies. Process design and understanding involve identifying critical process parameters (CPPs) and linking them to CQAs. Process robustness is the ability of a process to deliver acceptable drug product quality while tolerating variability in the process and material inputs. Process capability measures the inherent variability of a stable process in relation to established acceptance criteria. QbD tools include prior knowledge, risk assessment, DoE, and PAT. These tools facilitate the implementation of QbD and help in the identification of critical variables that impact product quality. The control strategy includes three levels of controls: Level 1 utilizes automatic engineering control to monitor CQAs in real time, Level 2 involves reduced end-product testing and flexible material attributes, and Level 3 relies onThis review clarifies the concept of pharmaceutical quality by design (QbD) and describes its objectives. QbD is a systematic approach to development that begins with predefined objectives and emphasizes product and process understanding and control based on sound science and quality risk management. The goals of QbD include achieving meaningful product quality specifications based on clinical performance, increasing process capability and reducing product variability, increasing product development and manufacturing efficiencies, and enhancing root cause analysis and postapproval change management. QbD elements include a quality target product profile (QTPP) that identifies critical quality attributes (CQAs), product design and understanding including identification of critical material attributes (CMAs), process design and understanding including identification of critical process parameters (CPPs), a control strategy that includes specifications for the drug substance, excipient, and drug product, and process capability and continual improvement. QbD tools and studies include prior knowledge, risk assessment, mechanistic models, design of experiments (DoE), and data analysis, as well as process analytical technology (PAT). The FDA encourages risk-based approaches and the adoption of QbD principles in drug product development, manufacturing, and regulation. QbD has evolved with the issuance of ICH Q8 (R2), ICH Q9, and ICH Q10. These documents provide high-level directions regarding the scope and definition of QbD in the pharmaceutical industry. QbD aims to ensure that drug products meet the desired quality, taking into account safety and efficacy. It involves identifying CQAs, which are properties or characteristics of an output material that should be within an appropriate limit to ensure the desired product quality. CQAs may include identity, assay, content uniformity, degradation products, residual solvents, drug release or dissolution, moisture content, microbial limits, and physical attributes. Product design and understanding involve the physical, chemical, and biological characterization of the drug substance, identification and selection of excipient type and grade, and knowledge of intrinsic excipient variability. Formulation optimization studies are essential in developing a robust formulation that is not on the edge of failure. These studies provide important information on the robustness of the formulation, identification of CMAs, and development of control strategies. Process design and understanding involve identifying critical process parameters (CPPs) and linking them to CQAs. Process robustness is the ability of a process to deliver acceptable drug product quality while tolerating variability in the process and material inputs. Process capability measures the inherent variability of a stable process in relation to established acceptance criteria. QbD tools include prior knowledge, risk assessment, DoE, and PAT. These tools facilitate the implementation of QbD and help in the identification of critical variables that impact product quality. The control strategy includes three levels of controls: Level 1 utilizes automatic engineering control to monitor CQAs in real time, Level 2 involves reduced end-product testing and flexible material attributes, and Level 3 relies on