Kumar Sumant, Alsaidan Omar Awad, Alzarea Sami I, Kumar Akshay, Kondaveeti Suresh Babu, Sharma Diksha, Kumar Mohit, Kumar Devesh
Department of Pharmaceutical Sciences and Technology, Maharaja Ranjit Singh Punjab Technical University (MRSPTU), Bathinda, 151001, Punjab, India.
Department of Pharmaceutics, College of Pharmacy, Jouf University, 72341, Sakaka, Saudi Arabia.
AAPS PharmSciTech. 2025 Jul 28;26(7):198. doi: 10.1208/s12249-025-03191-8.
Quality by Design (QbD) has emerged as a systematic and proactive approach in pharmaceutical development, ensuring consistent product quality through a thorough understanding of formulation components and critical process parameters. In the context of phytosomal formulations, which increase bioavailability and therapeutic effectiveness of phytoconstituents. QbD-driven risk analysis is essential for optimizing formulation parameters and reducing variability. The incorporation of risk assessment tools, such as Fault Tree Analysis (FTA), Ishikawa fishbone diagrams, Failure Mode and Effect Analysis (FMEA), and Design of Experiments (DoE), facilitates the identification and management of critical material attributes (CMAs) and critical process parameters (CPPs) that profoundly affect the quality attributes of phytosomal carriers. Utilizing a scientific and data-driven methodology, QbD enhances formulation development, resulting in superior stability, encapsulation efficiency, and controlled release properties. Furthermore, the utilization of QbD principles ensures regulatory adherence, improves repeatability, and minimizes batch-to-batch variability, resulting in a more dependable and scalable production process. The pharmaceutical industry is shifting to a methodical and knowledge-based approach, and QbD-driven risk analysis in phytosomal formulations is a transformational tool for maximizing the therapeutic potential of bioactive phytoconstituents.
质量源于设计(QbD)已成为药物研发中的一种系统且积极主动的方法,通过全面了解制剂成分和关键工艺参数来确保产品质量的一致性。在提高植物成分生物利用度和治疗效果的植物脂质体制剂背景下,QbD驱动的风险分析对于优化制剂参数和减少变异性至关重要。纳入故障树分析(FTA)、石川鱼骨图、失效模式与效应分析(FMEA)和实验设计(DoE)等风险评估工具,有助于识别和管理对植物脂质体载体质量属性有深远影响的关键物料属性(CMA)和关键工艺参数(CPP)。利用科学且数据驱动的方法,QbD可加强制剂研发,从而实现卓越的稳定性、包封效率和控释性能。此外,运用QbD原则可确保符合法规要求,提高可重复性,并将批次间的变异性降至最低,从而实现更可靠且可扩展的生产过程。制药行业正在转向一种系统且基于知识的方法,而植物脂质体制剂中QbD驱动的风险分析是一种变革性工具,可最大限度地发挥生物活性植物成分的治疗潜力。