Quality by design (QbD) approach in marketing authorization procedures of Non-Biological Complex Drugs: A critical evaluation

设计质量 灵活性(工程) 风险分析(工程) 质量(理念) 计算机科学 制药工业 过程(计算) 关键质量属性 过程管理 销售授权 授权 生化工程 管理科学 新产品开发 业务 工程类 营销 医学 药理学 计算机安全 生物信息学 哲学 统计 数学 认识论 生物 操作系统
作者
Daniela M. Zagalo,João Sousa,Sérgio Simões
出处
期刊:European Journal of Pharmaceutics and Biopharmaceutics [Elsevier BV]
卷期号:178: 1-24 被引量:33
标识
DOI:10.1016/j.ejpb.2022.07.014
摘要

The emergence of innovator-driven complex drug products, such as Non-Biological Complex Drugs (NBCDs), has provided disruptive advances in the Nanotechnology and Biotechnology fields. However, the design and development of NBCDs can be particularly challenging due to some unresolved scientific and regulatory challenges associated with the pharmaceutical quality assessment. The application of a more holistic, systematic, integrated science and risk-based approach, such as Quality by Design (QbD), is essential to address key scientific, technological, and regulatory constraints in the research and development of the NBCDs. The deeper product and process understanding derived from the implementation of the QbD approach ensures consistent, reliable, and high-quality pharmaceutical products. Furthermore, this approach promotes innovation and continuous improvement in the entire product lifecycle. Regulatory authorities highly recommend QbD-based submissions to successfully translate NBCDs from laboratory-scale research to the pharmaceutical market with the required quality, safety, and efficacy standards. The main aim of this article is to obtain a comprehensive and in-depth investigation into the state of implementation of the QbD approach in the pharmaceutical development and marketing authorization of NBCDs in Europe and the United States, through the analysis of the available data from their regulatory dossiers. In addition, it aims to understand and discuss how the QbD approach is used and implemented for complex drug products in the pharmaceutical industry, highlighting the gaps and challenges involved with its implementation. An analysis is held regarding QbD's advantages in terms of knowledge growth, regulatory flexibility, and the speed of development based on big data science, along with the reduction of regulatory failures and market withdrawals.

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