Modernizing Process Validation: A QbD and Data Driven Perspective

Process validation is a critical element in pharmaceutical manufacturing, ensuring consistent product quality and regulatory compliance. This paper examines these guidelines in detail and highlights the transition from traditional validation methods to Quality by Design (QbD)-driven strategies. By integrating QbD principles with digital tools and lifecycle management, pharmaceutical manufacturers can enhance process understanding, reduce variability, and achieve higher product quality. This technical review highlights the critical role of Quality by Design (QbD) methodologies in enhancing pharmaceutical process validation. QbD employs Design of Experiments (DOE) and Multivariate Data Analysis (MVA) to develop predictive models that improve product and process understanding throughout the product lifecycle. DOE systematically investigates the influence of process variables on critical quality attributes, enabling optimization and robust control strategy development, as demonstrated by case studies in crystallization and blending processes. MVA techniques further support process optimization by analyzing complex multi-parameter data to identify critical process parameters and predict product quality. The integration of digital tools and electronic data platforms facilitates efficient data collection and analysis, enhancing continuous process verification and control. This review underscores the transformative impact of digital QbD applications in achieving consistent, high-quality pharmaceutical manufacturing compliant with evolving regulatory expectations.