QBD 2.0: An Integrated Five-Pillar-Based Conceptual Predictive Lifecycle Framework for Next-Generation Pharmaceutical Development

Pharmaceutical development is gradually transitioning from empirical methodologies to science- and risk-based paradigms as outlined by ICH Q8-Q12. Conventional Quality by Design (QbD) has improved process understanding, but its practical implementation is hindered by fragmented data systems, reactive control methodologies, and poor correlation to downstream clinical performance. This review analyses how Industry 4.0 technology drives the transition into an Integrated Predictive Lifecycle (IPL) or "QbD 2.0" framework. Evidence from the current literature on AI-driven process control, digital twins, patient-centric modelling, supply chain intelligence, and sustainability measures was systematically compiled and organized into five interconnected thematic pillars. These comprise AI-enabled predictive control, digital continuity across the product lifecycle, mechanistic-clinical integration using quantitative patient-centric models, resilient-by-design supply chains, and the formalization of sustainability through gCQAs and green metrics. Together, the components establish a digitally unified and clinically aligned ecosystem that continuously optimizes product quality, manufacturing performance, and patient outcomes. The review also identifies challenges to implementation, which include interoperability limitations, AI/ML system validation, regulatory uncertainty, financial sensitivity, and organizational readiness. It also outlines evidence-aligned mitigation strategies. Therefore, QbD 2.0 is a progressive, evidence-based paradigm that improves predictability, lifecycle connection, resilience, and patient relevance while defining a practical pathway for the next generation of pharmaceutical manufacturing.