A Living Comparability Protocol for Biopharmaceutical Manufacturing Processes That Continuously Evolve without Losing Product Understanding across Product Lifecycles

Biopharmaceutical manufacturing processes evolve through scale changes, equipment replacement, raw-material variation, site transfers, analytical modernization, process intensification, and post-approval optimization. Conventional comparability plans are commonly structured around a defined change and a prespecified evidence package, but repeated and interacting changes can fragment product knowledge across development and commercial lifecycles. This article proposes a living comparability protocol as an original adaptive-comparability framework for maintaining traceable product understanding while manufacturing processes continue to evolve. The protocol connects a version-controlled knowledge baseline, change classification, impact hypotheses, dynamic critical-quality-attribute weighting, tiered analytical and functional evidence, continuous process and product monitoring, requalification rules, and governance controls. Continuous monitoring is treated as a learning mechanism rather than as passive data collection: observations are interpreted against prior variability, mechanistic expectations, assay capability, and unresolved uncertainty. Protocol versioning records how assumptions, attribute priorities, analytical methods, acceptance rationales, and evidence requirements change over time. Requalification is triggered when accumulated evidence invalidates a prior assumption, alters an attribute’s relevance, reveals analytical blind spots, or weakens confidence in the existing control strategy. Governance and regulatory communication are organized around transparent change histories, explicit uncertainty statements, predefined escalation logic, and documented human accountability. The original contribution is therefore not a new analytical test or regulatory pathway, but a proposed architecture for preserving comparability reasoning across sequential manufacturing changes. The framework requires prospective testing using real product histories, orthogonal analytical evidence, functional studies, monitoring performance, and decision-concordance assessments. It does not establish clinical equivalence, interchangeability, regulatory acceptability, or universal applicability.