PDA Journal of Pharmaceutical Science and Technology最新文献

One of the most important requirements for a sterile packaging system is container closure integrity (CCI). For vial-based systems comprised of a vial, a hyper-elastic stopper, and a rigid crimp seal, CCI testing is an integral part of the drug development process.  During the vial-capping process, the component dimensions and materials play a critical role in creating a robust and adequate seal that will satisfy CCI. Although these properties are manufactured within certain tolerances there exist lot to lot variabilities and aging effects. If not taken into consideration during initial design, these factors can potentially impact the Residual Seal Force (RSF)  for a container closure system (CCS). Residual Seal Force (RSF) of the vial, while not predictive or causal, is correlated with CCI. For example, is possible that containers with sufficient RSF can contain defects that compromise CCI, including but not limited to fibers, cracks, and folds.A robust and efficient deterministic finite element model capable of predicting RSF for fixed displacement crimping systems was developed for this study. A probabilistic analysis was conducted, and stopper top dimensions (height and outer diameter (OD)) were found to be the most important drivers of seal force magnitude and variation. Seal force was positively correlated with both stopper height and OD. The effect of 2-year accelerated aging of the stopper, prior to assembly, was an increase to material stiffness and corresponding seal force. However, this increase in force was small (~3%). This corresponds well with practical findings where shelf aging is typically associated with increased material stiffness over time as well as an increase in RSF.

The European Qualified Person (QP) holds unique legal responsibility for certifying batch release, ensuring patient safety, and maintaining regulatory compliance. Modern pharmaceutical manufacturing-especially in biologics, ATMPs, and personalized medicinesâgenerates complex, multi-site, data-rich environments that challenge traditional oversight. Artificial Intelligence (AI) offers predictive analytics, anomaly detection, and trend recognition to support decision-making but cannot currently replace the QPâs scientific judgment or legal accountability. The forthcoming Annex 22 introduces Human-in-the-Loop (HITL) frameworks that embed human oversight within AI-supported processes, aligning technological advancement with regulatory control. This review explores evolving QP responsibilities, core and emerging competencies, AI integration within Quality Risk Management (QRM) and GMP frameworks, and ethical considerations, illustrated with practical case studies. By developing AI literacy and applying HITL oversight, QPs can more effectively translate technological potential into transparent, science-based, and patient-centered batch-release decisions.

Good contamination control practices in a controlled manufacturing environment demand consistency, which can be undermined by the common belief that the use of disinfectants alone will control the microbiological risk.  This comes from a legacy misunderstanding that use of a sporicide will correct other control failures.  The use of a sporicide in a cleanroom is not meant to replace good cleaning and broad-spectrum microbial disinfection but to complement broad spectrum efficacy when bacterial spore-formers are a persistent risk to the process .  Along with the rotation of a sporicidal disinfectant, a good balance of microbiological control for incoming materials and good gowning practices reduce the risk of introduction of microbiological contamination into a cleanroom or controlled environment.  Clear understanding of bacterial spore-formers and a risk-based approach to the removal of potential sources of bacterial spore-formers will lead to a good practice for the use of a sporicide in sterile pharmaceutical manufacturing environments.

During their clinical use, medical devices contact, directly or indirectly, tissue of the person (patient) whose medical condition is being treated or monitored by the device. During contact, substances present in or on the medical device can be leached from the device. Medical devices are chemically characterized to establish the patient's actual exposure to leachables.Establishing actual leachables from implanted methodical devices is problematic as so doing would require sampling of the in vivo environment in which the device is implanted. Thus, leachables from implanted medical devices are estimated by performing extraction studies. Often, such extraction studies use extraction solvents of multiple polarities to establish the device's total extractables profile (all possible extractables at their highest possible levels).As the potential range of extractables' polarities is large, using a small number of extraction solvents with widely different polarities can produce polarity gaps, where an extractable is either not revealed by the selected extraction solvents (an omission gap) or is underestimated in the extraction solvents (a magnitude gap). In either circumstance, the patient's exposure to extractables (as potential leachables) is underestimated.Furthermore, extraction studies which use extraction solvents with polarities outside of the polarity range of in vivo environments are inefficient, as they reveal extractables that cannot possibly be leachables at levels that cannot possibly be achieved during clinical use.After discussing these challenges from a thermodynamic and conceptual perspective, this author proposes that extraction studies for implanted medical devices use extraction solvents whose polarities bracket the polarity of the implanted in vivo environment and that a non-polar solvent never be used for bracketing purposes. To accomplish bracketing, this author introduces the polarity range termed seminon- polar" establishes the polarity of in vivo environments, and specifies polarity brackets.

Lyophilization is a critical process, removing water and or solvent through sublimation to ensure the stability and longevity of injectable drug products. The complexity of the lyophilization process, involving multiple stages such as freezing, primary drying, and secondary drying, necessitates a robust approach to ensure product quality and consistency. Along with applying Quality by Design (QbD) principles in lyo process development, robust statistical and risk-based methodologies are essential for assessing process variability. This paper presents a risk-based and statistically sound sampling methodology for assessing variability in lyophilized drug products during Continued Process Verification (Stage 3a) of Process Validation. Sampling plans are strategically designed, ensuring representative data collection from lyophilizer shelves. By integrating variance analysis, capability indices, and probability, the methodology provides a comprehensive understanding of both intra-batch and inter-batch variability. The assessment enables estimation of future batch performance concerning critical quality attributes, including water content, assay, pH, and impurities. Identifying and controlling both intra-batch (within-shelf and between-shelf) and inter-batch variability ensures robustness. The study highlights the importance of statistically rigorous sampling plans, justification of the plans and data analysis to ensure process control. A case study is presented, demonstrating the application of the approach in a lyophilization process. The methodology supports regulatory compliance and enhances process understanding, enabling tighter process control and continuous improvement. The risk-based Stage 3a framework provides a structured method for post-commercialization variability assessment, bridging process design and continued verification.

This review article explores the application of artificial intelligence (AI) within Advanced Therapy Medicinal Products (ATMP) analysis, specifically focusing on challenges related to chemistry, manufacturing, and controls (CMC) and manufacturing processes. The inherent complexity and variability in ATMPs necessitate innovative solutions for potency testing, real-time process monitoring, and stability assessment. We examine how AI tools can contribute to these areas while navigating increasingly stringent regulatory landscapes. This work acknowledges the growing importance of data protection regulations worldwide, including frameworks such as HIPAA, GDPR, PIPEDA, POPIA, and LGPD, highlighting the need for secure data handling and patient privacy considerations within ATMP development and analysis. The integration of AI also necessitates attention to explainability and transparency, potentially leveraging techniques like SHAP values and physics-informed neural networks to ensure regulatory compliance and build trust in AI-driven insights.

Managing the transition from the new paradigm of in-process control using continuous biofluorescent particle counters from the traditional growth-based air monitoring is a difficult challenge requiring a comprehensive regulatory strategy. This is best approached within confines of the concept of process analytical technology. A five-stage approach to the evaluation, validation, test runs and data analysis, regulatory approval, and implementation is recommended. Critical to the implementation is the application of the safe harbor concept to avoid non-compliance issues.

Cell therapy products represent a transformative class of advanced medicinal products with unique manufacturing and quality control challenges. Unlike conventional parenteral products, cell therapies consist of living cells-typically delivered as turbid, non-filterable suspensions-which inherently complicates the control and detection of visible (VP) and subvisible particles (SvP). This review outlines the distinctive risks associated with particle generation in autologous and allogeneic cell therapies and highlights limitations of existing pharmacopeial methods for particle testing.We identify three major sources of particles in cell therapy products: the manufacturing process with often several manual manipulation steps, the single use manufacturing components, and the container closure systems. The complexity of the process is compounded by small batch sizes, short shelf-life, and complex formulations, and thus traditional sampling and visual inspection approaches have limitations in their utility. Therefore, cell therapy products often require tailored inspection strategies and supplemental process simulations.We review the current global regulatory requirements (USP <790>, Ph. Eur. 2.9.20, JP 6.06), contrast US and EU definitions for particle types, and discusses practical gaps in harmonization. We further evaluate emerging technologies like flow imaging microscopy for SvP characterization and propose optimized visual inspection strategies tailored for turbid cell suspensions. However, preventative or preemptive control, rather than end-stage inspection, is recommended as the most effective strategy. This requires systematic risk assessment, raw material control, process simulations, and supplier collaboration.The authors advocate for the development of cell therapy-specific inspection standards and call for regulatory alignment to support consistent global development and patient access.

Knowledge management (KM) is vital for supporting product quality throughout a biologic drug product's lifecycle. This paper presents suggestions for management of pre-PPQ (Process Performance Qualification) knowledge management for biologic manufacturing organizations. This topic was presented at the 2024 PDA Annual conference, with subjective audience survey questions that were employed in real time to customize the talking points for the presentation of KM suggestions.This paper presents a lifecycle knowledge management concept called the CQA (Critical Quality Attribute) Knowledge Accessibility Maintenance Loop (CQA-KAML). This lifecycle has been created to help organizations effectively find and manage CQA-relevant knowledge starting in the pre-PPQ phase of biologic product development to align with ICH (International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use) Q10 and other regulatory guidances.

Regulatory intelligence (RI) is an emerging and increasingly fundamental function within regulatory affairs, particularly in the biotechnology sector. Defined by its focus on the systematic collection, analysis, and dissemination of regulatory information, RI supports informed decision-making and strategic planning in a complex and rapidly evolving regulatory landscape. Despite its growing significance, regulatory intelligence remains underrepresented in academic literature. This paper seeks to provide a foundational understanding of the discipline by examining the evolving regulatory landscape, the processes involved in regulatory intelligence, and future considerations for its advancement. Data sources include peer-reviewed publications, regulatory authority documents, web-based articles, and industry blog posts. An integrated literature review identified three core components of regulatory intelligence: (1) information collection, (2) information analysis, and (3) information dissemination. The effectiveness of these components is closely linked to the maturity and integration of systems employed by biotechnology organizations. As regulatory frameworks become more dynamic and digital technologies advance, the role of RI will become increasingly central to proactive compliance, innovation strategy, and global market access.