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The Korean Society of Food, Drug and Cosmetics Regulatory Sciences (KFDC) has been at the forefront of regulatory science development in Korea since its establishment in 2004. This study analyzes 20 years of the society's academic publications and conferences to elucidate the evolution of regulatory science research in Korea. We analyzed 299 journal articles published from 2006 to June 2025 and 448 presentations from 26 conferences held between 2011 and 2025. First, journal publications showed steady growth from 21 articles in 2006 to approximately 20 annually by 2021, reaching a cumulative total of 299 articles. Second, author composition shifted dramatically from government-dominated (70%) in the early years to academia-centered (70%) after 2019, indicating the transition of regulatory science from a policy-support domain to an independent academic discipline. Third, research scope expanded from pharmaceuticals (90%) to include medical devices (20- 30%), cosmetics, and food products, demonstrating the diversification of regulatory science. Fourth, conference participation increased from 93 attendees in 2018 to 318 in 2025, with presentations from industry (44%), government (37%), and academia (19%), establishing a balanced industry-academia-government collaboration structure. Fifth, emerging technology keywords including digital therapeutics (19 occurrences), big data/RWD/ RWE (18 occurrences), and artificial intelligence (11 occurrences) showed exponential growth after 2017, marking a paradigm shift toward evidence-based regulation. Based on these findings, this study provides strategic implications for the future development of regulatory science research and offers recommendations for the operation of academic conferences and journal management.

As the pharmaceutical industry transitions toward QbD (Quality by Design), implementing effective QRM (Quality Risk Management) is essential for ensuring drug safety. However, current practices often rely on subjective qualitative assessments and suffer from data disconnection caused by fragmented management across different departments. This study analyzes the methodological characteristics of risk assessment tools to propose an optimized, objective framework for pharmaceutical manufacturing. We conducted a comprehensive comparative analysis of major assessment methodologies based on International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) Q9 guidelines and International Organization for Standardization (ISO) / International Electrotechnical Commission (IEC) standards, evaluating their logical reasoning mechanisms, levels of data quantification, and suitability across the product lifecycle. The results demonstrate that distinct methodologies are required for different stages: qualitative approaches for design, inductive analysis for process establishment, and systematic monitoring for commercial manufacturing. Consequently, recognizing that no single tool covers the entire lifecycle, we propose an integrated model combining Quality Function Deployment (QFD), Failure Mode and Effects Analysis (FMEA), and Hazard Analysis and Critical Control Points (HACCP). This approach utilizes QFD design data to objectify FMEA severity criteria and link high-risk items to HACCP critical control points. This organic integration not only mitigates data disconnection but also enhances the objectivity of risk assessment throughout the product lifecycle.

Post-marketing surveillance of adverse events in real-world settings is a key process in drug safety management, and signal detection through spontaneous reporting systems provides critical evidence for regulatoryscientific decision-making. This study analyzed GLP-1 Receptor Agonists (GLP-1 RAs) class-related adverse event signals using the FDA Adverse Event Reporting System (FAERS) and identified factors influencing their formation. FAERS data from the second quarter of 2021 to the third quarter of 2025 were analyzed using disproportionality metrics (PRR, ROR, IC). The exposure group included all GLP-1 RA class drugs, and the comparator group comprised non-GLP-1 receptor agonists used for diabetes and obesity. Detected signals were categorized by MedDRA System Organ Class (SOC), and machine learning models (Random Forest (RF), XGBoost) were applied to identify predictors and contextual patterns of gastrointestinal (GI) adverse events. Signal detection results showed that GI disorders were frequently reported in the exposure group (a=211,797), with strong signals (ROR 2.94 [95% CI: 2.92–2.97]. The XGBoost and RF models achieved a high AUROC of 0.926 and 0.929, respectively, identifying patient age (45-64 years), seriousness, and reporter type as major predictors of GI-related signals. This suggests that GI adverse event reporting may be associated with specific reporting contexts and demographics, such as ‘patient age (45-64 years)’ and ‘seriousness’. The model's input features could predict whether a report was for a GI event with 92.9% accuracy. This study demonstrates the practical applicability of regulatory-scientific analytics, showing that combining machine learning with spontaneous reporting data enhances the accuracy and efficiency of post-marketing signal detection and provides stronger evidence for pharmacovigilance and risk management.

Although the incidence and mortality of chronic hepatitis B are increasing, there is a relative paucity of appropriate disease models mimicking disease progression over several years. Consequently, substantial delays in appropriate therapy might occur with the current diagnostic criteria, i.e., hepatitis B virus (HBV) DNA, alanine aminotransferase (ALT), and hepatitis B e antigen levels. Tenofovir is currently used as a firstline therapy for HBV but it does not cure the disease and treatment is often limited by resistance or adverse effects. Therefore, novel therapeutic agents to cure HBV, yet differences between human and animal immune systems and the challenges of long-term evaluation present limitations for animal studies, making alternative approaches necessary. The objectives of this study were to develop a mechanism-based quantitative systems pharmacology (QSP) model to depict immune active phase of chronic HBV, to predict the disease progression of HBV based on the QSP model, to confirm the dynamic profiles including interactions of biomarkers, and ultimately to suggest an appropriate timing for treatment initiation. To achieve this, we constructed an ODEbased model structure and selected parameters based on a comprehensive literature review. In vitro and animal experimental data were used to estimate biomarker dynamics. Model predictions were verified by comparison with clinical biomarker data observed in blood of real-world HBV patients and knock-out analysis was performed to assess model validity. In conclusion, our present study suggested QSP modeling as an alternative for disease models through applying QSP modeling approach to depict HBV progression. Ultimately, our QSP model might contribute to predicting and selecting appropriate treatment approaches through evaluating effectiveness and risks of drug therapy by integrating clinical data and pharmacokinetic-pharmacodynamic modeling.

With the growing importance of patient-centered approach in drug development, the U.S. Food and Drug Administration (FDA) has taken the lead in legalizing the systematic collection and regulatory reflection of patient perspectives. This study aimed to analyze Patient-Focused Drug Development (PFDD) meetings and Patient Listening Sessions (PLS) as representative patient engagements in the U.S. Reports from the FDA website were collected and reviewed for operational characteristics, participant profiles, and disease areas. Changes in operational characteristics were analyzed by year, and differences in disease areas were analyzed using Chi-square test. A total of 198 reports available as of January 23, 2025, were reviewed. The number of External-led PFDD meetings and PLSs rapidly surpassed those of FDA-led meetings. Most meetings (99%) adopted virtual or hybrid formats, enhancing the accessibility. In both meetings, external-led meetings were more likely to address rare diseases compared to FDA-led meetings (PFDD p-value = 0.0005; PLS p-value = 0.0031). These findings indicate that the FDA actively encourages patient engagement. External-led format expands opportunities for patients, particularly those with rare diseases, to communicate with regulators. For patient-centered approach, this study addresses the need of structured guidance for systematically collecting and incorporating patient perspectives into Korean regulatory context.

This study aims to provide an in-depth analysis of the current status, future directions, and regulatory and industrial significance of the Technical Documents developed by the Working Groups of the International Medical Device Regulators Forum (IMDRF). As an international consultative body dedicated to lowering market entry barriers caused by disparate regulations among member states and achieving harmonization, the IMDRF establishes in fact global standards. Drawing on the official IMDRF website and recently published technical documents, this research systematically analyzes working items across eight key sectors, including Adverse Event Terminology (AET), Artificial Intelligence/Machine Learning (AI/ML), and Software as a Medical Device (SaMD). The findings confirm that IMDRF technical documents exert a substantial influence on medical device development and quality management systems (QMS), independent of whether they have been formally codified into law by individual member nations. Specifically, these documents contribute to streamlining multi-country licensing procedures, enhancing regulatory review efficiency, and ultimately strengthening product competitiveness. Based on this analysis, this study suggests that the domestic medical device industry and regulatory authorities must establish proactive response strategies, including the continuous monitoring of IMDRF trends and the preemptive adoption of these international technical standards.

The expanding globalization of pharmaceutical manufacturing necessitates rigorous quality oversight for imported drugs. As comprehensive inspections of all overseas sites are resource-prohibitive, implementing a strategic risk-based approach is imperative. This study aims to analyze and compare inspection target selection models and derive policy implications for the Ministry of Food and Drug Safety (MFDS) in Korea by analyzing international standards, including the International Council for Harmonisation (ICH) and the Pharmaceutical Inspection Co-operation Scheme (PIC/S). We compared the risk assessment algorithms and data management systems of the U.S. Food and Drug Administration (FDA) and the European Medicines Agency (EMA) with the status of the MFDS. The findings indicate that unlike the FDA and EMA, which utilize dynamic models and integrated platforms such as the Site-Selection Model (SSM) and EudraGMDP (European Union Drug Regulating Authorities – Good Manufacturing and Distribution Practices) to reflect intrinsic product risks and real-time compliance history, the MFDS does not publicly disclose a quantitative scoring algorithm or weighting scheme, and its inspection-related data remain in fragmented systems. Consequently, this study suggests policy considerations for improving the current system. Furthermore, we suggest establishing an integrated data platform and a dedicated department to enhance inspection efficiency. These measures are expected to strengthen the scientific validity and regulatory rigor of drug safety management in Korea.

This study compares the adoption of three key post-approval CMC change management tools defined in ICH Q12—Established Conditions (EC), Post-Approval Change Management Protocol (PACMP), and Product Lifecycle Management (PLCM)—across five regulatory authorities: the United States (FDA), the European Union (EMA), Japan (MHLW/PMDA), Canada (HC), and the Republic of Korea (MFDS). A comparative analysis of laws and guidelines published through January 2026 was conducted, focusing on risk-based change categorization, the regulatory integration of Q12 tools, and the existence of pilot programs. While all five authorities apply riskbased principles, the extent of Q12 tool adoption varies considerably. The United States has institutionalized all three tools through legislation and internal policies. The EU and Japan have substantially advanced PACMP implementation, whereas Canada remains in a phased adoption stage. Korea operates a risk-based, CTD-linked review system but lacks explicit legal or procedural frameworks for any of the three tools. This study proposes a phased adoption strategy through pilot programs and the extension of Korea's pre-submission consultation system to post-approval change management, thereby enhancing regulatory predictability and strengthening the global competitiveness of the Korean pharmaceutical industry.

This study evaluated the regulatory impact and limitations of the Post-Approval Change Management Protocol (PACMP), introduced in ICH Q12, through analysis of industrial case studies. Nine cases of PACMP application were selected from official regulatory documents and public industry presentations. The cases included manufacturing site changes, raw material and process changes, analytical procedure changes, and shelf-life extension. Both single-regulator pilots and ICMRA multi-regulator collaborative assessment pilots were analyzed, comparing each case by regulatory jurisdiction, change type, reporting category changes, and review timeline. The analysis showed that PACMP's effects varied by change characteristics. For changes with long data-generation periods and high regulatory complexity, meaningful regulatory efficiency gains were observed: in a singleregulator pilot, the typical 12-month prior approval review was reduced to approximately three months, while a multi-regulator collaborative pilot reported an approximately five-month reduction. Some cases further demonstrated PACMP's potential as an extended change management framework applicable across multiple products and sites. In contrast, for changes with short data-generation periods such as analytical procedure changes, PACMP's benefits were limited. These findings suggest PACMP's effects vary by change type, and effective implementation requires strategic application supported by a mature Pharmaceutical Quality System (PQS) and regulatory cooperation frameworks.

Legacy drugs developed prior to the implementation of Quality by Design (QbD) typically rely on single set-points without clearly defined design spaces, which often complicates lifecycle management and the transition to the Common Technical Document (CTD) format. The inherent lack of variance in commercial production data further limits the ability to establish correlations between critical process parameters (CPPs) and critical quality attributes (CQAs). To address these challenges, this study proposes a practical framework that integrates retrospective QbD with continued process verification (CPV). Key parameters were evaluated through quality risk assessment (QRA) and statistical analysis of 70 commercial batches. Comparative analysis between normal and process variation groups was conducted using Welch’s t-test and the Mann-Whitney U test, while nonparametric process capability indices (Ppk) were applied to non-normal data. To compensate for the limited data variance, effect sizes (Hedges’ g, r) were calculated to ensure analytical rigor. By synthesizing these quantitative statistical results with a deep mechanistic understanding of the process, parameters were classified into critical process parameters (CPPs) and non-critical process parameters (PPs) based on risk assessment supported by statistical evidence. Initial proven acceptable ranges (PARs) were proposed within the historical operating ranges to ensure a Ppk ≥ 1.33. This framework provides a practical strategy for the CTD transition of legacy products by leveraging empirical production data, thereby minimizing the need for extensive prospective experimentation. The identified CPPs and PARs thereby serve as a foundation for prioritized monitoring in subsequent CPV stages.

Although package inserts are essential for the safe and effective use of medicines, they have often been criticized for poor legibility and readability, especially in South Korea. This study compares regulatory frameworks for package inserts for consumers in South Korea, the European Union, the United States, Canada, and Australia. We reviewed national laws, regulations, and guidelines, focusing on mandatory requirements and recommendations for formatting standards, plain language, content structure, and verification procedures. We found that, unlike South Korea, the other four jurisdictions use a two-tiered system that separates information for healthcare professionals and consumers, and they provide standardized templates, detailed formatting criteria, and verification mechanisms for package inserts for consumers. In contrast, South Korea does not provide separate package inserts for consumers and regulates only the minimum font size and line spacing, resulting in limited legibility standards. For readability, South Korea offers only a list of plain-language terms and lacks verification procedures, such as pre-market evaluation, to ensure package inserts are understandable. To improve the safe and effective use of medicines, the regulatory framework should specify detailed legibility criteria, introduce comprehension-enhancing measures through a stepwise approach tailored to the Korean context, and establish a dedicated unit to conduct integrated pre- and post-market evaluations.