SeltaSquare

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Outlining global regulatory shifts, including ICH M14, and design principles for RMP-based RWD safety studies

 

SeltaSquare (CEO Minkyung Shin), an AI-driven pharmacovigilance (PV) and real-world evidence (RWE) company, announced on the 13th that it participated as a Diamond Sponsor in the 2026 KoNECT International Conference (KIC 2026) at Lotte Hotel Seoul and hosted a luncheon session.

The luncheon session was held on the first day of the conference, the 13th, in Crystal Ballroom A on the 2nd floor of Lotte Hotel Seoul, under the theme “From RMP to Regulatory-Grade RWE.” Hyejung Lee, Head of SeltaSquare’s Integrated Evidence (IE) Strategy Division, spoke at the session. She shared study design and execution strategies for generating RWE that can support regulatory decision-making amid a changing global regulatory environment.

Global regulatory authorities increasingly emphasize generating safety evidence in post-marketing studies based on clear research questions and fit-for-purpose data.

The ICH M14 guideline, which concerns the use of real-world data for drug safety assessment, has entered the implementation phase, and the U.S. FDA operates an RWE Program to improve regulatory acceptability.

Japan recently issued guidelines for conducting post-marketing database studies, shifting the paradigm from uniform post-marketing surveillance to research-question-driven studies. In Korea, the re-examination system was abolished in February 2025, and post-marketing safety management has been consolidated around the Risk Management Plan (RMP). As a result, fit-for-purpose real-world data (RWD) and sound study design are becoming increasingly important.

In her presentation, Head Lee addressed the key requirements RWD studies must meet to support regulatory decision-making in this changing landscape. She explained the principle of selecting data sources, study designs, and analytical methods suited to the research question, and of transparently assessing study limitations such as bias and confounding.

In particular, she described RWD study design approaches that scientifically evaluate treatment effects and clinical outcome measures in real-world clinical practice, so that the findings can inform regulators’ benefit-risk assessments and discussions.

SeltaSquare also introduced the current status of its AI-based RWD safety studies using structured and unstructured healthcare data.

The company is developing in-house AI technology capable of detecting unstructured clinical records (clinical narratives) that are easily missed by diagnosis codes alone. Building on this, it is advancing natural language processing (NLP)-based detection technology to analyze post-marketing safety information efficiently, and is currently reviewing its applicability across a range of disease areas.

Through the luncheon session, Head Lee emphasized that “as the global regulatory environment rapidly shifts toward purpose-driven, research-question-based studies and broader use of RWE, RMP-based RWD safety studies are a core foundation supporting benefit-risk management across the entire product lifecycle.”

She added, “RWE that can be used for regulatory decision-making is not secured by data volume alone; it depends on the research question and study design that start from the RMP.” She continued, “Based on AI technology spanning both structured and unstructured data, SeltaSquare will build practical safety evidence.”

Original article: [약업신문]셀타스퀘어, 2026 KIC서 ‘RMP 기반 RWD 안전성 연구의 규제 활용 전략’ 발표