{"id":43601,"date":"2026-09-09T13:54:42","date_gmt":"2026-09-09T13:54:42","guid":{"rendered":"https:\/\/eurekainfomed.it\/en\/?p=43601"},"modified":"2026-09-09T13:54:42","modified_gmt":"2026-09-09T13:54:42","slug":"how-meddra-works-in-pharmacovigilance","status":"publish","type":"post","link":"https:\/\/eurekainfomed.it\/en\/how-meddra-works-in-pharmacovigilance\/","title":{"rendered":"How MedDRA works in pharmacovigilance"},"content":{"rendered":"

A suspected adverse reaction report can be received using very different wording: \u201cstomach pain,\u201d \u201cepigastric pain,\u201d \u201cgastritis,\u201d or \u201cgastrointestinal event.\u201d Understanding how MedDRA works<\/strong> means transforming this linguistic variability into data that can be compared, analyzed, and used in regulatory pharmacovigilance processes.<\/p>\n

\n

MedDRA is not simply a dictionary of medical terms. It is a standardized clinical terminology developed to classify information related to the safety of medicinal products and, in specific contexts, medical devices. Its correct application affects the quality of case reports, aggregated signal analysis, the preparation of periodic safety documents, and the consistency of communication between local and global functions and competent authorities.<\/p>\n

What MedDRA is and why it is used<\/h2>\n

MedDRA, the acronym for Medical Dictionary for Regulatory Activities<\/strong>, is the international terminology used to code regulatory medical data. It includes adverse events, adverse reactions, therapeutic indications, medical history, medical procedures, diagnostic test results, and other concepts relevant to safety.<\/p>\n

Its operational value comes from standardization. Information collected from patients, healthcare professionals, scientific literature, support programs, or digital channels may be expressed using different terminology and varying levels of detail. MedDRA makes it possible to represent this information through controlled terms and codes while preserving, as much as possible, the meaning of the original data.<\/p>\n

This standardization allows comparison of cases originating from different countries, clinical studies, sources, and time periods. It also makes it possible to query safety databases in a structured way, identify clinically significant patterns, and generate consistent analyses for signal management and regulatory reporting activities.<\/p>\n

The terminology is multilingual and updated regularly. This aspect is essential: a reliable coding process cannot be separated from version management and assessment of the impact that updates may have on historical data and ongoing analyses.<\/p>\n

How MedDRA works: the hierarchical structure<\/h2>\n

MedDRA is organized according to a five-level hierarchy. Each level serves a specific purpose and makes it possible to move from detailed clinical information recorded in an individual case to an aggregated view useful for safety analysis.<\/p>\n

The broadest level is the System Organ Class (SOC)<\/strong>. It represents a high-level category generally based on body systems, organs, etiology, or purpose. Examples include \u201cGastrointestinal disorders,\u201d \u201cSkin and subcutaneous tissue disorders,\u201d and \u201cNervous system disorders.\u201d<\/p>\n

Below the SOC are the High Level Group Terms (HLGTs)<\/strong>, which group related clinical areas. These are followed by High Level Terms (HLTs)<\/strong>, which bring together related Preferred Terms based on anatomical, pathological, or clinical characteristics. The Preferred Term (PT)<\/strong> is the level normally used for analysis and reporting. It represents a single standardized medical concept, such as \u201cNausea,\u201d \u201cHeadache,\u201d or \u201cRash.\u201d<\/p>\n

The most specific level is the Lowest Level Term (LLT)<\/strong>. LLTs include synonyms, lexical variants, colloquial expressions, and more or less specific formulations linked to a PT. During data entry, the coder usually selects the LLT that best reflects the verbatim, namely the wording provided by the source. The system then links that LLT to the corresponding PT.<\/p>\n

This structure prevents two opposite errors: losing the detail of the original report or maintaining data that are so heterogeneous that meaningful analysis becomes impossible.<\/p>\n

Multiaxiality and the Primary SOC<\/h2>\n

A PT may be linked to more than one SOC. This mechanism, known as multiaxiality<\/strong>, reflects the fact that some medical concepts may be relevant to more than one organ system or clinical area.<\/p>\n

To ensure consistency in cumulative analyses, however, each PT has a predefined Primary SOC<\/strong>. The Primary SOC determines where the term is counted by default in aggregate analyses. The other links remain available for broader or more targeted searches.<\/p>\n

Multiaxiality requires careful management when creating queries and tables. If it is not handled properly, it can generate duplicate counts or inconsistent interpretations of event incidence. It is therefore not sufficient to extract all terms belonging to a SOC. The classification logic being used must be understood and the analytical approach documented.<\/p>\n

From clinical narrative to coded term<\/h2>\n

MedDRA coding always starts with the quality of the available information. A complete, contextualized, and clinically understandable verbatim facilitates appropriate term selection. Conversely, vague wording requires caution and does not justify interpretations that are not supported by the source.<\/p>\n

If a patient reports \u201csevere stomach burning after taking the medicine,\u201d the coder must determine whether the documented concept corresponds to a term such as \u201cPyrosis\u201d or whether additional information supports a different clinical description. If the report simply states \u201cstomach problems,\u201d selecting an overly specific term would introduce an unjustified assumption.<\/p>\n

The fundamental principle is to code what is reported, not what is presumed to have occurred. Clinical assessments, follow-up requests, and source clarification activities follow a separate but complementary process to coding.<\/p>\n

In complex cases, a single narrative may contain multiple codable concepts, including symptoms, diagnoses, outcomes, laboratory results, and exposure circumstances. The selection depends on company procedures, approved coding conventions, and the context of the case. A confirmed diagnosis may make it unnecessary to code all the individual signs and symptoms that comprise the clinical picture unless they are independently relevant. This is an area where medical judgment and procedural governance make a significant difference.<\/p>\n

Coding is not a literal translation<\/h2>\n

In international organizations, MedDRA is often perceived as a bridge between different languages. While this is true, reducing it to a translation tool is misleading. The coder must understand the clinical concept, verify the meaning of the verbatim, and select the term that represents it accurately according to applicable conventions.<\/p>\n

When required, the specialized translation of a report must be traceable and consistent with the source documentation. A linguistic error can propagate through coding, narratives, listings, and aggregate analyses. For this reason, collaboration among Pharmacovigilance, Medical Writing, Medical Information, and scientific translation functions is particularly valuable when data flows involve multiple markets and multiple reporting channels.<\/p>\n

Quality, versioning, and operational consistency<\/h2>\n

New versions of MedDRA are released regularly. Each update may introduce new terms, modify hierarchical relationships, or revise existing wording. Companies must therefore clearly define which version is used across different systems and processes, from individual case management to the preparation of periodic reports.<\/p>\n

Version management is not merely an IT detail. Using different versions without a transition plan can compromise the comparability of longitudinal analyses. For example, a recently introduced PT may not be available in historical data and may require recoding activities or a documented strategy for trend interpretation.<\/p>\n

An effective quality system includes updated procedures, initial and ongoing coder training, risk-based quality controls, and management of recurring coding decisions. Internal coding conventions are particularly important when MedDRA offers multiple plausible options. They transform potentially subjective decisions into repeatable and verifiable criteria.<\/p>\n

Quality controls may focus on serious cases, terms with significant regulatory impact, unexpected coding choices, discrepancies between the verbatim and the PT, and complex therapeutic areas. There is no universally correct review frequency. It depends on case volume, team maturity, product type, system architecture, and the results of previous reviews.<\/p>\n

MedDRA in safety analyses<\/h2>\n

Accurate coding supports activities that go far beyond entering data into a database. MedDRA PTs and hierarchies are used in line listings, cumulative tables, SOC analyses, disproportionality assessments, signal detection activities, and sections of documents such as PSURs, PBRERs, DSURs, and RMPs.<\/p>\n

For certain analytical purposes, Standardised MedDRA Queries (SMQs)<\/strong> are used. These are predefined groupings of terms related to conditions or syndromes of particular interest. SMQs can facilitate the identification of potentially relevant cases, but they do not replace clinical review. A broad search may increase sensitivity and capture non-specific cases, while a narrow search improves specificity but may exclude useful information. The choice depends on the safety question being investigated and should be justified.<\/p>\n

Customized MedDRA Queries<\/strong> may also be appropriate, provided they are developed, validated, and documented rigorously. In both cases, the quality of the output depends on the quality of the initial coding and on a correct understanding of the hierarchy.<\/p>\n

A safeguard for both data and decision-making<\/h2>\n

The correct application of MedDRA requires terminological expertise, clinical awareness, knowledge of procedures, and the ability to work with traceable data. It is not merely an administrative activity. Every coding decision can influence how an event is searched, aggregated, and evaluated over time.<\/p>\n

For understaffed teams, expanding portfolios, or processes involving multiple markets, specialist support can ensure continuity without reducing internal control. Eureka InfoMed supports pharmacovigilance functions through a structured approach that integrates scientific, documentary, and regulatory expertise.<\/p>\n

Clear coding does not eliminate clinical complexity, but it makes it manageable. And it is precisely from clear, consistent, and verifiable data that sound safety decisions can emerge.<\/p>\n

Sources<\/strong><\/p>\n

    \n
  1. International Council for Harmonisation (ICH). Medical Dictionary for Regulatory Activities (MedDRA)<\/em>.<\/li>\n
  2. MedDRA Maintenance and Support Services Organization (MSSO). MedDRA Introductory Guide<\/em>.<\/li>\n
  3. MedDRA Maintenance and Support Services Organization (MSSO). MedDRA Term Selection: Points to Consider<\/em><\/li>\n
  4. European Medicines Agency (EMA). Good Pharmacovigilance Practices (GVP), Module VI \u2013 Collection, Management and Submission of Reports of Suspected Adverse Reactions to Medicinal Products<\/em>.<\/li>\n<\/ol>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

    A suspected adverse reaction report can be received using very different wording: \u201cstomach pain,\u201d \u201cepigastric pain,\u201d \u201cgastritis,\u201d or \u201cgastrointestinal event.\u201d Understanding how MedDRA works means transforming this linguistic variability into…<\/p>\n","protected":false},"author":16,"featured_media":43602,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[25,4],"tags":[],"class_list":["post-43601","post","type-post","status-publish","format-standard","has-post-thumbnail","category-pharmacovigilance","category-news"],"yoast_head":"\nHow MedDRA works in pharmacovigilance - Eureka Info Med<\/title>\n<meta name=\"description\" content=\"Learn how MedDRA works and how standardized medical coding supports pharmacovigilance, safety analysis, signal detection, and regulatory reporting.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/eurekainfomed.it\/en\/how-meddra-works-in-pharmacovigilance\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"How MedDRA works in pharmacovigilance - 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