> For the complete documentation index, see [llms.txt](https://docs.snomed.org/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.snomed.org/snomed-ct-practical-guides/snomed-ct-data-analytics-guide/7-task-oriented-analytics/7.2-population-based-analytics/7.2.2-pharmacovigilance.md).
# Pharmacovigilance
Pharmacovigilance is the collection, detection, assessment, monitoring and prevention of adverse effects with pharmaceutical products. It is concerned with identifying the hazards associated with pharmaceutical products and minimizing the risk of any harm that may come to patients. An important part of pharmacovigilance is postmarketing surveillance, which monitors the safety of a pharmaceutical drug or medical device after it has been released on the market. Since drugs are approved on the basis of clinical trials, which involve relatively small numbers of people, postmarketing surveillance plays an important part in further refining, confirming or denying the safety of a drug in the general population.
Pharmacovigilance uses a number of data sources to assess and monitor the safety of licensed drugs, including clinical trial data, medical literature, spontaneous reporting databases, prescription events, electronic health records, and patient registries. Data mining of large volumes of clinical data can be used to highlight potential safety concerns. However, current mechanisms to analyze this data is often both costly and insensitive.
The availability of large datasets of richly encoded SNOMED CT data within longitudinal healthcare records can greatly assist pharmacovigilance. Where SNOMED CT is not used natively to capture clinical data, free text narrative and other code systems may be mapped to SNOMED CT to support a homogeneous approach to querying across diseases, signs and symptoms, lab results, medications, devices, procedures, allergies, adverse reactions, body sites and substances. SNOMED CT's polyhierarchy and defining relationships, which provide links between these domains provide a rich source of meaning-based information across which queries can be performed.
Many drug regulatory authorities and pharmaceutical companies currently use the Medical Dictionary for Regulatory Activities (MedDRA) to classify adverse drug events. MedDRA is an international standard adverse event classification used from pre-marketing through to post-marketing activities. However, as MedDRA was not designed to support routine clinical data collection, its penetration into clinical systems is limited. Therefore mapping from SNOMED CT to MedDRA would enable both styles of analysis and reporting to be performed from the same clinical data. The UK Medicines and Healthcare products Regulatory Agency (MHRA) is working (with input from the MedDRA Maintenance and Support Services Organization) to develop a mapping from a subset of SNOMED CT to MedDRA for this purpose.
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