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Related Concept Videos

Pharmacovigilance01:19

Pharmacovigilance

Post-marketing surveillance is a critical component of pharmaceutical regulation, often uncovering unanticipated adverse drug reactions (ADRs) once a drug is widely used over an extended period.
This process, termed pharmacovigilance, aims to detect, evaluate, and minimize harmful effects related to medication use. The data collection for pharmacovigilance depends on spontaneous reporting systems, where healthcare professionals or patients voluntarily report suspected ADRs.
In some cases, there...
Pharmaceutical Alternatives: Polymorphic Form-Related and Particle Size-Related Therapeutic Nonequivalence01:27

Pharmaceutical Alternatives: Polymorphic Form-Related and Particle Size-Related Therapeutic Nonequivalence

Changes in polymorphic forms can significantly influence the bioavailability of poorly soluble drugs. Although the FDA defines pharmaceutical equivalence based on having the same active ingredient, dosage form, and route of administration, it does not automatically disqualify products with different polymorphic forms. This means two products with different polymorphs can still be deemed pharmaceutically equivalent. However, polymorphic differences can affect properties like wettability,...
Therapeutic Drug Monitoring: Overview and Classification01:16

Therapeutic Drug Monitoring: Overview and Classification

Therapeutic Drug Monitoring (TDM) is a clinical practice that measures specific drug levels in a patient's blood at designated intervals to ensure the drug concentration stays within a therapeutic range. This monitoring is crucial for optimizing individual dosage regimens, enhancing therapeutic efficacy, and minimizing drug-related toxicity. TDM is vital for drugs with narrow therapeutic windows, significant variability in pharmacokinetics, and a clear correlation between plasma levels and...
Drug Nomenclature01:17

Drug Nomenclature

During the development of a new pharmaceutical, the manufacturer initially assigns a code name to the drug. Once approved, the drug receives a United States Adopted Name (USAN)—a generic, nonproprietary designation. Upon being listed in the United States Pharmacopeia, this nonproprietary name becomes the drug's official name. Additionally, the manufacturer assigns a proprietary name or trademark, which serves as the brand name under which the drug is marketed. It is worth noting that the same...
Dosage Regimens: Partial Pharmacokinetic Parameters01:01

Dosage Regimens: Partial Pharmacokinetic Parameters

It is not uncommon for complete drug pharmacokinetic profiles to remain elusive in pharmacokinetics. This necessitates certain educated assumptions by pharmacokineticists to determine appropriate dosage regimens without comprehensive pharmacokinetic data from animal or human studies. One prevalent assumption is setting the bioavailability factor, denoted as F, to 1 or 100%. This assumption caters to the scenario where a drug doesn't achieve full systemic absorption, resulting in the patient...
Structure-Activity Relationships and Drug Design01:28

Structure-Activity Relationships and Drug Design

Drug design is a dynamic field that involves discovering and developing new medications based on specific biological targets. This process heavily relies on structure-activity relationships (SAR) and quantitative structure-activity relationships (QSAR) to guide the design and optimization of efficient drugs.
SAR studies the intricate relationship between a drug's chemical structure and biological activity. It focuses on understanding how modifications to a drug's structure can influence its...

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Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
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Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

Grouping pharmacovigilance terms with semantic distance.

Marie Dupuch1, Magnus Lerch, Anne Jamet

  • 1Université Pierre et Marie Curie - Paris 6, Paris F-75006, France.

Studies in Health Technology and Informatics
|September 7, 2011
PubMed
Summary

This study introduces an automated method for grouping adverse drug reaction (ADR) terms using semantic distance. This approach aims to improve the detection of safety signals and enhance pharmacovigilance efforts.

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Area of Science:

  • Pharmacovigilance and drug safety research.
  • Computational linguistics and natural language processing in healthcare.

Background:

  • Adverse drug reactions (ADRs) require continuous monitoring for patient safety.
  • Existing methods for ADR detection, including Standardised MedDRA Queries (SMQs), have limitations in sensitivity and coverage.
  • Grouping of ADR terms can enhance the detection of safety signals.

Purpose of the Study:

  • To develop an automatic method for creating effective groupings of MedDRA terms.
  • To improve the identification of previously unknown adverse drug reactions.
  • To address limitations in current Standardised MedDRA Queries (SMQs) for safety signal detection.

Main Methods:

  • Utilized statistical algorithms and semantic distance metrics between Medical Dictionary for Regulatory Activities (MedDRA) terms.
  • Developed an automated approach for generating term groupings.
  • Conducted experiments to evaluate the performance of the proposed method.

Main Results:

  • The proposed automatic method for term grouping demonstrated promising precision.
  • The method achieved an acceptable level of recall in identifying relevant ADR terms.
  • Experimental results suggest improved capabilities for safety signal detection.

Conclusions:

  • The developed automatic method offers a novel way to create term groupings for pharmacovigilance.
  • This approach has the potential to enhance the effectiveness of ADR detection and safety signal analysis.
  • Further research can build upon this method to refine safety monitoring systems.