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Related Concept Videos

Dosage Regimen Designs: Nomograms and Tabulations01:23

Dosage Regimen Designs: Nomograms and Tabulations

Nomograms and tabulations are vital tools used by clinicians to design accurate and individualized dosage regimens. These instruments provide a straightforward method for adjusting dosages based on individual patient characteristics, including age, weight, and physiological condition. The foundation of a drug's nomogram is population pharmacokinetic data collected and analyzed using specific models. This data simplifies complex equations, presenting them diagrammatically or tabularly for easy...
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Individualization in dosing regimens is the customization of medication doses for individual patients. Its necessity arises from the goal of maximizing therapeutic benefits while minimizing risks. This approach is pivotal because human responses to drugs can vary widely; what is effective for one person may be inadequate or excessive for another. Interpatient (intersubject) variability refers to differences in drug responses between individuals, while intrapatient (intrasubject) variability...
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Therapeutic Drug Monitoring (TDM) is a clinical practice that measures specific drug levels in a patient's blood or body tissues to tailor drug therapy effectively. This monitoring is critical for managing drugs with narrow therapeutic indices like digoxin and phenytoin, ensuring they are both safe and effective. For instance, monitoring theophylline levels in asthma patients involves precision and sensitivity to adjust doses according to individual responses to therapy, ensuring efficacy and...
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Designing a dosage regimen, which refers to the manner of drug administration, is a complex process involving the selection of drug dose, route, and frequency. This process is underpinned by pharmacokinetic parameters derived from tests and population averages. These parameters are then tailored to patient-specific variables such as diagnosis, demographics, and allergy status. Once therapy commences, therapeutic response monitoring is critical and achieved through clinical and physical...
Therapeutic Drug Monitoring: Overview and Classification01:16

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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...
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A drug dosage regimen describes the specific instructions and schedule for administering a drug to a patient. It considers factors such as drug dosage, frequency, route of administration, and duration of treatment. Designing an appropriate dosage regimen for a patient aims to achieve a target drug concentration at the site of action.
Typically, the starting dose and dosing interval are guided by the manufacturer's recommendations based on clinical trials conducted during and after drug...

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Updated: Jun 2, 2026

Validated LC-MS/MS Panel for Quantifying 11 Drug-Resistant TB Medications in Small Hair Samples
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RxMap: an LLM-assisted tool for medication normalization.

Eero Korpela1, Leah H Rubin2,3,4,5, Raha M Dastgheyb2

  • 1Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD, United States.

JAMIA Open
|June 1, 2026
PubMed
Summary
This summary is machine-generated.

RxMap accurately normalizes free-text medication data to standardized RxNorm concepts using a novel pipeline. This system enhances research by providing scalable, automated, and reproducible medication data processing.

Keywords:
RxNormdata harmonizationlarge language modelsmedical concept normalization

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Last Updated: Jun 2, 2026

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Published on: December 6, 2024

Area of Science:

  • Biomedical Informatics
  • Computational Pharmacology
  • Health Services Research

Background:

  • Accurate normalization of free-text medication data is crucial for research.
  • Existing methods may lack accuracy and scalability for diverse medication strings.

Purpose of the Study:

  • To develop RxMap, a system for accurate, researcher-oriented normalization of medication strings to RxNorm ingredient-level concepts.
  • To provide a freely available tool for improving medication data standardization.

Main Methods:

  • RxMap employs a pipeline combining deterministic RxNorm candidate generation with large language model (LLM)-assisted parsing.
  • It normalizes raw medication strings to RxNorm ingredient-level (IN/MIN) concepts and assigns ATC codes.
  • An optional review interface allows for transparent human oversight.

Main Results:

  • Evaluation on over 22,000 unique medication strings showed significant improvements compared to deterministic matching alone.
  • RxMap achieved RxCUI-level precision, recall, and F1-score of 0.969, 0.964, and 0.966, respectively.
  • Similar gains were observed at the ingredient level, demonstrating enhanced accuracy.

Conclusions:

  • RxMap offers accurate and scalable normalization of free-text medication data to RxNorm concepts.
  • The system is fully automated with optional review, supporting reproducible research workflows.
  • It provides a valuable resource for researchers working with medication data.