Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Pharmacodynamic Models: Overview

Pharmacodynamic Models: Overview

Pharmacodynamic (PD) responses describe the interaction between a drug and its biological target, culminating in a physiological effect. These responses can be classified into different types: continuous variables, such as blood glucose levels; categorical outcomes, like survival rates; and time-to-event metrics, such as disease progression. Understanding and modeling PD responses are critical for optimizing drug efficacy and safety.PD models describe the relationship between drug concentration...

Pharmacokinetic Models: Overview

Pharmacokinetic Models: Overview

Pharmacokinetic models utilize mathematical analysis to achieve a detailed quantitative understanding of a drug's life cycle within the body. They are instrumental in simulating a drug's pharmacokinetic parameters, predicting drug concentrations over time, optimizing dosage regimens, linking concentrations with pharmacologic activity, and estimating potential toxicity.
There are three primary types of models: empirical, compartment, and physiological. Empirical models, with minimal assumptions,...

Pharmacokinetic–Pharmacodynamic Relationship: Model Components

Pharmacokinetic–Pharmacodynamic Relationship: Model Components

Pharmacokinetic-pharmacodynamic (PK–PD) modeling is essential in drug development and clinical pharmacology. It provides a quantitative framework to predict drug behavior and response over time. This approach integrates pharmacokinetics (PK), which describes the drug's absorption, distribution, metabolism, and excretion, with pharmacodynamics (PD), which characterizes the drug’s biological effects and mechanisms of action.The disposition kinetics of a drug determine its plasma...

Impact of Pharmacokinetic–Pharmacodynamic Models: Regulatory Decisions

Impact of Pharmacokinetic–Pharmacodynamic Models: Regulatory Decisions

PK–PD modeling has significantly influenced FDA regulatory decisions, particularly drug approval, dosage optimization, and labeling. These models integrate pharmacokinetics (PK) and pharmacodynamics (PD) to predict drug behavior and effects, aiding in optimizing dosing regimens and enhancing the probability of clinical trial success.One notable example is Nesiritide (Natrecor®), a recombinant human brain natriuretic peptide for treating acute decompensated congestive heart failure (CHF).

Drug Administration and Therapy Phases: Overview

Drug Administration and Therapy Phases: Overview

Drugs, the chemical agents used in diagnosing, treating, or preventing diseases, undergo a four-phase process of development: pharmaceutic, pharmacokinetics, pharmacodynamics, and therapeutic.
The pharmaceutical phase focuses on leveraging the physicochemical properties of the drug to design and manufacture an effective product. Variants include orally administered tablets or capsules, topical creams or ointments, and parenteral-delivery solutions or emulsions.
The pharmacokinetic phase...

Dosage Regimen Designs: Nomograms and Tabulations

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...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Effect of free trade agreements on pharmaceutical market competition: The case of the 2009 US-Peru free trade agreement and its implementation as national drug policy.

Health policy OPEN·2023

Same author

Trade agreements and drug access: assessment of the impact of the 2009 Peruvian new drug policy on anti-infectives registration and availability.

Journal of pharmaceutical policy and practice·2018

Same author

The Exploitation of Drug Users.

Substance use & misuse·2015

Same author

Seeing is believing, looks are deceiving: what does one see in images of drugs and drug use(rs)?

Substance use & misuse·2014

Same author

Drugs on the Internet, Part V: absinthe, return of the emerald mask.

Substance use & misuse·2013

Same author

Drugs on the internet, part IV: Google's Ngram viewer analytic tool applied to drug literature.

Substance use & misuse·2013

Search research articles

Related Experiment Video

Updated: May 11, 2026

A Bilingual Computational Workflow for Identifying Potential PLK1 Inhibitors in American Sign Language and English

A Bilingual Computational Workflow for Identifying Potential PLK1 Inhibitors in American Sign Language and English

Published on: April 3, 2026

Pharmaceutical pictograms: a model for development and testing for comprehension and utility.

Michael Montagne¹

¹Massachusetts College of Pharmacy & Health Sciences, 179 Longwood Ave., Boston, MA 02115, USA.

Research in Social & Administrative Pharmacy : RSAP

|May 18, 2013

Summary

Pictograms improve medication understanding and adherence, but comprehension varies. Patient counseling on pictogram use significantly enhances their effectiveness for better drug information recall and use.

Keywords:

Medication literacy Pictograms Visual aids

More Related Videos

Rapid Analysis and Exploration of Fluorescence Microscopy Images

Rapid Analysis and Exploration of Fluorescence Microscopy Images

Published on: March 19, 2014

Pharmacophore Modeling for Targets with Extensive Ligand Libraries: A Case Study on SARS-CoV-2 Mpro

Pharmacophore Modeling for Targets with Extensive Ligand Libraries: A Case Study on SARS-CoV-2 Mpro

Published on: September 26, 2025

Related Experiment Videos

Last Updated: May 11, 2026

A Bilingual Computational Workflow for Identifying Potential PLK1 Inhibitors in American Sign Language and English

A Bilingual Computational Workflow for Identifying Potential PLK1 Inhibitors in American Sign Language and English

Published on: April 3, 2026

Rapid Analysis and Exploration of Fluorescence Microscopy Images

Rapid Analysis and Exploration of Fluorescence Microscopy Images

Published on: March 19, 2014

Pharmacophore Modeling for Targets with Extensive Ligand Libraries: A Case Study on SARS-CoV-2 Mpro

Pharmacophore Modeling for Targets with Extensive Ligand Libraries: A Case Study on SARS-CoV-2 Mpro

Published on: September 26, 2025

Area of Science:

Health literacy
Pharmaceutical sciences
Human-computer interaction

Background:

Growing concerns regarding patients' medication literacy skills necessitate improved information materials.
Effective drug use and patient understanding are paramount in healthcare.

Purpose of the Study:

To review existing pictogram development projects.
To propose a model for pharmaceutical pictogram development and testing.
To enhance comprehension and use of medication information.

Main Methods:

Summarizing previous pictogram development efforts in healthcare, pharmacy, engineering, and safety.
Assessing pictogram impact on knowledge acquisition, information retention, and adherence.
Analyzing comprehension and recall levels of various pictogram types.

Main Results:

Pictograms are crucial for enhancing medication information comprehension, recall, and adherence.
Many pictograms exhibit low comprehension levels, with inconsistent impacts on medication knowledge.
Patient counseling on pictogram meaning and use significantly boosts their effectiveness.

Conclusions:

Pictograms are vital for redesigning medication information to improve patient outcomes.
A structured model for pictogram development and testing is essential for effective pharmaceutical communication.
Further research is needed to optimize pictogram design and integration into patient education.