Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Pharmacovigilance01:19

Pharmacovigilance

1.0K
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...
1.0K
Structure-Activity Relationships and Drug Design01:28

Structure-Activity Relationships and Drug Design

1.1K
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...
1.1K
SBAR II: Application of SBAR01:14

SBAR II: Application of SBAR

4.8K
SBAR is an effective communication tool used by healthcare professionals to communicate patient information accurately. SBAR stands for Situation, Background, Assessment, and Recommendation. For a better understanding, an example is given below.
SBAR Report from a Nurse to a Health Care Provider
S: "Hello, Dr. Smith. This is Jane, RN, from the Med Surg unit. I am calling to tell you about Ms. White in Room 210, who is experiencing increased pain and redness at her incision site. Her recent...
4.8K
Preclinical Development: Overview01:28

Preclinical Development: Overview

4.9K
Preclinical development consists of a series of tests that ensure the safety and efficacy of a new therapeutic compound before it is tested in humans. There are four main phases to this process. First, safety pharmacology tests are conducted to ensure the drug does not produce any acutely harmful effects. These tests examine parameters such as bronchoconstriction, cardiac dysrhythmias, blood pressure changes, and ataxia. Next, preliminary toxicological testing is performed to determine the...
4.9K
Drug Discovery: Overview01:26

Drug Discovery: Overview

8.9K
Drug discovery is a multifaceted process involving extensive screening, testing, and optimization of lead compounds to identify potential new drugs for therapeutic use. It combines several approaches, including screening large numbers of natural products, chemical modification of known active molecules, identification of new drug targets, and rational design based on biological mechanisms and drug-receptor structure. These approaches are carried out in both academic research laboratories and...
8.9K
Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

5.9K
The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
5.9K

You might also read

Related Articles

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

Sort by
Same author

Naloxone Distribution in the United States, 2018-2023.

American journal of public health·2026
Same author

U.S. Poison Center exposure cases involving marijuana and selected comparator substances.

Drug and alcohol dependence·2026
Same author

A Systematic Process for Assessing Fitness-for-Purpose of Health Outcomes for Computable Phenotyping With Electronic Health Record Data.

Pharmacoepidemiology and drug safety·2026
Same author

United States healthcare encounters for poisoning involving cannabis relative to other substances.

The American journal of drug and alcohol abuse·2026
Same author

Variations in US county-level trends in buprenorphine use, 2018-2022.

Addiction (Abingdon, England)·2025
Same author

Characterizing the FDA Adverse Event Reporting System (FAERS) as a Network to Improve Pattern Discovery.

Drug safety·2025

Related Experiment Video

Updated: Sep 23, 2025

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
05:33

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Published on: July 11, 2025

297

"Artificial Intelligence" for Pharmacovigilance: Ready for Prime Time?

Robert Ball1, Gerald Dal Pan2

  • 1US Food and Drug Administration, Center for Drug Evaluation and Research, Office of Surveillance and Epidemiology, Silver Spring, MD, USA. Robert.Ball@fda.hhs.gov.

Drug Safety
|May 17, 2022
PubMed
Summary

Artificial intelligence (AI) can aid pharmacovigilance (PV) by processing safety reports. However, current AI requires human oversight for quality assurance in evaluating individual case safety reports (ICSRs).

More Related Videos

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

7.6K
Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions
08:31

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions

Published on: December 1, 2020

5.2K

Related Experiment Videos

Last Updated: Sep 23, 2025

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
05:33

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Published on: July 11, 2025

297
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

7.6K
Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions
08:31

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions

Published on: December 1, 2020

5.2K

Area of Science:

  • Pharmacovigilance and Drug Safety
  • Artificial Intelligence in Healthcare
  • Regulatory Science

Background:

  • Growing interest in applying artificial intelligence (AI) to pharmacovigilance (PV).
  • Focus on AI's role in processing and evaluating Individual Case Safety Reports (ICSRs) for the FDA Adverse Event Reporting System (FAERS).

Purpose of the Study:

  • To present a framework for assessing AI readiness in PV.
  • To provide examples of AI applications in ICSR processing and evaluation.
  • To identify challenges and future directions for AI in PV.

Main Methods:

  • Development of a general framework for AI readiness in PV.
  • Review of industry and FDA examples of AI applied to ICSR processing and evaluation.
  • Identification of scientific and policy issues for AI implementation in PV.

Main Results:

  • AI shows utility in specific aspects of ICSR processing and evaluation.
  • Current AI algorithms necessitate a 'human-in-the-loop' approach for quality assurance.
  • Several key issues require addressing for broader AI adoption in PV.

Conclusions:

  • AI can enhance ICSR processing and evaluation, but human oversight is crucial.
  • Further research and policy development are needed for AI's full potential in PV.
  • Stepwise implementation and practical experience will inform future AI adoption in pharmacovigilance.