Development of the medicine safety data monitoring system GERMES PV (literature monitoring and internet sources)

The global coronavirus pandemic of recent years has led to an emergency situation in the field of health care, determined the need to develop new vaccines for the treatment of the population under the guidance of the World Health Organization. Assessment of the safety and effectiveness of the use of these vaccines requires a wide range of research, one of the methods of which is literature monitoring of scientific publications. Significant labor costs for the search and analysis of articles make the creation and implementation of computer information and search systems for monitoring literature and Internet sources an urgent issue. Developed for this purpose, the medicine safety data monitoring system Germes PV is intended for the comprehensive application of modern technologies of automated monitoring of periodicals and Internet resources (web portals, websites, electronic libraries, etc.) in order to search for publications on the safety of drugs, availability adverse reactions and lack of effectiveness of medicinal products, feedback and suggestions of interested persons and other information in the field of pharmacovigilance. In this work, a comprehensive analysis of the subject area is carried out and ways of automating the activities of health care institutions and pharmaceutical companies in this area are described.

Authors

Institutions

Publication Details

Journal
PROBLEMS IN PROGRAMMING
Published
2024-09-01
DOI
https://doi.org/10.15407/pp2024.02-03.190
Primary Topic
Biomedical and Engineering Education
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Development of the medicine safety data monitoring system GERMES PV (literature monitoring and internet sources)

Serhiy Mashkovskyi, А.В. Чадюк
PROBLEMS IN PROGRAMMING
Biomedical and Engineering Education
article

Development of the medicine safety data monitoring system GERMES PV (literature monitoring and internet sources)

Serhiy Mashkovskyi, А.В. Чадюк
article en

Abstract

The global coronavirus pandemic of recent years has led to an emergency situation in the field of health care, determined the need to develop new vaccines for the treatment of the population under the guidance of the World Health Organization. Assessment of the safety and effectiveness of the use of these vaccines requires a wide range of research, one of the methods of which is literature monitoring of scientific publications. Significant labor costs for the search and analysis of articles make the creation and implementation of computer information and search systems for monitoring literature and Internet sources an urgent issue. Developed for this purpose, the medicine safety data monitoring system Germes PV is intended for the comprehensive application of modern technologies of automated monitoring of periodicals and Internet resources (web portals, websites, electronic libraries, etc.) in order to search for publications on the safety of drugs, availability adverse reactions and lack of effectiveness of medicinal products, feedback and suggestions of interested persons and other information in the field of pharmacovigilance. In this work, a comprehensive analysis of the subject area is carried out and ways of automating the activities of health care institutions and pharmaceutical companies in this area are described.

PROBLEMS IN PROGRAMMING(2-3)
Institute of Software Systems (UA), Information Systems Laboratories (United States) (US)
Openalex Percentile: Top 76%
Biomedical and Engineering Education
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.