Advancing In Silico Clinical Trials for Regulatory Adoption and Innovation.

IF 6.7 2区 医学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS IEEE Journal of Biomedical and Health Informatics Pub Date : 2024-11-08 DOI:10.1109/JBHI.2024.3486538
Georgia Karanasiou, Elazer Edelman, Francois-Henri Boissel, Robert Byrne, Luca Emili, Martin Fawdry, Nenad Filipovic, David Flynn, Liesbet Geris, Alfons Hoekstra, Maria Cristina Jori, Ali Kiapour, Dejan Krsmanovic, Thierry Marchal, Flora Musuamba, Francesco Pappalardo, Lorenza Petrini, Markus Reiterer, Marco Viceconti, Klaus Zeier, Lampros K Michalis, Dimitrios I Fotiadis
{"title":"Advancing In Silico Clinical Trials for Regulatory Adoption and Innovation.","authors":"Georgia Karanasiou, Elazer Edelman, Francois-Henri Boissel, Robert Byrne, Luca Emili, Martin Fawdry, Nenad Filipovic, David Flynn, Liesbet Geris, Alfons Hoekstra, Maria Cristina Jori, Ali Kiapour, Dejan Krsmanovic, Thierry Marchal, Flora Musuamba, Francesco Pappalardo, Lorenza Petrini, Markus Reiterer, Marco Viceconti, Klaus Zeier, Lampros K Michalis, Dimitrios I Fotiadis","doi":"10.1109/JBHI.2024.3486538","DOIUrl":null,"url":null,"abstract":"<p><p>The evolution of information and communication technologies has affected all fields of science, including health sciences. However, the rate of technological innovation adoption by the healthcare sector has been historically slow, compared to other industrial sectors. Innovation in computer modeling and simulation approaches has changed the landscape in biomedical applications and biomedicine, paving the way for their potential contribution in reducing, refining, and partially replacing animal and human clinical trials. In Silico Clinical Trials (ISCT) allow the development of virtual populations used in the safety and efficacy testing of new drugs and medical devices. This White Paper presents the current framework for ISCT, the role of in silico medicine research communities, the different perspectives (research, scientific, clinical, regulatory, standardization, data quality, legal and ethical), the barriers, challenges, and opportunities for ISCT adoption. In addition, an overview of successful ISCT projects, market-available platforms, and FDA- approved paradigms, along with their vision, mission and outcomes are presented.</p>","PeriodicalId":13073,"journal":{"name":"IEEE Journal of Biomedical and Health Informatics","volume":"PP ","pages":""},"PeriodicalIF":6.7000,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Journal of Biomedical and Health Informatics","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1109/JBHI.2024.3486538","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0

Abstract

The evolution of information and communication technologies has affected all fields of science, including health sciences. However, the rate of technological innovation adoption by the healthcare sector has been historically slow, compared to other industrial sectors. Innovation in computer modeling and simulation approaches has changed the landscape in biomedical applications and biomedicine, paving the way for their potential contribution in reducing, refining, and partially replacing animal and human clinical trials. In Silico Clinical Trials (ISCT) allow the development of virtual populations used in the safety and efficacy testing of new drugs and medical devices. This White Paper presents the current framework for ISCT, the role of in silico medicine research communities, the different perspectives (research, scientific, clinical, regulatory, standardization, data quality, legal and ethical), the barriers, challenges, and opportunities for ISCT adoption. In addition, an overview of successful ISCT projects, market-available platforms, and FDA- approved paradigms, along with their vision, mission and outcomes are presented.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
推进硅学临床试验,促进法规采纳和创新。
信息和通信技术的发展已经影响到包括卫生科学在内的所有科学领域。然而,与其他工业部门相比,医疗保健部门采用技术创新的速度历来缓慢。计算机建模和仿真方法的创新改变了生物医学应用和生物医学的格局,为其在减少、完善和部分取代动物和人体临床试验方面的潜在贡献铺平了道路。硅学临床试验 (ISCT) 允许开发虚拟人群,用于新药和医疗设备的安全性和有效性测试。本白皮书介绍了当前的 ISCT 框架、硅医学研究团体的作用、不同的视角(研究、科学、临床、监管、标准化、数据质量、法律和伦理)、采用 ISCT 的障碍、挑战和机遇。此外,还概述了成功的 ISCT 项目、市场上可用的平台和 FDA 批准的范例,以及它们的愿景、使命和成果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
IEEE Journal of Biomedical and Health Informatics
IEEE Journal of Biomedical and Health Informatics COMPUTER SCIENCE, INFORMATION SYSTEMS-COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
CiteScore
13.60
自引率
6.50%
发文量
1151
期刊介绍: IEEE Journal of Biomedical and Health Informatics publishes original papers presenting recent advances where information and communication technologies intersect with health, healthcare, life sciences, and biomedicine. Topics include acquisition, transmission, storage, retrieval, management, and analysis of biomedical and health information. The journal covers applications of information technologies in healthcare, patient monitoring, preventive care, early disease diagnosis, therapy discovery, and personalized treatment protocols. It explores electronic medical and health records, clinical information systems, decision support systems, medical and biological imaging informatics, wearable systems, body area/sensor networks, and more. Integration-related topics like interoperability, evidence-based medicine, and secure patient data are also addressed.
期刊最新文献
Machine Learning Identification and Classification of Mitosis and Migration of Cancer Cells in a Lab-on-CMOS Capacitance Sensing platform. Biomedical Information Integration via Adaptive Large Language Model Construction. BloodPatrol: Revolutionizing Blood Cancer Diagnosis - Advanced Real-Time Detection Leveraging Deep Learning & Cloud Technologies. EEG Detection and Prediction of Freezing of Gait in Parkinson's Disease Based on Spatiotemporal Coherent Modes. Functional Data Analysis of Hand Rotation for Open Surgical Suturing Skill Assessment.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1