定量系统药理学和毒理学模型的发展:通过DILIsym发展的经验和教训

Q3 Pharmacology, Toxicology and Pharmaceutics Drug Discovery Today: Disease Models Pub Date : 2016-12-01 DOI:10.1016/j.ddmod.2017.04.001
Brett A. Howell , Scott Q. Siler , Hugh A. Barton , Elizabeth M. Joshi , Antonio Cabal , Gary Eichenbaum , Paul B. Watkins
{"title":"定量系统药理学和毒理学模型的发展:通过DILIsym发展的经验和教训","authors":"Brett A. Howell ,&nbsp;Scott Q. Siler ,&nbsp;Hugh A. Barton ,&nbsp;Elizabeth M. Joshi ,&nbsp;Antonio Cabal ,&nbsp;Gary Eichenbaum ,&nbsp;Paul B. Watkins","doi":"10.1016/j.ddmod.2017.04.001","DOIUrl":null,"url":null,"abstract":"<div><p><span>The development of new pharmaceuticals for the treatment of human disease is increasingly challenging. New methods such as quantitative systems pharmacology (QSP) and quantitative systems toxicology (QST) can help address </span>drug development challenges. Despite its promise, QSP/QST is not without its challenges. An investment is required to collect the necessary input data and ensure key components are represented qualitatively and quantitatively well. One strategy for addressing these concerns is conducting model development within consortia. Consortia offer companies the ability to share data, seek feedback from health authorities collectively, guide model development, learn from others, and share platform development costs. This article highlights lessons learned from past experiences associated with The DILI-sim Initiative – a collaborative effort focused on developing DILIsym software for predicting drug-induced liver injury (DILI).</p></div>","PeriodicalId":39774,"journal":{"name":"Drug Discovery Today: Disease Models","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.ddmod.2017.04.001","citationCount":"8","resultStr":"{\"title\":\"Development of quantitative systems pharmacology and toxicology models within consortia: experiences and lessons learned through DILIsym development\",\"authors\":\"Brett A. Howell ,&nbsp;Scott Q. Siler ,&nbsp;Hugh A. Barton ,&nbsp;Elizabeth M. Joshi ,&nbsp;Antonio Cabal ,&nbsp;Gary Eichenbaum ,&nbsp;Paul B. Watkins\",\"doi\":\"10.1016/j.ddmod.2017.04.001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p><span>The development of new pharmaceuticals for the treatment of human disease is increasingly challenging. New methods such as quantitative systems pharmacology (QSP) and quantitative systems toxicology (QST) can help address </span>drug development challenges. Despite its promise, QSP/QST is not without its challenges. An investment is required to collect the necessary input data and ensure key components are represented qualitatively and quantitatively well. One strategy for addressing these concerns is conducting model development within consortia. Consortia offer companies the ability to share data, seek feedback from health authorities collectively, guide model development, learn from others, and share platform development costs. This article highlights lessons learned from past experiences associated with The DILI-sim Initiative – a collaborative effort focused on developing DILIsym software for predicting drug-induced liver injury (DILI).</p></div>\",\"PeriodicalId\":39774,\"journal\":{\"name\":\"Drug Discovery Today: Disease Models\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/j.ddmod.2017.04.001\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Drug Discovery Today: Disease Models\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1740675717300166\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Pharmacology, Toxicology and Pharmaceutics\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Drug Discovery Today: Disease Models","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1740675717300166","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Pharmacology, Toxicology and Pharmaceutics","Score":null,"Total":0}
引用次数: 8

摘要

开发用于治疗人类疾病的新药越来越具有挑战性。定量系统药理学(QSP)和定量系统毒理学(QST)等新方法可以帮助解决药物开发挑战。尽管前景光明,QSP/QST也并非没有挑战。需要投资收集必要的输入数据,并确保关键组件在定性和定量上都得到很好的表示。解决这些问题的一个策略是在联盟中进行模型开发。联盟为公司提供了共享数据、集体向卫生当局寻求反馈、指导模型开发、向他人学习和分担平台开发成本的能力。本文重点介绍了与DILI-sim计划相关的过去经验教训。DILI-sim计划是一项合作努力,重点开发用于预测药物性肝损伤(DILI)的DILIsym软件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Development of quantitative systems pharmacology and toxicology models within consortia: experiences and lessons learned through DILIsym development

The development of new pharmaceuticals for the treatment of human disease is increasingly challenging. New methods such as quantitative systems pharmacology (QSP) and quantitative systems toxicology (QST) can help address drug development challenges. Despite its promise, QSP/QST is not without its challenges. An investment is required to collect the necessary input data and ensure key components are represented qualitatively and quantitatively well. One strategy for addressing these concerns is conducting model development within consortia. Consortia offer companies the ability to share data, seek feedback from health authorities collectively, guide model development, learn from others, and share platform development costs. This article highlights lessons learned from past experiences associated with The DILI-sim Initiative – a collaborative effort focused on developing DILIsym software for predicting drug-induced liver injury (DILI).

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Drug Discovery Today: Disease Models
Drug Discovery Today: Disease Models Pharmacology, Toxicology and Pharmaceutics-Drug Discovery
自引率
0.00%
发文量
0
期刊介绍: Drug Discovery Today: Disease Models discusses the non-human experimental models through which inference is drawn regarding the molecular aetiology and pathogenesis of human disease. It provides critical analysis and evaluation of which models can genuinely inform the research community about the direct process of human disease, those which may have value in basic toxicology, and those which are simply designed for effective expression and raw characterisation.
期刊最新文献
Balanced actions of estradiol and progesterone—A new paradigm of women’s reproductive health Women’s reproductive system as balanced estradiol and progesterone actions—A revolutionary, paradigm-shifting concept in women’s health Influence of progestagens on bone health. Bone changes related to ovulatory disturbances and low progesterone levels Hereditary bullous diseases: current and innovative models to study the skin blistering disease epidermolysis bullosa The extent and causes of natural variation in menstrual cycles: Integrating empirically-based models of ovarian cycling into research on women’s health
×
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