{"title":"超越炒作,走向应用:临床前药物安全性中的肝脏复合体体外模型。","authors":"Sushma Jadalannagari, Lorna Ewart","doi":"10.1080/17425255.2024.2328794","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Drug induced Liver-Injury (DILI) is a leading cause of drug attrition and complex <i>in vitro</i> models (CIVMs), including three dimensional (3D) spheroids, 3D bio printed tissues and flow-based systems, could improve preclinical prediction. Although CIVMs have demonstrated good sensitivity and specificity in DILI detection their adoption remains limited.</p><p><strong>Areas covered: </strong>This article describes DILI, the challenges with its prediction and the current strategies and models that are being used. It reviews data from industry-FDA collaborations and strategic partnerships and finishes with an outlook of CIVMs in preclinical toxicity testing. Literature searches were performed using PubMed and Google Scholar while product information was collected from manufacturer websites.</p><p><strong>Expert opinion: </strong>Liver CIVMs are promising models for predicting DILI although, a decade after their introduction, routine use by the pharmaceutical industry is limited. To accelerate their adoption, several industry-regulator-developer partnerships or consortia have been established to guide the development and qualification. Beyond this, liver CIVMs should continue evolving to capture greater immunological mimicry while partnering with computational approaches to deliver systems that change the paradigm of predicting DILI.</p>","PeriodicalId":94005,"journal":{"name":"Expert opinion on drug metabolism & toxicology","volume":" ","pages":"607-619"},"PeriodicalIF":0.0000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Beyond the hype and toward application: liver complex in vitro models in preclinical drug safety.\",\"authors\":\"Sushma Jadalannagari, Lorna Ewart\",\"doi\":\"10.1080/17425255.2024.2328794\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>Drug induced Liver-Injury (DILI) is a leading cause of drug attrition and complex <i>in vitro</i> models (CIVMs), including three dimensional (3D) spheroids, 3D bio printed tissues and flow-based systems, could improve preclinical prediction. Although CIVMs have demonstrated good sensitivity and specificity in DILI detection their adoption remains limited.</p><p><strong>Areas covered: </strong>This article describes DILI, the challenges with its prediction and the current strategies and models that are being used. It reviews data from industry-FDA collaborations and strategic partnerships and finishes with an outlook of CIVMs in preclinical toxicity testing. Literature searches were performed using PubMed and Google Scholar while product information was collected from manufacturer websites.</p><p><strong>Expert opinion: </strong>Liver CIVMs are promising models for predicting DILI although, a decade after their introduction, routine use by the pharmaceutical industry is limited. To accelerate their adoption, several industry-regulator-developer partnerships or consortia have been established to guide the development and qualification. Beyond this, liver CIVMs should continue evolving to capture greater immunological mimicry while partnering with computational approaches to deliver systems that change the paradigm of predicting DILI.</p>\",\"PeriodicalId\":94005,\"journal\":{\"name\":\"Expert opinion on drug metabolism & toxicology\",\"volume\":\" \",\"pages\":\"607-619\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Expert opinion on drug metabolism & toxicology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/17425255.2024.2328794\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/3/13 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Expert opinion on drug metabolism & toxicology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/17425255.2024.2328794","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/3/13 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
导言:药物性肝损伤(DILI)是药物损耗的一个主要原因,而复杂体外模型(CIVM),包括三维(3D)球体、三维生物打印组织和基于流动的系统,可以改善临床前预测。尽管 CIVM 在 DILI 检测中表现出良好的灵敏度和特异性,但其应用仍然有限:本文介绍了 DILI、其预测所面临的挑战以及目前正在使用的策略和模型。文章回顾了行业与美国食品药品管理局(FDA)合作及战略伙伴关系的数据,最后展望了临床前毒性测试中的 CIVMs。文献检索通过 PubMed 和 Google Scholar 进行,产品信息则从制造商网站收集:肝脏CIVMs是预测DILI的有前途的模型,尽管在其问世十年后,制药行业的常规使用还很有限。为了加快其应用,一些行业-监管机构-开发商合作或联合体已经成立,以指导其开发和鉴定。除此以外,肝脏 CIVM 应继续发展,以捕捉更多的免疫拟态,同时与计算方法合作,提供改变 DILI 预测模式的系统。
Beyond the hype and toward application: liver complex in vitro models in preclinical drug safety.
Introduction: Drug induced Liver-Injury (DILI) is a leading cause of drug attrition and complex in vitro models (CIVMs), including three dimensional (3D) spheroids, 3D bio printed tissues and flow-based systems, could improve preclinical prediction. Although CIVMs have demonstrated good sensitivity and specificity in DILI detection their adoption remains limited.
Areas covered: This article describes DILI, the challenges with its prediction and the current strategies and models that are being used. It reviews data from industry-FDA collaborations and strategic partnerships and finishes with an outlook of CIVMs in preclinical toxicity testing. Literature searches were performed using PubMed and Google Scholar while product information was collected from manufacturer websites.
Expert opinion: Liver CIVMs are promising models for predicting DILI although, a decade after their introduction, routine use by the pharmaceutical industry is limited. To accelerate their adoption, several industry-regulator-developer partnerships or consortia have been established to guide the development and qualification. Beyond this, liver CIVMs should continue evolving to capture greater immunological mimicry while partnering with computational approaches to deliver systems that change the paradigm of predicting DILI.