Performance assessment and economic analysis of a human Liver-Chip for predictive toxicology

工作流程 药物开发 药品 医学 更安全的 芯片上器官 生产力 预测值 风险分析(工程) 危害 制药工业 临床试验 药物发现 药理学 毒理 计算机科学 生物信息学 病理 内科学 纳米技术 心理学 经济 材料科学 宏观经济学 微流控 生物 社会心理学 数据库 计算机安全
作者
Lorna Ewart,Αθανασία Αποστόλου,Skyler A. Briggs,Christopher V. Carman,Jake T. Chaff,Anthony R. Heng,Sushma Jadalannagari,Jeshina Janardhanan,Kyung‐Jin Jang,Sannidhi R. Joshipura,Mahika M. Kadam,Marianne Kanellias,Ville Kujala,Gauri Kulkarni,Christopher Y. Le,Carolina Lucchesi,Dimitris V. Manatakis,Kairav K. Maniar,Meaghan E. Quinn,Joseph S. Ravan
出处
期刊:Communications medicine [Springer Nature]
卷期号:2 (1) 被引量:153
标识
DOI:10.1038/s43856-022-00209-1
摘要

Conventional preclinical models often miss drug toxicities, meaning the harm these drugs pose to humans is only realized in clinical trials or when they make it to market. This has caused the pharmaceutical industry to waste considerable time and resources developing drugs destined to fail. Organ-on-a-Chip technology has the potential improve success in drug development pipelines, as it can recapitulate organ-level pathophysiology and clinical responses; however, systematic and quantitative evaluations of Organ-Chips' predictive value have not yet been reported.870 Liver-Chips were analyzed to determine their ability to predict drug-induced liver injury caused by small molecules identified as benchmarks by the Innovation and Quality consortium, who has published guidelines defining criteria for qualifying preclinical models. An economic analysis was also performed to measure the value Liver-Chips could offer if they were broadly adopted in supporting toxicity-related decisions as part of preclinical development workflows.Here, we show that the Liver-Chip met the qualification guidelines across a blinded set of 27 known hepatotoxic and non-toxic drugs with a sensitivity of 87% and a specificity of 100%. We also show that this level of performance could generate over $3 billion annually for the pharmaceutical industry through increased small-molecule R&D productivity.The results of this study show how incorporating predictive Organ-Chips into drug development workflows could substantially improve drug discovery and development, allowing manufacturers to bring safer, more effective medicines to market in less time and at lower costs.Drug development is lengthy and costly, as it relies on laboratory models that fail to predict human reactions to potential drugs. Because of this, toxic drugs sometimes go on to harm humans when they reach clinical trials or once they are in the marketplace. Organ-on-a-Chip technology involves growing cells on small devices to mimic organs of the body, such as the liver. Organ-Chips could potentially help identify toxicities earlier, but there is limited research into how well they predict these effects compared to conventional models. In this study, we analyzed 870 Liver-Chips to determine how well they predict drug-induced liver injury, a common cause of drug failure, and found that Liver-Chips outperformed conventional models. These results suggest that widespread acceptance of Organ-Chips could decrease drug attrition, help minimize harm to patients, and generate billions in revenue for the pharmaceutical industry.
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