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

用于预测毒理学的人体肝脏芯片的性能评估和经济分析

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作者:Lorna Ewart, Athanasia Apostolou, 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 J Kujala, Gauri Kulkarni, Christopher Y Le, Carolina Lucchesi, Dimitris V

Background

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.

Conclusions

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.

Methods

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.

Results

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. Conclusions: 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.

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