Performance assessment and economic analysis of a human Liver-Chip for predictive toxicology
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Published:2022-12-06
Issue:1
Volume:2
Page:
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ISSN:2730-664X
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Container-title:Communications Medicine
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language:en
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Short-container-title:Commun Med
Author:
Ewart LornaORCID, Apostolou Athanasia, Briggs Skyler A., Carman Christopher V., Chaff Jake T.ORCID, Heng Anthony R.ORCID, Jadalannagari Sushma, Janardhanan Jeshina, Jang Kyung-Jin, Joshipura Sannidhi R., Kadam Mahika M., Kanellias MarianneORCID, Kujala Ville J., Kulkarni Gauri, Le Christopher Y., Lucchesi Carolina, Manatakis Dimitris V.ORCID, Maniar Kairav K.ORCID, Quinn Meaghan E., Ravan Joseph S., Rizos Ann Catherine, Sauld John F. K., Sliz Josiah D., Tien-Street William, Trinidad Dennis Ramos, Velez James, Wendell MaxORCID, Irrechukwu Onyi, Mahalingaiah Prathap Kumar, Ingber Donald E.ORCID, Scannell Jack W., Levner Daniel
Abstract
Abstract
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 to 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.
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.
Publisher
Springer Science and Business Media LLC
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