Webinar Abstract
This is webinar is presented on data from a bioRxiv preprint. The final version of this paper, “Performance assessment and economic analysis of a human Liver-Chip for predictive toxicology” is now live in Communications Medicine, part of Nature Portfolio.
To hear commentary from the authors about the impact these findings could have on the future of research and drug development, watch our webinar “Towards A More Predictive Model of Human Biology: A Fireside Chat.”
Failure in late stages of the drug development pipeline is one of the major challenges the pharmaceutical industry faces today. Human organ-on-a-chip (Organ-Chip) technology has the potential to disrupt preclinical drug discovery, as it has been shown to recapitulate organ-level pathophysiology and clinical responses. Additionally, industrial guidelines have been published that describe the criteria for qualifying preclinical models for a particular use application; however, systematic and quantitative evaluation of Organ-Chips’ predictive value has not been conducted to date.
To explore how this challenge might be approached, 780 human Liver-Chips were analyzed to determine their ability to predict drug-induced liver injury caused by small molecules. Across a blinded set of 27 known hepatotoxic and non-toxic drugs, the LIVER-CHIP demonstrated a sensitivity of 87% and a specificity of 100%. A computational economic value analysis suggests that, with this performance, the Liver-Chip could generate $3 billion per year to small-molecule drug development by driving an increase in research and development productivity.
In this webinar, we discuss:
- Why preclinical models with greater predictive validity will improve clinical success and productivity
- How the Emulate Liver-Chip performed against the IQ MPS guidelines
- How the Emulate Liver-Chip compared to animal models and hepatic spheroids
- What the economic impact of the Liver-Chip in routine use of small-molecule liver toxicity could be
- Where the Emulate Liver-Chip can be implemented into the drug development process