A scalable human liver-on-a-chip platform for predictive safety assessment

Area of Science:

• Toxicology
• Biotechnology
• In vitro models

Background:

• Non-animal methods for hepatotoxicity testing, like liver-on-a-chip, face adoption barriers due to cost, scalability, and validation issues.
• Drug-induced liver injury (DILI) assessment is crucial for pharmaceutical development and chemical safety.

Purpose of the Study:

• To develop and validate a cost-effective, scalable, and human-relevant liver-on-a-chip model for predictive hepatotoxicity testing.
• To address limitations in current non-animal testing methods for DILI.

Main Methods:

• Utilized the OC-Plex microfluidic platform with primary human hepatocytes (PHHs).
• Assessed PHH viability, albumin and urea production, and cytochrome P450 gene expression for long-term functionality.
• Detected acetaminophen-induced hepatotoxicity using six mechanistic readouts.

Main Results:

• PHHs maintained viability and metabolic competence in the model.
• The system successfully detected acetaminophen-induced liver injury.
• Tested 17 compounds, achieving 85.7% sensitivity, 100% specificity, and 92.3% accuracy for known toxic liabilities.

Conclusions:

• The developed liver-on-a-chip model is feasible, cost-effective, and scalable for predictive hepatotoxicity testing.
• This model demonstrates high predictive performance and human relevance.
• The system holds potential to replace animal testing in chemical safety assessment with further validation.