Advancing hepatotoxicity assessment: current advances and future directions

Area of Science:

• Pharmacology
• Toxicology
• Biomedical Engineering

Background:

• Drug development requires assessing efficacy and safety, with liver toxicity (hepatotoxicity) being a primary concern due to liver-mediated drug clearance.
• Current methods like animal models and primary human hepatocytes have limitations, leading to drug withdrawals post-market.
• Unforeseen hepatotoxicity in patients necessitates improved predictive models.

Purpose of the Study:

• To systematically review and compare conventional and emerging hepatotoxicity assessment models.
• To evaluate the advantages, limitations, and predictive reliability of different methodologies.
• To propose future directions for enhancing hepatotoxicity assessment in drug development.

Main Methods:

• Comparative analysis of 2D cell culture models, animal models, advanced 3D liver cultures, organ-on-a-chip systems, and in silico (computational, AI-based) models.
• Evaluation of predictive reliability and translational relevance of each model type.

Main Results:

• Conventional models show limitations in predicting human hepatotoxicity.
• Emerging models, including 3D cultures, organ-on-a-chip, and AI-driven computational approaches, demonstrate higher potential for accurate prediction.
• A critical evaluation highlights the strengths and weaknesses of each methodology.

Conclusions:

• There is a critical need to refine hepatotoxicity assessment strategies in drug development.
• Future directions should focus on integrating advanced in vitro and in silico models, particularly AI-driven approaches.
• Enhancing translational relevance and reducing animal testing are key goals for improved drug safety evaluation.