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Updated: Aug 9, 2025

Author Spotlight: Investigating Liver Cancer Pathogenesis Using Patient-Derived Organoids
Published on: August 18, 2023
A Human Ovarian Tumor & Liver Organ-on-Chip for Simultaneous and More Predictive Toxo-Efficacy Assays
Arianna Fedi1,2, Chiara Vitale2,3, Marco Fato1
1Department of Computer Science, Bioengineering, Robotics and Systems Engineering (DIBRIS), University of Genoa, 16126 Genoa, Italy.
Abstract:
In oncology, the poor success rate of clinical trials is becoming increasingly evident due to the weak predictability of preclinical assays, which either do not recapitulate the complexity of human tissues (i.e., in vitro tests) or reveal species-specific outcomes (i.e., animal testing). Therefore, the development of novel approaches is fundamental for better evaluating novel anti-cancer treatments. Here, a multicompartmental organ-on-chip (OOC) platform was adopted to fluidically connect 3D ovarian cancer tissues to hepatic cellular models and resemble the systemic cisplatin administration for contemporarily investigating drug efficacy and hepatotoxic effects in a physiological context. Computational fluid dynamics was performed to impose capillary-like blood flows and predict cisplatin diffusion. After a cisplatin concentration screening using 2D/3D tissue models, cytotoxicity assays were conducted in the multicompartmental OOC and compared with static co-cultures and dynamic single-organ models. A linear decay of SKOV-3 ovarian cancer and HepG2 liver cell viability was observed with increasing cisplatin concentration. Furthermore, 3D ovarian cancer models showed higher drug resistance than the 2D model in static conditions. Most importantly, when compared to clinical therapy, the experimental approach combining 3D culture, fluid-dynamic conditions, and multi-organ connection displayed the most predictive toxicity and efficacy results, demonstrating that OOC-based approaches are reliable 3Rs alternatives in preclinic.
Insights
This study introduces a novel organ-on-chip (OOC) platform to accurately predict anti-cancer drug efficacy and toxicity. This advanced model offers a reliable alternative to traditional preclinical testing methods.
Area of Science:
- Oncology
- Biotechnology
- Pharmacology
Background:
- Preclinical oncology trials face low success rates due to unreliable in vitro and animal models.
- There is a critical need for advanced models that better predict human responses to anti-cancer drugs.
Purpose of the Study:
- To develop and validate a multicompartmental organ-on-chip (OOC) platform for evaluating anti-cancer drug efficacy and hepatotoxicity.
- To assess the predictive capability of the OOC platform compared to traditional preclinical models.
Main Methods:
- A multicompartmental OOC platform fluidically connected 3D ovarian cancer tissues with hepatic cellular models.
- Computational fluid dynamics simulated capillary-like blood flow and cisplatin diffusion.
- Cytotoxicity assays were performed on the OOC platform, static co-cultures, and dynamic single-organ models.
Main Results:
- Increasing cisplatin concentrations linearly decreased ovarian cancer and liver cell viability.
- 3D ovarian cancer models exhibited greater cisplatin resistance than 2D models under static conditions.
- The OOC platform demonstrated superior predictive accuracy for drug toxicity and efficacy compared to clinical therapy data.
Conclusions:
- The developed OOC platform accurately mimics systemic drug administration in a physiological context.
- Organ-on-chip technology provides a reliable 3Rs (Replacement, Reduction, Refinement) alternative for preclinical drug evaluation.
- This approach enhances the predictability of anti-cancer drug efficacy and toxicity assessments.

