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Updated: Jan 8, 2026
Diagonal Method to Measure Synergy Among Any Number of Drugs
Published on: June 21, 2018
Leveraging multi-organ models for drug combination therapy safety
Valentin Mieville1, Jakub Gubala1, Seungsu Han2
1School of Pharmaceutical Sciences, Faculty of Science, University of Geneva, Geneva 1211, Switzerland; Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, Geneva 1211, Switzerland; Translational Research Center in Oncohaematology, Geneva 1211, Switzerland.
Abstract:
In this study, we developed a streamlined in vitro platform to assess the systemic toxicity of multidrug combinations within a clinically relevant timeframe, facilitating its application in personalized medicine. By incorporating cellular models that represent major toxicity-sensitive organs, such as the kidney, liver, and heart, we evaluated two previously optimized multidrug combinations (C2 and REMP). Our findings revealed distinct organ-specific toxicity profiles, with some drug-induced toxicities exacerbated upon combination. To evaluate the influence of model complexity, we compared responses between simple proliferative cell lines and more advanced models. Proliferative cell models, while useful for initial toxicity screenings, frequently failed to predict the severity of drug-induced toxicity. For instance, the C2 combination decreased cell viability by 50 % in patient-derived kidney organoids but only by 20 % in HEK293T cells. However, the C2 combination caused a 77 % viability reduction in differentiated hepatocyte spheroids, 32 % more than its effect on non-differentiated hepatocyte-like cells. C2 showed significant release of lactate dehydrogenase compared to 0.1 % DMSO. These findings underscore the critical need for systemic and biologically relevant drug safety assessments in the development of novel drug combinations, regardless of known single-drug safety. Despite some limitations, the platform accurately reproduced known single-drug toxicity profiles, confirming its translational potential. Overall, this biologically relevant approach enables efficient early-stage toxicity screening of drug combinations, supporting a safer development of personalized cancer therapy.
Insights
A new in vitro platform assesses multidrug combination toxicity in organs like the kidney and liver. Biologically relevant models are crucial for predicting severe drug-induced toxicity, unlike simple cell lines.
Area of Science:
- Pharmacology
- Toxicology
- Biomedical Engineering
Background:
- Assessing systemic toxicity of multidrug combinations is critical for personalized medicine.
- Existing methods may not accurately predict organ-specific toxicities or combination effects.
- Clinically relevant timeframes are needed for efficient drug development.
Purpose of the Study:
- To develop and validate a streamlined in vitro platform for assessing systemic toxicity of multidrug combinations.
- To compare the predictive power of different cellular models for drug-induced toxicity.
- To evaluate the organ-specific toxicity profiles of multidrug combinations.
Main Methods:
- Development of a multi-organ in vitro platform using cellular models of kidney, liver, and heart.
- Evaluation of two multidrug combinations (C2 and REMP) using the platform.
- Comparison of toxicity responses between simple cell lines and advanced organoid/spheroid models.
Main Results:
- The platform identified distinct organ-specific toxicity profiles for multidrug combinations.
- Some drug-induced toxicities were exacerbated in combination therapy.
- Advanced models (organoids, spheroids) showed higher sensitivity and better prediction of toxicity severity compared to simple cell lines.
- C2 combination demonstrated significantly higher toxicity in kidney organoids and differentiated hepatocyte spheroids compared to simpler cell models.
- Lactate dehydrogenase release indicated significant toxicity for C2.
Conclusions:
- Biologically relevant in vitro platforms are essential for accurate systemic toxicity assessment of drug combinations.
- Simple cell lines may underestimate the severity of drug-induced toxicity.
- The developed platform shows translational potential for early-stage toxicity screening in personalized cancer therapy development.
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