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Updated: Jun 8, 2025

Designing a Bioreactor to Improve Data Acquisition and Model Throughput of Engineered Cardiac Tissues
Published on: June 2, 2023
Design of experiments for the automated development of a multicellular cardiac model for high-throughput screening
Kavita Raniga1, William Stebbeds2, Arun Shivalingam3
1The Biodiscovery Institute, University of Nottingham, Nottingham, UK, NG7 2RD; GlaxoSmithKline R&D, Stevenage, UK, SG1 2NY.
Abstract:
Cardiovascular toxicity remains a major cause of drug attrition in early drug development, clinical trials, and post-market surveillance. In vitro assessment of cardiovascular liabilities often relies on single cell type-based model systems coupled with functional assays, like calcium flux and multielectrode arrays. Although these models offer high-throughput capabilities and demonstrate good predictivity for functional cardiotoxicities, they fail to consider the vital contribution of non-myocyte cells, thus limiting the potential for integrated risk assessment. Complex 3D hPSC-derived multicellular cardiac model systems have been growing in popularity; however, many of these models are limited to low-throughput with lengthy development timelines and high costs, which hampers their suitability to drug discovery. To optimize the development of an in vitro multicellular model system containing human-induced pluripotent stem-cell derived cardiomyocytes, endothelial cells and cardiac fibroblasts, we employed the Synthace platform, which enables scientists to express complex experimental intent in a simple format (e.g. Design of Experiments) and to translate this to automation protocols using no-code. Utilizing this approach, we systematically screened the impact of multiple cell culture parameters, including the co-culture of three cell types, on cardiac contractility, with minimal hands-on time. Our platform accelerates the assay development process, providing users with an efficient means to explore and optimize the experimental space for the development of multicellular models. This is particularly valuable in scenarios involving variable biological responses and limited understanding of underling mechanisms. Moreover, users can make better use of resources, streamline their workflows, and drive data-driven decision-making throughout the assay development journey.
Insights
Developing better in vitro cardiovascular toxicity models is crucial for drug safety. This study optimized a multicellular cardiac model using automation, accelerating drug discovery and improving risk assessment for cardiotoxicity.
Area of Science:
- Biomedical Engineering
- Cardiovascular Pharmacology
- Stem Cell Biology
Background:
- Cardiovascular toxicity is a primary reason for drug failure in development and clinical use.
- Current in vitro models often use single cell types, neglecting the complex cardiac environment and limiting comprehensive risk assessment.
- Existing multicellular cardiac models are often low-throughput, costly, and time-consuming, hindering their application in drug discovery.
Purpose of the Study:
- To optimize the development of an in vitro multicellular cardiac model using human-induced pluripotent stem cells (hPSC).
- To systematically screen cell culture parameters for improved cardiac contractility in a co-culture system.
- To leverage automation and design of experiments for efficient assay development.
Main Methods:
- Employed the Synthace platform for automated experimental design and protocol translation.
- Co-cultured hPSC-derived cardiomyocytes, endothelial cells, and cardiac fibroblasts.
- Systematically screened multiple cell culture parameters to assess impact on cardiac contractility.
Main Results:
- Successfully optimized an in vitro multicellular cardiac model with minimal hands-on time.
- Demonstrated efficient exploration and optimization of experimental parameters for model development.
- Accelerated the assay development process for complex biological systems.
Conclusions:
- The Synthace platform enables efficient development of advanced multicellular cardiac models for drug discovery.
- This approach enhances the assessment of cardiovascular liabilities by incorporating multiple cardiac cell types.
- Streamlined workflows and data-driven decision-making improve resource utilization in assay development.

