Disease Modeling

Using 3D cell structures for modeling tumors, organs, and tissue to accelerate translational research

What is Disease Modeling?

Disease modeling is a fundamental aspect of biomedical research, encompassing the creation of representative systems that mimic the behavior of diseases in a controlled environment. These models help researchers gain insights into the underlying mechanisms of diseases, test the effectiveness of potential therapies, and ultimately pave the way for improved patient care.

Disease model systems range in complexity and scale from simple 2D cell cultures to complex model organisms. While model organisms offer in vivo context, they are often costly and may not represent human biology. On the other hand, while traditional 2D cell culture systems have been used for many years, they have limitations in representing the complex three-dimensional structure and cellular interactions found in living tissues. As a result, 3D cell cultures have emerged as an attractive model system for disease modeling.

Register for on-demand webinar, The search for answers: Using lab automation with patient-derived tumors to find more relevant therapies for clinically aggressive cancers.

Leveraging 3D cell models for studying human diseases

3D cell models recapitulate key aspects of in vivo tissue and organ complexity, which makes them suitable for studying human diseases. In addition to being more experimentally tractable than model organisms, 3D models can be derived from human cells, which makes them highly relevant to the human disease being studied. For example, 3D brain organoids grown from iPSC can be used to study neurodegenerative diseases such as Alzheimer's and Parkinson's, cardioids or heart organoids can be used to study cardiovascular diseases such as heart failure, while patient-derived organoids (PDOs) generated from tumor biopsies can serve as models for oncology research to understand patient-specific drug responses and provide more effective treatment options.

Patient-derived organoids for disease research and drug discovery

Many oncology drugs fail at the later stages of the drug development pipeline and in clinical trials, despite promising data for their efficacy in vitro. This high failure rate is partly attributed to the lack of predictive models used to screen drug candidates in the early stages of drug discovery. As such, there is a need to develop and utilize more representative models that are amendable for efficient compound testing to discover new therapeutic targets.

3D cell models, specifically patient-derived organoids (PDOs), offer a promising solution to this problem. Cells grown in 3D can better mimic cell-cell interactions and the tissue microenvironment, including cancer stem cell niches. Studies show that patients and their derived organoids respond similarly to drugs, suggesting the therapeutic value of using PDOs to improve therapeutic outcomes. However, challenges such as assay reproducibility, scalability, and cost have limited the use of PDOs in mainstream drug discovery pipelines.

Here we showcase our featured patient-derived cancer organoid research. Our results show the superior potential of PDOs vs. other tissues in both precision medicine and high-throughput drug discovery applications when using automation with high-content imaging and AI data analysis.

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Breast cancer patient-derived tumoroids

Triple negative breast cancer is a clinically aggressive tumor subtype, with high rates of metastasis, recurrence, and drug resistance. Currently there are no clinically approved small molecule targeted therapies for this disease, underlining the critical need to discover new therapeutic targets. Primary tumor-derived models can recapitulate tumor heterogeneity and morphology, as well as complex genetic and molecular composition thereby accelerating drug development and drug testing. In the present study we describe automation of imaging and cell culture methods that enables scaling up complex 3D cell-based assays.

View more breast cancer tumoroid research

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Colorectal cancer (CRC) patient-derived organoids

In this poster, we demonstrate their utility in high-throughput applications using colorectal cancer (CRC) PDOs. Treated with selected anti-cancer drugs at various concentrations, the PDOs were monitored over time using transmitted-light imaging, and a deep learning-based image segmentation model was developed to analyze PDO size, texture, intensity, and other morphological and phenotypic readouts. Our results support the efficiency of using assay-ready PDOs for high-throughput assays such as compound screening.

View more CRC organoid research

Types of human-relevant 3D cell culture models

There are various types of 3D cell models used for disease modeling and drug discovery, including spheroids, organoids, and organ-on-a-chip. Each type of 3D cell model has its own unique advantages, and the choice of specific 3D models depends on the specific research needs. By using these human-relevant 3D cell models, researchers can study the effects of different treatments on disease progression, identify potential drug candidates, and understand disease mechanisms.

3D biology application and research for disease modeling

The use of 3D cell models in disease modeling is a rapidly growing field with significant potential to improve our understanding of complex diseases and accelerate the development of new therapeutics. Molecular Devices is committed to advancing this field and providing researchers with the tools and technologies needed to conduct cutting-edge research in 3D biology.

Combining this complex biology with advanced high-content imaging techniques, such as those enabled by the ImageXpress Micro Confocal System opens up a whole new level of assays. A powerful automated confocal imaging instrument equipped with AI/machine learning 3D analysis capabilities can allow researchers to obtain accurate, quantitative results and answers to their questions very quickly and in a robust and scalable manner.

Latest Resources

Resources for Disease Modeling