Benefits of Using 3D Cell Models in Drug Discovery

As researchers explore therapeutic strategies for more complex and heterogeneous diseases the need for more physiologically relevant models has never been greater. Researchers are increasingly looking to 3D cell cultures, spheroids, organoids and microtissues to bridge the gap between 2D cell cultures and in vivo animal models.

We recently caught up with Dr. Karin Boettcher, Associate Product Manager Cellular Imaging & Analysis at PerkinElmer to discuss how 3D models can be applied to drug discovery. Karin highlights the impact these models are having on the field and provides tips on how to ensure your 3D cell models are consistent and reproducible.

Laura Mason (LM): What is 3D cell culture and how can 3D models be applied to the drug discovery field?

Karin Boettcher (KB): Cell culture is an indispensable technique for generating large numbers of cells for a wide range of in vitro applications, such as high-throughput screening. Classically, cells are used in microplates where they grow as adherent monolayers, or 2D cell cultures. In 3D cell culture, rather than growing as a layer, cells are cultured in a three-dimensional shape in a gel matrix, or in the form of spheroids or organoids. 3D cultures can be used as model systems in a multitude of applications across the drug discovery workflow, including target identification and validation, lead optimization, candidate selection, or during assay development to make informed decisions on high-throughput screening strategies. 3D cell models may also be used in a research context, e.g. in regenerative medicine, developmental biology, cancer research, and toxicology.

LM: What are the key benefits of using 3D models compared to other available models? Are there any particular examples you could share that demonstrate these benefits?

KB: Researchers are increasingly looking to 3D cell cultures, spheroids, organoids and microtissues to bridge the gap between 2D cell cultures and in vivo animal models. 3D cell models provide more physiologically relevant conditions than 2D cell cultures, as they closely mimic the microenvironments, cell-to-cell interactions and biological processes that occur in vivo. Plus, they show a higher degree of morphological and functional differentiation – again, similar to in vivo cell characteristics.

LM: Could you tell us about some of the challenges associated with using 3D models?

KB: Reproducible cell seeding and reliable formation of similar-sized 3D microtissues is essential for robust and repeatable results, especially when you’re integrating 3D models into high-throughput workflows. Generating consistent, reproducible 3D cell models can be problematic.

If you’re analyzing your 3D cell model using a high-content imaging approach, high-quality images are a crucial prerequisite for success, and capturing these images can be particularly challenging for large, thick 3D structures like spheroids.

Also, in a high-content assay, you’re aiming to capture very high-resolution images in order to analyze fine sub-cellular detail, but acquiring all of this information when you’re working with 3D cell samples may slow you down and undoubtedly increase the amount of imaging data that you generate. It can be a challenge to handle the huge volumes of data that imaging and analysis of 3D cell models produces.

LM: How are researchers able to overcome these challenges?

#1: Growing consistent 3D cell models

There are several means by which consistent 3D cell models can be produced. 

Specialized microplates with advanced surface coatings in which to grow spheroids are commercially available. For example, the use of ultra-low attachment (ULA) microplates is a popular method. It’s ideal if you need a simple and economical method to grow uniform spheroids. The synthetic plate coating ensures reduced cell-to-plate adhesion, which typically promotes uniform, single-spheroid formation. 

Other methods to generate 3D spheroids or support the structures of 3D cell model systems include agarose, hydrogels, scaffolds or even a combination of these substrates with growth factors. There are also physical methods to form 3D spheroids that include gravity or “hanging drop” systems, bioprinting and magnetic nanoparticles.

Seeding of cells, transfer of microtissues and medium exchange can be performed reliably using automated hand-held pipetting devices, but this is not practical when large numbers of spheroids are needed for high-throughput studies. In this case, automated liquid handling can provide greater efficiency and reproducible results.

#2: Obtaining high quality images

For high-content analysis approaches, confocal spinning disk imaging systems yield the best signal-to-noise ratios and highest X, Y, and Z resolution, while maintaining high-throughput acquisition. In addition, with a confocal high-content imaging system that combines laser-based excitation with two or four cameras, images are acquired at very high frame rates with minimal sample illumination. This reduces photodamage, so it’s ideal for imaging 3D cell models when multiple frames and fluorescent channels are required.

To image deep into 3D structures, you can use water immersion objectives, which have higher numerical apertures allowing capture of up to four times more light and providing higher resolution in X, Y, and Z than comparable air objective lenses. Furthermore, water immersion objectives have a smaller focal depth and therefore reduce the amount of contaminating light and background compared to air objectives.

#3: Minimizing imaging time and data volumes

Often, in imaging assays using 3D models or microtissues, only part of the total well area (where the 3D model is situated) will be of interest to you. Ideally, you only want to acquire high resolution data from that region and not spend time capturing data from the rest of the well.

With PerkinElmer’s PreciScan intelligent image acquisition technology (component of our Harmony high-content imaging and analysis software), you can accurately target regions of interest at low resolution and then image only the 3D cell model at high-resolution. This significantly reduces acquisition and analysis times, as well as reducing the amount of data you need to analyze and manage. 

LM: How can researchers get the most out of using 3D cell cultures?

KB: As an investigator, you might have spent months or years developing the appropriate cell model for your research. To get the most out of your 3D cell cultures, we suggest a high-content imaging and analysis approach to maximize the return on your investment.

Analyzing images in 3D, rather than 2D or 2.5D (maximum intensity projection), is recommended as these methods miss out on things like cell type distribution within 3D cell cultures, spatial differences between outer and inner spheroid layers and differences in subcellular morphology features. Investigators tend to avoid 3D volumetric analysis because it is difficult, cumbersome and there have been no seamless, integrated image analysis solutions available. Now, however, with solutions like PerkinElmer’s Harmony 4.8 software, you can segment and quantitate volume and morphology in 3D, better visualize and understand spatial relationships, plus accelerate 3D image acquisition and analysis.

To best understand your 3D cell model in drug discovery applications, full 3D volumetric analysis for validating and identifying targets, lead optimization, candidate selection or selective screening approaches is key to making informed decisions on screening strategies.

Karin Boettcher was speaking to Laura Elizabeth Mason, Science Writer for Technology Networks