Organoids and Complex 3D Models: Transforming Drug Discovery and Biological Imaging

For decades, drug discovery and biological research had depended on 2D cell cultures, comprised of single-cell layers grown on flat plastic dishes. While simple and easy to handle, these models ignore the true structure and complexity found inside living tissues.

In response to these limitations, scientists are adopting complex 3D models, like organoids, tumoroids, and induced pluripotent stem cell (iPSC)-derived structures. These models reflect the environments and functions of human organs, ultimately helping researchers predict how drugs affect human patients.

For context, organoids are tiny, organ-like clusters of cells grown in the lab. While not complete organs, they recreate key features of complete organs like distinct cell types, communication between cells, varied oxygen levels, and even necrotic cores, which are areas of cell death commonly found in tumors. Realism enabled by organoids allows researchers to study drug responses and disease mechanisms that conventional models, like 2D cell cultures, may miss.

The role of 3D models in drug discovery

The shift from the use of 2D cultures to the use of 3D cultures marks a major change in biomedical science research and drug development. 3D models have a variety of benefits to scientists that were not possible with 2D cultures. Specifically, 3D cultures can help provide researchers and scientists with more accurate, human-like data on drug activity and safety. They also capture complex cell interactions found in real tissue, like immune cell movement and nutrient gradients, while simultaneously supporting the development of personalized medicine, allowing for testing on patient-derived organoids.

The NAM Initiative: Driving change in research

A key driver in the shift toward the broader use of 3D cell cultures, like organoids, has been the New Approach Methodologies (NAM) initiative. This is a framework of programs and funding efforts led by U.S. agencies that aims to reduce animal testing by promoting in vitro and computational model research.

As a result, the biomedical community has seen more grant funding supporting organoids and 3D models. Labs have also been moving from animal models to advanced cell-based systems. Regulatory agencies are also taking action as they build guidelines and standards for organoid use.

Outside of the U.S., Europe is also investing heavily in the regulatory approval of non-animal organoid assays for drug discovery.

Imaging 3D models: Opportunities and hurdles

While the ability to visualize complex models using 3D models, like organoids, is revolutionizing how we understand drug responses, there are still challenges that the biomedical community must overcome to see widespread adoption of these 3D models.

One challenge is that, unlike 2D cell cultures, the deeper scientists probe into a 3D sample, the more light gets scattered or absorbed. This is often because most confocal microscopes can only see two or three cell layers before the image fades. These factors make it hard to examine what’s happening in the middle of an organoid, such as drug infiltration or immune activity. To address these challenges, researchers often leverage several techniques to overcome this hurdle. For example, optical clearing allows different chemicals to make samples translucent, enabling light to penetrate deeper. But, while this is effective for fixed (dead) samples, it is less helpful when cell cultures are still living.

Another strategy is lattice light sheet microscopy. This gives researchers deep, high-speed imaging of live samples. However, this strategy also comes with challenges, such as the cost of the technology and the need for extensive sample preparation. Finally, researchers also use near-infrared dyes, which allow light to penetrate further, enabling better imaging for deeper layers of an organoid.

In addition to light blocking, phototoxicity is another concern of 3D models. Repeated exposure to strong light, especially used in Z-stack 3D imaging technology, can damage live cells and fade fluorescent dyes. Researchers can help overcome phototoxicity with the use of specialized mounting media that keeps dyes stable, as well as photostable fluorescent dyes.

Hardware and software: Supporting the 3D revolution

As technological innovations are enabling scientists to overcome common hurdles present by 3D models, they also play a large role in making sure operations stay consistent throughout the process. Specifically, imaging live 3D samples demands precise environmental control, so microscopes require on-stage incubators to keep cells at the right temperature and CO₂ level. The solutions/innovations that scientists and researchers often use for this control often include automated z-stack (multi-layer) imaging, allowing them to monitor cellular behavior and structural changes without disturbing the microenvironment, as well as motorized stages for scanning entire samples or plates and high-resolution objectives for detailed views.

It is worth noting that handling vast amounts of image data is a challenge, but automation can let researchers image and analyze hundreds of wells with little manual effort.

AI and automation: Unlocking new potential

Not surprisingly, in recent years, AI and machine learning (ML) has changed how scientists analyze cell images. When leveraged correctly, AI/ML algorithms have the potential to spot subtle changes in cell shape and behavior, classify cell types and responses automatically, predict drug effects more reliably, and speed up analysis while reducing the need for manual labor.

In fact, recent reports have shown that AI-powered imaging increases throughput, improves data reproducibility, and boosts accuracy in drug screening.

Additionally, automation, like robotic handling and built-in software routines, can help enable high-volume screening, allowing labs to run hundreds or thousands of drug response tests quickly and consistently.

Reagents and tools for 3D model research

Labeling and tracking cells in 3D models require the right reagents. This means having the right:

• Fluorescent dyes to highlight organelles, cell structures, and proteins
• Antibodies that pinpoint cell markers for analysis
• Fluorescent reporter to monitor cell health, activity, and drug response

Reagents come in fixable (survive fixation for endpoint analysis) and non-fixable (for live cell work) classes. Online tools now help researchers select stains and reagents tailored to their experiment needs.

Practical tips for researchers

For researchers diving into 3D models to better understand drug response and disease mechanisms, it is critical to start with a straightforward question. Asking “What are you trying to measure?” helps scientists determine how complex their 3D model should be, ensuring that its design aligns with the overarching research goals.

With a variety of solutions available to scientists and researchers, it is also critical to choose technology that not only fits the workflow, but also balances hardware, software, and reagent options. Additionally, for those conducting 3D culture model research, it is beneficial to consult guides on 3D culture media, imaging, and analysis planning. Finally, researchers must stay informed. AI integration is growing fast, and it is crucial to keep an eye out for software updates and new hardware options that could contribute to meaningful outcomes.

The future: Smarter, faster, more ethical research

Taken together, these shifts point toward a clear future: as NAM funding expands and standards solidify, 3D organoid-based testing is rapidly becoming the new norm. Coupled with innovative technologies like automated light-sheet imaging and next-generation dyes, this enables deeper, faster, and more precise screening. The result is a research ecosystem that more faithfully models human biology—accelerating drug discovery, reducing reliance on animal testing, and advancing precision medicine.

Steve Titus is Senior Manager, Product Management, Protein and Cell Analysis at Thermo Fisher Scientific. He specializes in 3D cell models, imaging platforms, and translational research tools for life science labs.