When we talk about 3D models, we’re referring to in vitro techniques that allow cells to grow and interact in a three-dimensional environment. Unlike 2D cultures, which flatten cells into a monolayer, these models, such as spheroids, organoids, and bioprinted cell models, mimic not only the three-dimensional architecture of human tissues, but also the surrounding cellular microenvironment.
This includes elements like extracellular matrix composition, cell–cell and cell–matrix signaling, and mechanical forces, all of which influence how cells grow, differentiate, and respond to drugs. By recreating this dynamic and complex microenvironment, 3D models can better reflect in vivo biology and improve the predictive power of preclinical studies.
“The buzz around 3D models really began in the late 2000s and early 2010s,” says Morgan Hamon, PhD, Technical Sales Specialist at Inventia Life Science. “There was this big promise of personalized medicine, faster and safer drug development, and even the vision of lab-grown mini-organs. Media coverage amplified the excitement — ‘organs in a dish’ made for a compelling headline. And of course, the idea of reducing reliance on animal testing struck a chord with both scientists and the public.”
2D cultures have been a staple for decades, but they oversimplify biology. They limit cell–cell interactions and erase the critical role of the extracellular matrix. On the other hand, animal models introduce a different set of challenges: species differences that limit predictivity, high costs, and mounting ethical concerns.
“The attrition rate in drug development was another wake-up call,” Morgan notes. “When over 90% of drugs that look promising in animals fail in human trials, it highlights a systemic gap. Researchers realized we needed models that better represent human biology.”
A lot has changed in the past decade. Advances in stem cell biology and organoid technology have been critical. So has the development of new biomaterials, particularly xeno-free scaffolds that provide a more controlled environment.
“But the real turning point,” Morgan explains, “has been technologies like 3D bioprinting, which bring reproducibility and scalability into the picture. Add in automation, imaging, and data analytics, and suddenly you have a workflow that’s not just exciting but practical. And importantly, we now have a growing body of data demonstrating the utility of these models across applications.”
Academic labs were among the first to embrace 3D, using it to study development and tissue biology. With the development of applications for cancer and immuno-oncology research, drug discovery, and toxicity testing, major pharma companies and biotechs have been eager to adopt 3D technology to drive relevance, reproducibility, and scale in their programs.
“It’s been great to see this adoption accelerate,” says Morgan. “Large pharma and innovative biotechs alike are recognizing the value of these models, not only for improving translatability but also for streamlining drug screening workflows.”
“We’re also seeing patient-specific models built from iPSCs to study disease mechanisms and test therapies,” Morgan adds. “It’s still early days, but these approaches are beginning to influence translational research in a major way. The potential to move toward personalized, predictive models of disease is incredibly exciting.”
Despite progress, hurdles remain around standardization — both between labs and across the industry. Ensuring reproducibility at scale continues to be a challenge, as does striking the balance between complexity and usability.
“Accessibility is another issue,” Morgan points out. “While the technology is moving forward quickly, cost can still be a barrier, particularly for smaller labs. Making 3D more accessible without compromising quality is a challenge we all need to tackle. That’s exactly why we developed RASTRUM™ Allegro: to bring advanced 3D model generation into a high-throughput, reproducible, and more accessible format. RASTRUM Allegro helps bridge the gap between research innovation and everyday usability.”
Looking ahead, Morgan sees 3D models increasingly integrated with AI and computational approaches to boost predictive power. “I also think we’ll see more applications in diagnostics and personalized treatment planning,” he says. “And as regulatory frameworks evolve, these models are going to play a bigger role in reducing animal testing.”
“3D models have grown beyond the buzz,” Morgan concludes. “They’ve become essential tools that bridge the gap between simplistic 2D cultures and non-human animal models. With continued innovation and collaboration, we’re seeing them reshape biomedical research and drug discovery — moving from a future promise to a present-day reality.”
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