Intro

What if the failure rate in clinical trials isn't about picking the wrong drug candidates—but about testing them in the wrong models?

When you move cells from a 2D culture plate into a bioreactor, you're not simply scaling volume. You're fundamentally changing the biological context. Cell density shifts. Mass transfer dynamics evolve. Mechanical cues emerge. The cells sense these changes and respond—often in ways that derail strategies built on oversimplified assumptions.

Most preclinical research still relies on flat plastic surfaces and animal models that miss critical aspects of human biology. The result? Therapeutics fail late in development because the models couldn't predict how human tissues would actually respond.

In this episode, David Brühlmann speaks with Catarina Brito, Principal Investigator at ITQB NOVA and Head of the Advanced Cell Models Laboratory at iBET and ITQB NOVA in Portugal. Catarina's career-defining insight came early: studying glycan-protein interactions in murine versus human cells revealed that species differences weren't just nuances—they were fundamental gaps that could mislead entire research programs.

Catarina and her team have developed neural, liver, and tumor models that capture the multicellular complexity and microenvironmental cues that 2D cultures cannot replicate. Her work creates preclinical models sophisticated enough to predict human responses while remaining scalable for drug development workflows.

Highlights of the episode:

• Limitations of traditional 2D cell cultures and animal models in capturing realistic tissue behavior and therapeutic responses (06:27)
• Catarina Brito's personal scientific journey: from discovering model limitations to pioneering 3D culture systems in neural and liver tissues (04:19)
• How advanced 3D models recreate cell-to-cell interactions, tissue-specific microenvironments, diffusion gradients, and multicellular complexity (10:35)
• Regulatory movements toward reducing animal models, and the challenge of validating advanced alternatives for systemic biology studies (09:10)
• Key differences in designing bioreactors for various cell types, with practical examples from liver and neural models (15:16)
• The impact of scalable, robust 3D models on accelerating drug development and improving selection of candidate therapies (17:22)

Key Takeaway:

Bioprocess development starts when you choose the model that validates your therapeutic approach. If that model can't capture the biology that matters, every downstream optimization is built on a flawed foundation.

In Part 2, Catarina reveals how 3D tumor microenvironments expose drug resistance mechanisms invisible in 2D cultures, and her vision for AI-powered digital twins enabling personalized medicine.

Subscribe & Review:

If this conversation changed how you think about preclinical model selection, leave a review on Apple Podcasts. Your reviews help other biotech scientists discover these insights.

For more CMC development insights, visit smartbiotechscientist.com.

Connect with Catarina Brito:

LinkedIn: www.linkedin.com/in/catarina-brito-ibet

Advanced Cell Models Lab – iBET: www.ibet.pt/laboratories/advanced-cell-models-lab

Next step:

Need fast CMC guidance? → Get rapid CMC decision support here

Support the show