Introducing Experts @ Greiner Bio-One: Dr. Glauco R. Souza

At Greiner Bio-One, scientific expertise is more than a claim — it’s part of our daily work. In this portrait series, we introduce the experts behind our solutions, share authentic insights into their fields, and show how research turns into products that create real value for our customers.

About Dr. Souza

What fascinates you most about your subject area?

As a chemist, I see it this way, cells are smart: place them in the right proportions, the right geometry, with the right “touch” between them — and they do exactly what they’re supposed to do.

That geometry matters at every scale — from how individual cells contact each other, to how tissues organize across space and time. And it’s not always Euclidean. Tissue geometry can be Euclidean or fractal — and fractal dimensions can be spatial, temporal, or both. Snowflakes are a familiar example of spatial fractals — self-similar patterns repeating at every scale. The same logic appears in blood vessel networks, lung airways, neuron dendrites. Temporal fractals are subtler — think of heartbeat variability. My PhD dissertation was in fractal geometry of nano aggregates to detect and characterize DNA and proteins — so this isn’t abstract to me, and it is a topic that still keeps me up. The spatial dimension we’ve made progress on. The temporal dimension is still largely unexplored — achieving the resolution needed to track cell movement in real time remains one of the hardest open problems in the field.

Two dimensions — compounds that looked promising, failing in patients. The biology wasn’t wrong. The model was.

What is the central question currently occupying you in your work?

How do we make advanced cell culture models routine at scale? The biology is solid across 3D, HTS, and mass cell culture. The challenge is integration — fitting these models into existing workflows so labs can adopt them without rebuilding everything. That requires the right consumables, instrumentation partnerships, and application support that meets scientists where they are. That translation is where I spend most of my time.

Can you give an example of how your research or expertise is directly incorporated into products or processes at Greiner Bio-One?

Bioscience requires convergence — surface/material chemistry, optics, cell biology, high-throughput screening. It all connects. That’s what makes it interesting. Looking ahead, AI makes this moment hard to ignore. Better models, richer data, patterns we wouldn’t know to look for.

What motivates you every day in your work at Greiner Bio-One?

The opportunity is here — the science, the market, the regulatory tailwinds all point in the same direction. Greiner Bio-One has the potential and global reach. The goal is to connect those dots. Balancing science, strategy, and people every day.

What changes would you like to see in everyday laboratory work or diagnostics over the next five years?

Advanced cell culture models as the default, not the exception. Most screening labs still run primary assays in 2D because the infrastructure is already there and habits are hard to change. In five years, I want 3D and HTS-compatible models integrated into standard workflows — routine, automated, validated. The tools exist. The science is clear.

The regulatory environment is moving that way too. The FDA Modernization Act 2.0 opened the door to non-animal testing methods for drug applications. In April 2025, the FDA went further — releasing a formal roadmap to phase out animal testing requirements, starting with monoclonal antibodies, with the stated goal of making animal studies the exception rather than the norm within 3 to 5 years. In Europe, the 3Rs movement — Replace, Reduce, Refine — has been reshaping preclinical standards for years. These aren’t fringe positions anymore; they’re policy. The science and the direction of regulation are now aligned. The next five years are about execution — building validated, scalable platforms that make that transition real in laboratories everywhere.

What is a common misconception in your field – and what is your view on it?

That the name predicts the performance. Spheroids, organoids, tumoroids — the label doesn’t determine the biology. A well-designed spheroid can be just as predictive as an organoid. And not all cells form organoids — nor should they have to. The question is always whether the model recapitulates what matters for the experiment.

If you could give one piece of advice to a young scientist or medical professional – what would it be?

The secret of happiness is NOT doing what you love — it’s loving what you’re good at. Find out what you’re good at. Then learn to love it. The curiosity, the passion, the drive — those tend to follow.

I try to teach my children that, too. It doesn't always work out. But I'm not giving up.