Bruker launches a new system created thanks to a technological development by Ricardo García’s group

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The multinational company Bruker has just launched the ViscoDirect software module, which enables the automated, artificial intelligence-assisted measurement of the viscoelastic properties of soft samples—specifically, biological cells and tissues. This technological development was made possible by the work of Ricardo García’s team at the Madrid Institute of Materials Science, part of the Spanish National Research Council (CSIC).

The development from ICMM-CSIC uses AI to predict the viscoelastic properties of cells based on data obtained via atomic force microscopy (AFM). These viscoelastic properties can serve as indicators of disease. Licensed in 2025, this is the first patent of its kind developed in Spain and one of the first worldwide.

Thanks to this Spanish development, the multinational now offers the ViscoDirect software module for its own NanoWizard BioAFM platform. This advancement enables automated, AI-assisted viscoelastic analysis of living cells, tissues, and soft matter, significantly improving the speed and ease of atomic force microscopy (AFM) experiments.

“The force microscope works very well, but it has limitations related to the speed at which data is acquired and processed,” explains García, who emphasizes that this issue of timing is crucial in biomedicine: “Speed ​​and numerical precision are essential in this field. It is necessary to analyze many samples to obtain reliable statistics, ensuring that individual variability does not lead us to erroneous results.”

With this idea in mind, his team began developing AI code a few years ago to streamline the analysis of data obtained via AFM. “Using the information we receive through AFM, our artificial intelligence method allows for a faster prediction of a cell’s physical state,” the researcher explains. With his new algorithm, data processing tasks that previously took an average of eight hours can now be completed in just 30 minutes.

The first results emerged about two years ago, and since then, they have worked hand in hand with Bruker on a patent license. This is the first license for AI applied to atomic force microscopy signed by Bruker—a multinational company that manufactures scientific instrumentation for molecular and materials research, as well as for industrial and applied analysis.

“Using supervised machine learning, this unique fitting module extracts viscoelastic parameters from force-distance curves (FDCs) obtained during AFM measurements. This simplifies applications such as mapping mechanical gradients, characterizing the multiscale structure of cells, and quantifying the time-dependent behavior and viscoelastic response of hydrogels, polymers, and colloidal materials,” the company explains.

These are advances that show how laboratory work makes its way into the industry, which in turn leads to improvements in the research itself. “With these new methods, we are achieving greater spatial, numerical, and temporal precision,” concludes García.

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