- – Center for Applied Tissue Engineering and Regenerative Medicine, Munich University of Applied Sciences
- – Heinz-Nixdorf-Chair of Biomedical Electronics, TranslaTUM, Campus Klinikum rechts der Isar Technical University of Munich
- – Center for NanoScience (CeNS), Ludwig-Maximilians-University
- – Department of Applied Sciences and Mechatronics, Munich University of Applied Sciences
- – Institute of Biomaterials and Biomolecular Systems, University of Stuttgart
As we seek to accelerate our understanding of tissue and organ physiologies, the ability to engineer advanced, bio-inspired 3D microfluidics comes into focus. These combine intricate vascular systems with organotypical extracellular matrix architectures, composition and biophysical traits. While they could lead to advancements such as increased accuracy of drug testing and even the production of entire organs, engineering such systems proved to be an onerous task. Until now.
Tapping into the power of Algorithmic Engineering and Hyperganic Core, a model of the vascularized alveoli was printed in polymer and proteinaceous resin using two-photon stereolithography.
Bioprinting and Its Different Design Approaches
Bioprinting is one of the most exciting fields within Additive Manufacturing. Instead of polymers or metal powders, hydrogels infused with living cells (so-called bio-inks) serve as printing materials. This allows researchers to fabricate tissues in-vitro, recapitulating biological systems. Currently, most prints happen on a small scale with focus on how cells survive and evolve within the printed scaffolds. The immense potential of bioprinting runs the gamut: from patient-specific drug tests to the reduction of animal testing or to the ability to print and grow entire organs tailored to our individual immune systems.
One approach to generate objects for bioprinting is to use CT scans of native tissue. While CT scans match their native counterparts to a high extent, they provide a fixed geometry with limited options for geometric adjustments. However, to methodically study derivatives of biological systems, print templates must have the ability to be adjusted systematically. The other approach is with parametric CAD tools, which allow for the design of multiple variations, but they are not optimized to generate organotypical geometries.
Hyperganic’s New Approach
At Hyperganic, we create automated engineering workflows using algorithms to generate physical objects. We call this new paradigm Algorithmic Engineering. We liken the algorithms we write to the DNA of an object that tells it how to grow. Through this unique design approach, we have the ability to mimic natural growth patterns in order to engineer organic shapes and systems.
This particular project was a collaboration between Hyperganic and Germany’s leading bioengineering institutes with the goal of printing and studying alveoli – tiny air bubbles within our lungs on the scale of the cross-section of human hair. Alveoli transport oxygen from the air we inhale into our blood vessels.
The aforementioned Hyperganic’s algorithms not only created one alveoli, but an entire application to generate hundreds and thousands of different alveoli. Our design starts with the bubbly base shape that represents the air sacs. A ventilation inlet and an outlet are then integrated to that base shape that is spanned by a vascular system composed of a set of capillary tubes. These algorithms allow for parametric sweeps of the key geometric features, such as the air sac size, the degree of vascularisation and wall thickness.
An interesting aspect of biological systems is that their macroscopic properties are often driven by microscopic randomness. No two repetitive subcomponents within a tissue will ever look the same! Their properties and phenotypes vary within certain ranges and distributions. The same variation can be achieved through Algorithmic Engineering. Design rules within the algorithms can be overlayed with artificial randomness. For instance, while the average air sac size and capillary branching behavior can be specified, the actual generated instances will slightly deviate from these input values.
“While using CAD tools, I often struggled to design organotypical bioprinting templates. Considering the lengthy process of modeling alveoli in CAD, I was surprised by how quickly and effortlessly Hyperganic Core had allowed me to create not only one but a limitless variety of these biomimetic scaffolds. This was especially true for the generation of interconnected vascular networks, which are automatically adjusted to the tissue to be perfused, enabling us to perform extensive research on angiogenesis.”Amelie Erben, PhD
Business Development, Hyperganic
Following the Algorithmic Engineering phase, the alveoli models were printed in both polymer and proteinaceous resin. Even at a diameter of 0.5 mm, the plastic print reveals astonishing levels of detail under a scanning electron microscope.
At 0.3 mm in diameter, the print using actual proteins is even smaller. Under a confocal microscope, the details still shine through, highlighting the printability and resolution of these delicate objects.
What The Future Holds
With Hyperganic’s Algorithmic Engineering solution, we are empowering the rapid generation, iteration and optimization of organotypical scaffolds and accelerating research on tissue-specific physiologies. As a result, these advances translate into healthcare customization – i.e., the possibility to grow organs tailored to individuals as well as patient-specific drug tests, and simultaneously reduce animal testing practices.
This collaboration marks the first research application to feature Hyperganic’s new design and engineering paradigm in a scientific publication. Over the next months, more of such collaborations will come into fruition as we onboard additional innovative scientists and engineers onto the Hyperganic Core software platform. More to come – stay tuned!
Read the full paper here.