Proper, consistent and correct biomechanical characterization is very important for 3D bioprinted scaffolds. Conventional approach foresees pre-selection of the material model and fitting experimental data to quantify properties in time and spatial scales. For injectable biomaterials the interaction of the biomaterial and the system as well as various dissipative phenomena (often uncontrolled) make translation of the model outcomes to real devices difficult. With MDR 2017/745 and HTAR 2021/2282 manufacturers are required to characterize biomaterials and medical devices in the proper way to ensure correct risk and hazard assessment. This might be compromised if the artificially fitted data or incomplete ISO-based tests are deployed in realistic injection systems (including 3D bioprinting).
New patented BEST method (Biomaterials Enhanced Simulation Testing) enables a model-free assessment of invariant constitutive parameters of both bioprinted materials and the extrusion-based process. The method allows determination of e.g. biomaterials viscostiffness,
permeability, and other properties without a need of selection of material model and without use of complex transforms in frequency domain. As an example, a simple injection test of a hydrogel from syringe system shown to result in measured elastic and friction transition points, the onset of elasto-viscous transition, conditions for developing of viscous flow, characteristic response time and Deborah number, intrinsic system stiffness etc. - all from the single experiment. Such data are usually impossible to obtain from conventional rheology measurements, which suffer from mainly artificial assumptions or wrong boundary conditions (like use of complex modulus, which is not a physical quantity), lack of control of momentum diffusion, possible viscoelastic waves, low-Re secondary flows, uncontrolled elastic instabilities at high Wi numbers, etc.
This model-free approach is based on constitutive equations for a biomaterial, tissue or composite without fitting parameters or assumptions – the only one is the causality principle (no response before stimulus). This eliminates needs for complex math, locality, artificial models, etc. using the only real physical data.
The method enables coherent testing at physiologically and/or clinically relevant conditions beyond standards (“do what’s right, not what’s easy”) and supports high-output screening (more data, less time and costs) in lieu of high-throughput, saving the lab and pre-clinical costs, and
increases ethical value. Such testing is compliant with requirements of MDR 2017/745 and going beyond the data achievable with conventional standards and protocols.