Researchers from the Max Planck Institute of Computer Science and the University of California, Davis, have developed a novel technique that uses advanced computational methods. This method is based on creating a specific shape of an object dedicated, for example, to be implanted into the patient’s body to ensure controlled release of the drug. This discovery has significant implications for the pharmaceutical industry, which is currently intensively researching and developing 3D printing technologies.
Controlling the level of drugs in patients’ bodies is an important element of medical therapy. When administered intravenously, the concentration in the blood is determined by the drip rate multiplied by the proportion of the drug in the solution to be infused. Steady drug levels can be achieved by administering a high dose initially and then maintaining it for lower doses. When administered orally, such a regimen is much more difficult to ensure. The possibility of using multi-component, multi-material structures with different drug concentrations in different places is difficult to achieve. On the other hand, the advancement of 3D printing technology enables the creation of complex shapes, and thus the production of drugs with a constant biochemical distribution in the carrier material. For such drugs, the release depends solely on the geometric shape, which is easier to ensure and control.
The project led by Dr. Vahid Babaei (MPI for Computer Science) and prof. Juliana Panetta (UC Davis), is about creating 3D objects that dissolve over time, releasing their contents in a controlled manner. Through an innovative combination of mathematical modeling, lab experiments and 3D printing, the team is able to print 3D shapes that deliver a specific amount of the drug as it dissolves. This can be used to set predefined drug concentrations by oral administration.
Since there is no possibility of external influence on the process in the digestive tract after ingestion, the desired time-dependent drug concentration must be generated by the shape (active surface that dissolves) of the sample. With some effort, time-dependent dissolution can be calculated from a given geometric shape. For a sphere, for example, it is strictly proportional to the decreasing spherical area. The research team proposes a forward simulation, based on the geometric intuition that objects dissolve layer by layer.
The key role here is played by topological optimization (TO), which allows the simulation to be flipped forward to find a shape exhibiting a particular property. Originally developed for mechanical components, TO has found wide application. The team is the first to propose an inversion strategy to find shape based on release behavior using topological optimization. The dissolution is checked by experiments: the measured release curves are very close to the desired values.
In the experiment, objects are printed using a filament-based 3D printer. The dissolution is then evaluated by the camera system, i.e. actually measured, not just calculated by a mathematical model. For this purpose, the optical transmission of the solvent is recorded optically. In contrast to the measurement methods commonly used so far, which directly determine the concentration of the active substance (e.g. by titration), this method is much faster and easier to set.
The reverse design method can also take into account the different feasibility constraints of different manufacturing systems. For example, it can be modified to generate extruded shapes, which does not interfere with mass production. In addition to the discussed pharmaceutical use, further possibilities include the production of catalytic bodies or even coarse fertilizers.
Source: www.mpi-inf.mpg.de