Mimicking the complex structure and function of the lung in a lab setting is inherently challenging. The UD-developed 3D lung model is unique in several ways. First, the model breathes in the same cyclic motion as an actual lung. That’s key, Fromen said. The model also contains lattice structures to represent the entire volume and surface area of a lung. These lattices, made possible through 3D printing, are a critical innovation, enabling precise design to mimic the lung's filtering processes without needing to recreate its full biological complexity.

“There's nothing currently out there that has both of these features,” she explained. “This means that we can look at the entire dosage of an inhaled medicine. We can look at exposure over time, and we can capture what happens when you inhale the medication and where the medicine deposits, as well as what gets exhaled as you breathe.”

The testing process

Testing how far an aerosol or environmental particle travels inside the 3D lung model is a multi-step process. The exposure of the model to the aerosol only takes about five minutes, but the analysis is time-consuming. The researchers add fluorescent molecules to the solution being tested to track where the particles deposit inside the model’s 150 different parts. 

“We wash each part and rinse away everything that deposits. The fluorescence is just a molecule in the solution. When it deposits, we know the concentration of that, so, when we rinse it out, we can measure how much fluorescence was recovered,” Fromen said.

This data allows them to create a heat map of where the aerosols deposit throughout the lung model’s airways, which then can be validated against benchmarked clinical data for where such aerosols would be expected to go in a human under similar conditions. 

The team’s current model matches a healthy person under sitting/breathing conditions for a single aerosol size, but Fromen’s team is working to ensure the model is versatile across a much broader range of conditions.

“An asthma attack, exercise, cystic fibrosis, chronic obstructive pulmonary disorder (COPD) — all those things are going to really affect where aerosols deposit. We want to make sure our model can capture those differences,” Fromen said.

The ability to look at specific disease features, say, narrowing of the airways or accumulation of mucus, could one day contribute to more personalized care. For example, perhaps a patient might need longer doses of medicine because the medication is not getting saturated in the body site, or possibly they need a redesigned patient inhaler, so it targets a specific region. This is currently difficult to implement, but the UD-developed model provides a baseline tool for asking those questions.

“This is important because, right now, inhaled pharmaceutics are designed with a one-size-fits-all approach. But someone who has severe COPD, for example, is going to breathe very differently and have a very different lung structure than someone who is healthy,” Fromen said. 

Additionally, many inhaled medicines fail clinical trials for unknown reasons. When it doesn't work, researchers wonder, is it the molecule that isn’t effective, was the formulation flawed? Or did the molecule fail to accumulate at a certain level at its target in the lungs?

According to Fromen, clinical trials typically focus on whether a medication results in measurable improvement in a disease, while the UD-developed tool can provide deeper insights. It can determine whether the aerosol got where it needed to go in the first place, and in the right amount, potentially saving time and effort in formulation development and reducing setbacks during clinical trials.

The researchers shared their design and methods in an open-source format, in hopes others will adopt the UD-developed technique.

“Making it accessible to other researchers opens the door for impactful collaborations,” Fromen said. “Clinicians can provide priority patient profiles for us to model, while pharmaceutical developers could integrate the model into their workflows to optimize treatments for specific respiratory conditions.” 

Beyond applications in pharmaceutical development, the UD-developed model is also proving valuable in other fields. In a newly funded project with the Army Research Lab, in partnership with a group at Aberdeen Proving Ground, Fromen is using the UD-developed model to help toxicology researchers understand environmental exposures — not only how far things get in, but how much gets in over a given time span and how much is depositing in what regions of the lung, and what the impact is, positive or negative.