A recent study led by Dr Richard McNair highlights the role of the Marangoni effect in surfactant spreading, offering potential improvements in drug development and delivery for lung diseases.
3d illustration of lungs
A new study from the University of Manchester provides fresh insights into the dynamics of surfactant spreading in the lungs, potentially advancing targeted drug delivery for respiratory conditions. Led by physicist Dr Richard Mcnair, the research explores the Marangoni effect – a phenomenon where fluid flow is driven by differences in surface tension.
In this interview, Mcnair discusses his groundbreaking work and its potential application in improving treatments for conditions such as acute respiratory distress syndrome (ARDS), a severe lung condition where fluid builds up in the air sacs, making it difficult to breathe and depriving the organs of oxygen. Recently published in Physical Review Letters, this study builds on a series of earlier works, including two papers in The Journal of Fluid Mechanics, that examine fluid dynamics in complex biological systems.
The Marangoni effect: a key to drug transport
Mcnair’s research focuses on how surfactants – substances that reduce surface tension – affect the transport of pharmaceuticals through the intricate network of lung airways. His work investigates how the Marangoni effect can be leveraged to deliver drugs more effectively to specific areas of the lung. “This work can help researchers understand how the global effects of spreading in a large complex network can affect drug transport,” Mcnair explains. “Researchers will want to know how far pharmaceuticals can be transported deep into lung airways by Marangoni forces alone, and this research lays the groundwork for more sophisticated models for this.”
Researchers will want to know how far pharmaceuticals can be transported deep into lung airways by Marangoni forces alone, and this research lays the groundwork for more sophisticated models for this.
By developing a model of how exogenous (externally administered) surfactant spreads through the lung’s intricate network, Mcnair’s research provides valuable insights for clinicians and pharmacologists. Although he emphasises that he is not a clinician or pharmacologist, he recognises the significant impact his work can have on these fields. “I am not a clinician or a pharmacologist, so I cannot comment on specific drugs,” he clarifies. “However, hydrophobicity of solute that a clinician might want to spread deep into the lungs using a surfactant-based method might be important as the pharmaceuticals would be spread deeper if they can remain at the surface of the flow.”
From maze experiments to lung models
The current model developed by Mcnair and his team is best suited to larger liquid volumes, similar to those used in laboratory maze experiments. In these controlled environments, gravity plays a significant role, keeping the liquid surface relatively flat. However, the dynamics change dramatically within the much thinner liquid layers of the lung, where the influence of gravity compared to surface tension is reduced.
“The model we have produced is appropriate for the larger liquid layers in the maze experiments,” Mcnair explains. “In this situation, gravity dominated over Marangoni forces, keeping the interface approximately flat. In the much thinner liquid layers within the lung, the relative strength of gravity to surface tension forces is much smaller, which changes the fluid dynamics. Modelling this over a network structure is more complicated, but still very doable with the modelling machinery we have created.” Despite the added complexity, Mcnair believes that the existing modelling framework can be adapted to accurately simulate these dynamics within the lung’s complex structure.
Natural surfactants: a complicating factor
The presence of natural surfactants within the lungs introduces an additional layer of complexity. These naturally occurring surfactants interact with the exogenous surfactants, creating a global surfactant field that influences the overall spreading dynamics. “Natural surfactants and the exogenous surfactants combine to create a global surfactant field,” explains Mcnair. “This global field means that information about the structure of the entire geometry is communicated to every other point, affecting spreading dynamics. As every lung network is different, this means that the spreading dynamics in every lung will be slightly different.” He explains that the presence of natural surfactants can hinder certain treatments, as their concentration increases in the distal airways, preventing the effective spreading of exogenous surfactants. By quantitatively understanding these interactions through his modelling techniques, researchers can develop strategies to overcome this challenge.
Future directions: real-world data and heterogeneous spreading
McNair’s research is an ongoing process. He highlights a project, initiated during his PhD, that involves applying maze models to real-world lung geometry data.
“A piece of research we started during my PhD involves using the maze models on real data of lung network geometries. This is work we may look at continuing in the near future. This will give a better picture of how the large lung network can affect details of the spreading. One question we could then answer is about how heterogenous the spreading might be in such a complicated network.” This work, which he hopes to continue in the future, promises to provide a deeper understanding of how the intricate lung network influences surfactant spreading. One key question this research aims to address is the potential for heterogeneous spreading, where surfactant may penetrate further into certain lobes of the lung than others.
As Mcnair’s research progresses, it holds the promise of not only improving our understanding of surfactant dynamics but also advancing targeted drug delivery methods that could revolutionise treatments for respiratory diseases. As new data and technologies continue to emerge, Mcnair’s work provides a crucial foundation for bridging the gap between complex fluid dynamics and practical, life-saving medical treatments, ultimately benefitting both clinicians and patients alike.
Meet Dr Richard Mcnair
Richard Mcnair
Richard Mcnair is a postdoctoral researcher from Staffordshire, currently working at the University of Manchester, where he focuses on modelling exchange and transport in the human placenta. Mcnair earned a first-class BSc in mathematics and physics from the Open University before going on to complete an MSc in applied mathematics in 2019. He completed his PhD in 2023 at the University of Manchester, specialising in surfactant dynamics.