Deep-Tech Firm Ebenbuild Validates Lung Digital Twins For High-Precision Inhaled Drug Delivery Predictions

Ebenbuild study in Nature Communications Medicine confirms digital twins accurately predict inhaled drug deposition with 0.95 correlation to clinical data.

By: AXL Media

Published: Apr 15, 2026, 7:39 AM EDT

Source: Information for this report was sourced from EurekAlert!

Closing the Gap in Respiratory Drug Measurement

A significant hurdle in respiratory medicine has long been the inability to measure exactly how much of an inhaled medication reaches its specific site of action. Local drug deposition is a complex variable influenced by individual anatomy, fluctuating breathing patterns, and structural changes caused by disease. Traditionally, pharmaceutical developers have relied on population averages or late-stage clinical outcomes to make dosing decisions. However, Ebenbuild GmbH has introduced a patient-specific digital twin technology that transforms standard CT scans into high-resolution models. These twins allow researchers to visualize and quantify aerosol transport across both conducting airways and the alveolar region for the first time.

Physics-Based Modeling of Lung Mechanics

The core of Ebenbuild's innovation lies in its application of physics-based computational modeling to analyze the entire respiratory system. By simulating airflow, tissue mechanics, and aerosol transport at the individual patient level, the platform provides a comprehensive view of lung function. This approach accounts for the mechanical properties of the lung, such as the stiffness found in patients with idiopathic pulmonary fibrosis (IPF). By treating the lung as a dynamic, individualised environment rather than a static organ, the digital twin technology replaces broad assumptions with precise, data-driven evidence of how drugs interact with specific tissues.

Validation Against Gold-Standard Clinical Imaging

The study published in Nature Communications Medicine rigorously tested the digital twin's performance against 3D SPECT/CT imaging, which is the current clinical reference standard for assessing drug deposition patterns. The results demonstrated an exceptional quantitative agreement, with lobar deposition predictions achieving a correlation coefficient of 0.95. This level of accuracy confirms that the "in silico" (computer-simulated) model can reliably mirror "in vivo" (biological) results. This validation is critical for establishing trust in computational models within the medical community, proving that virtual simulations can be just as rigorous as traditional experimental methods.