The performance of your device in combination with your drug plays a crucial role in the success of clinical trials. Relying solely on in-vitro aerosol laboratory experiments to predict this success carries substantial risks.
Different deposition patterns resulting from different nebulizers simulated with Twinhale, our high-fidelity in silico model
Leverage digital evidence from Twinhale - the world's best in silico model for pulmonary drug delivery
Schedule meeting nowUsing Twinhale, developers can assemble virtual patient cohorts tailored to a specific drug, device, or indication. In silico inhalation simulations are then performed across these cohorts to systematically evaluate how design choices - such as device configuration, operating parameters, formulation, and dosing - affect regional drug deposition.
This approach transforms an effectively unlimited design space into a small number of well-characterized, data-driven options. Twinhale provides quantitative evidence on where an inhaled drug is delivered in the lung and under which conditions, enabling informed optimization of locally delivered dose.
By accounting for patient variability and process uncertainty before entering the clinic, Twinhale helps de-risk development decisions, refine trial design, and improve confidence in downstream clinical outcomes.
Schedule a 1h meeting where we identify your requirements. We will then design the in silico trial and select a suitable digital cohort.
After you receive and reviewed our proposal for your customized in silico trial, we will run the in silico trial and analyze the results.
Receive your results within 2 weeks providing you with quantitative and actionable insights.
Patient-specific lung geometries forming the basis of our digital twins. Find out more about how we generate in silico evidence using Twinhale here.
“We chose Ebenbuild because of their strong scientific expertise, very innovative technology and highly motivated team”
"Working with Ebenbuild allows us to simulate drug deposition in diseased human lungs without performing extensive clinical studies."
Get your product to market in record time by harnessing the power of next generation in silico technology
Make crucial design or supplier decsions with confidence and peace of mind.
Our collaboration is key to unlocking the potential of the digital age in drug development, enhancing the health and well-being of millions of people. They count on us.
Regulators are increasingly encouraging credible, human-relevant alternatives to traditional testing. Recent FDA and EMA initiatives highlight the role of New Approach Methodologies (NAMs), including computer simulations and in silico modeling, while FDA's Model-Informed Drug Development (MIDD) program continues to create structured pathways for discussing model-based evidence in development and regulatory review. For orally inhaled drug products, recent work by FDA-affiliated authors specifically describes lung regional deposition modeling as potential model-integrated evidence (MIE) when supported by validation data and model credibility. Twinhale is built for this shift: scalable in silico trials that quantify patient-specific regional and local lung dose before clinical trials begin.
FDA-affiliated perspective on lung regional deposition modeling as model-integrated evidence (MIE) for locally acting orally inhaled drug products.
FDA program supporting structured interactions on model-informed approaches in drug development and regulatory review.
Highlights regulatory momentum toward human-relevant methods, including NAMs and computational approaches.
Outlines expectations for validating NAMs, including in vitro, computational, and in silico approaches.
Shows European regulatory momentum toward qualified virtual evidence approaches and reduced animal use.
In silico evidence supporting the preclinical evaluation of inhaled connective tissue growth factor for the treatment of IPF.
Read more
Adaptive Breath-actuated Mesh Nebulisers: Using In Silico Evidence to Demonstrate Optimisation of Lung Deposition.
Read more
An Enhanced Approach to Predicting Site Specific Inhaled Drug Deposition in Humans via In-Vitro and In-Silico Data Fusion
Read more
Study details not yet public.
Study details not yet public.
