How is FRI a solution to your research question?

How is FRI a solution to your research question?


We’ve said it before: the respiratory field is the most expensive one in the pharmaceutical world. The low sensitivity of several clinical biomarkers make it difficult for therapy developers to limit the size of their trails. Similarly, in the clinical domain, high costs occur among others from insensitive or difficult measurements, late detection of disease (progression), and the chronic nature of many diseases.


Let us help you…

optimize therapy delivery
for the right patients

And detect…

any signal of efficacy
within the right safety margins

To ensure…

the optimal value proposition


It is time for change.

Because in the end, it is the patient who will suffer as a consequence. We are convinced that we can make the difference which the respiratory field so desperately needs, and together with many we have already been part of that change. FRI (functional respiratory imaging), when appropriately implemented as clinical endpoints in study designs, has downsized clinical trials significantly in both cost and time. With reductions in sample size up to 16 times [Mignot B., et al. ERS 2017], reductions in trial duration of more than 2 years [De Backer W. et al., ERJ 2014; Martinez F. et al., The Lancet 2015], and with FRI’s capability to detect the smallest signs of efficacy or effectiveness [Vos W., et al. Respiration 2013], the imaging endpoints have been able to bring better therapies to the patient faster than ever. However, we’re not there yet. We can help you to be part of that change as well. By combining our expertise with our technology, we will help you to optimize your therapy delivery and make sure it happens in the right patient population. We will help you to better understand your therapy benefits and therefore enable you to offer the highest value proposition. Bare with us to find out how FRI can be tailored towards your specific research question.

When you’re reading this article, the chances are real that you’ve heard of FRI before. Maybe from personal experience or from articles in the literature, or maybe you haven’t. Either way, FRI and how it is a solution for your specific therapy or drug development is not always completely straight forward. The reason for the complexity is due to the high potential of individualisation of the biomarkers. They can be tailored towards any type of respiratory related study or patient based on the anticipated results, the specific therapy, the disease manifestation, and the intended goal. In order to guide you towards what you are looking for, the FRI applications have been split into 4 categories: Therapy analysis, Delivery optimisation, Disease characterisation and Marketing excellence.


What is FRI?

FRI or functional respiratory imaging exists out of a set of distinct endpoints that analyse exposure, structure and function of the lungs and airways of any respiratory disease. The process behind the endpoints starts with High-Resolution Computed Tomography (HRCT) scans from the patient . These are taken at full inspiration level (TLC or Total Lung Capacity) and at expiration level (FRC or Functional Residual Capacity). Using FRI tailored programmes (Mimics and 3-Matic), the different respiratory structures (airways, lobes, blood vessels, air trapping, fibrosis, etc.) get segmented based on their Hounsfield Units (HU). These segmented voxels then represent the CT scan in a 3 dimensional way . Finally, these 3D geometries get quantified and result in the different FRI endpoints or are combined with CFD (Computational Fluid Dynamics) to quantify airflow and exposure .

Image aquisition

Structure segmentation

 Flow simulation

Delivery optimization

Is it possible to determine true lung deposition of my drug-device combination without needing to set-up a full scintigraphy study?

FRI aerosol deposition is your ultimate tool to optimise your particle or device delivery due to three reasons. First of all, these type of studies go extremely fast. Usually, once we obtain all the input data to run the study, first results can be delivered after 6 to 8 weeks. The reason for this is linked to the fact that no patient inclusion is necessary, since FLUIDDA has a database of airway geometries of different populations. Secondly, it is very easy to investigate how different inhalation scenarios (different particles (APSD data), different devices, different populations, different breathing profiles…) affect deposition in a controlled environment. Already as of very early pre-clinical stages, you can easily assess the influence of disease on your device performance or aerosol deposition. Lastly, the deposition results match reality. FRI aerosol deposition has been validated against scintigraphy and SPECT-CT multiple times showing that the results are the same.

Find out more about how FRI deposition is the same as scintigraphy here.

Therapy analysis

Is it possible to establish efficacy/effectiveness and safety in a small sample (even though I don’t expect much changes) with high confidence?

Due to the high sensitivity levels of the FRI measurements, any change that is induced by the therapy will be picked up. Since the endpoints have been used in many different trials over the past decade, they have been validated extensively with clinically relevant endpoints. The high sensitivity and clinical relevance have several important implications. The inclusion number can be kept small (often less than 10 patients will do to show significant results). In the early development phases, this means that you can easily combine efficacy measures with safety measures to maximize confidence before going to the later phases. In later development, this implies that you can decrease development costs enormously and safe quite some time by faster recruitment, which is particularly interesting in rare diseases.

Disease characterization

Is it possible to phenotype disease, to evaluate disease progression, or to predict events with sensitive and meaningful parameters?

At any stage in your development, it is extremely important to understand your target disease. Better disease description will help you understand how exactly your therapy improves the patient’s health. The clinically relevant FRI endpoints are sensitive enough to detect disease progression at very early stages. Not only does that help you to increase your target population, it will allow you to match your therapy to your target population much better. Our machine learning services are there to help you predict any kind of event happening in the population such as exacerbations [Lanclus et al., 2018 (in review)], lung rejections [Barbosa et al., Acad Radiol., 2018],…

Marketing excellence

How can I transform my scientific results into meaningful and intuitive communication if they’re only allowed to be scientific?

The FRI results are not only boring numbers and graphs. Due to the nature of the process, results can easily be visualised in three-dimensional, patient-specific airways and lungs. This means that your study results obtained from FRI, or real disease description of your target disease can be visualised with images and videos for any of your stakeholders.
Find out some examples of visualized images and videos here.

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