FRI Benefits

Currently, a lung disease is assessed by using pulmonary lung function tests, such as spirometry, which describe the lung as a whole, leaving a lot of information untouched. Data is viewed as numbers and graphs, and come with a high degree of variability.  FRI enables us to look inside the lung, by adding visualization and regional information to these measurements, therefore providing further insights in the regional functionality of the lung.

In the clinical practice, physicians have to deal with an unmet need for improvement of the current diagnostic tools. For personalized and precision treatment, an improved understanding of the disease pathophysiology and the complexity can be helpful for choosing the most suitable treatment approach. And especially in the difficult cases, it is essential to define the correct and most cost-effective treatment approach. Currently, this results in a high healthcare cost for chronically ill patients.
FRI gives sensitive patient-specific parameters that describe lung health at a regional level, enabling respiratory precision medicine.

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In clinical trials, it is very difficult to prove the efficacy of new drug compounds. This results in long and large clinical trials with a high development cost as a result.
FRI is a sensitive biomarker that can reduce the cost of clinical trials. The number of subjects required for a well-designed study can be reduced as the FRI parameters are much more sensitive. And as such, it can shorten these trials and facilitate the clinical development decisions.

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FRI decreases the number of patients in early clinical trials

Number of COPD patients tested in early clinical phase

(preserving statistical significance)

De Backer LA et al., 2012

Number of COPD patients tested in early clinical phase

(preserving statistical significance)

De Backer LA et al., 2012

Number of Asthma patients tested in early clinical phase

(preserving statistical significance)

Vos W et al., 2013

Number of Asthma patients tested in early clinical phase

(preserving statistical significance)

Vos W et al., 2013

FRI reduces clinical trial costs

At a cost of $1.6 billion per registered product, the development of respiratory drugs is significantly more expensive than for other drugs.  This is in part attributable to the lack of sensitive outcome parameters for the trials. The currently used parameters fail to clearly demonstrate the therapeutic benefits of newly developed therapies, thereby complicating the registration process. FRI reduces trial costs in due to its highly sensitive outcome parameters that make it possible to reduce the number of subjects and, using an approach that integrates both pre-clinical and clinical activities, it helps optimize the expensive translational process.