A clinically validated breath database that serves as a reference for diagnosing and phenotyping new patients
Generally speaking, integrated databases contain information collected from more than one data source. Combining data from multiple sources yields increased statistical power to identify important relationships between data elements. Integrated databases are commonly being used by research institutes, pharmaceutical companies, and regulatory agencies. The digital transformation of healthcare institutions has also been enhanced by the increased integration of the Internet of Things (IoT). Integrated databases enable data sharing between different clinical and academic partners without requiring an extra layer of applications. Cloud technology, AI and increased connectivity altogether have created roadmaps to personalized data driven medicine.
It is increasingly recognized that diseases such as asthma, COPD, lung cancer and other respiratory diseases are highly complex and dynamic and that the underlying molecular networks are different for each patient. That is why popular single-marker hypothesis-driven approaches seem outdated. On the other hand, molecular pattern recognition appears to fit perfectly with the current needs of healthcare by improving diagnostic accuracy and increasing the therapeutic efficiency of individual patients. The pattern recognition approach delivers a ‘fingerprint’ of the patient’s individual biology, which can include entirely novel and unanticipated networks. The simplicity of our breath test and the integrated database allows for data-driven medicine. With the data instantly at their fingertips, doctors and GPs will have more information to provide on the spot care. The breath data of each participant in clinical research will be added to the expanding BreathBase Data to make subsequent classification more accurate.