Lupus is a complex autoimmune disease that is difficult to detect and treat.
Patient-generated data, such as data from wearable devices, is being considered vital in chronic disease care as it facilitates continuous monitoring of relevant health signals in the clinic as well as outside of it.
A developer of diagnostic and digital technologies, Progentec noted that these signals rise in predictive value on integration with artificial intelligence (AI) algorithms and lupus-specific laboratory tests.
The latest research deal will support two studies in the US to assess the use of available new clinical tools, including proteomics and digital health, in offering a more practical approach to managing lupus.
The first study will assess the impact of aisle MGMT on the process of clinical decision-making.
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A lupus management platform developed by Progentec, aisle MGMT comprises the aisle DX Flare Risk Index test, the [AutoimmuneCorner] patient app, a smartwatch and access to health coaching specific to the disease.
The second study is based on the OASIS Study that commenced last year. Backed by Progentec’s LupusCorner Research platform, the OASIS Study is a completely decentralised clinical study.
It is evaluating how patient-reported outcomes and wearable device data could help in creating lupus-specific digital biomarkers and offer insight into variations in lupus disease activity.
Progentec chairman and CEO Mohan Purushothaman said: “For too long, precision medicine has been a buzzword when it comes to caring for lupus warriors.
“This research has the potential to show how both immunological data and patient-generated data can support clinicians as they identify the optimal treatment for each lupus patient.”
Both the studies are slated to commence this year, with the findings and results to be presented at scientific congresses and published in peer-reviewed journals.