Partners to use AI on clinical trial data to help advance care, therapies

Collaborators hope to discover prognostic markers for IPF, other ILDs

Patricia Inácio, PhD avatar

by Patricia Inácio, PhD |

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patientMpower and Qureight have joined forces to accelerate the discovery of new prognostic markers for interstitial lung diseases (ILDs), a group of lung diseases characterized by scarring and inflammation that includes idiopathic pulmonary fibrosis (IPF).

The collaboration will harness Qureight’s artificial intelligence (AI) capability along with patientMpower’s patient database to shed light on the mechanisms underlying ILDs in an effort to advance the development of new therapies.

The first project is the analysis of clinical data from patients enrolled in a multiple-site clinical trial in the U.K. The collaboration is expected to extend to patient data gathered from future clinical trials across Europe and the U.S. Results from the analysis of the first trial are expected this year.

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Increasing ILD knowlege ‘key to improving treatment and patient care’

“There is so much we have yet to learn about ILD, and of course this limits our clinical management of the disease and the treatments available to patients. Increasing our understanding of ILD is key to improving treatment and patient care,” Mel Wickremasinghe, MD, a respiratory consultant specializing in ILD, at Imperial College NHS Trust, U.K., and the lead investigator of the first trial targeted by the partnership, said in a press release.

Spirometry, a type of pulmonary function or breathing test, is frequently conducted in hospitals every six to 12 months to monitor disease progression in ILD patients. patientMpower’s technology enables the collection of daily spirometry results remotely, allowing healthcare professionals to rapidly identify potential complications and make informed decisions on patient care, while freeing up hospital resources and reducing the need for out-patient clinics.

Qureight’s proprietary AI and digital infrastructure will be used to structure, curate, and analyze the large sets of spirometry data from the platform.

The results will help inform the design of new therapies and evaluate the efficacy of existing treatments.

“AI analysis of digital patient data has potential to revolutionise the way we define and manage health conditions,” Wickremasinghe said. “The two companies involved in this collaboration have a track record in ILD research, and the pooling of their complementary capabilities is an exciting step in the pathway to better understand ILD.”

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