Real-world data specialist Medexprim partners with Openrad



Medexprim has announced its partnership with OpenRad, a remote radiology specialist, to promote the secondary use of high-quality Real-World imaging data.

As a Real-World data specialist based in France, Medexprim deploys its software suite and services in a growing network of leading European university hospitals.

In compliance with GDPR, Medexprim solutions extract, aggregate, curate, enrich and deidentify health data from multiple sources to deliver complex, regulatory-grade, multi-omics, and multicentric datasets to serve oncology, cardiology and neurology academic or industrial research projects.

Romain Cazavan, CEO of Medexprim, said:

“Imaging is an objective element of tumour/cancer evolution according to treatments, and in particular when the analysis is aimed at a longitudinal follow-up.

“As such, today, 40 per cent of clinical research questions require an analysis of the image produced during treatment administration.”

Located in London and Berlin, OpenRad delivers innovative radiology solutions for diagnostic imaging centres around the world.

The company aims to power better diagnostics by delivering an integrated, patient-first experience to healthcare professionals and the wider research community.

OpenRad can fully digitalise workflow processes within the radiological diagnostic sphere.

Its zero-footprint SaaS based solutions speed up implementation, increase centre utilisation, provide remote access, and reduce cost of ownership.

The preferred partnership promotes the optimised secondary use of imaging data by healthcare professionals, industrials, and clinical researchers for analysis, teaching and algorithm training.

Dominic Kirkman, Chief Revenue Officer of OpenRad, added:

“We are excited to have announced the partnership with Medexprim at our launch at RSNA.

“This collaboration enables our customers to collect, de-identify, and augment medical imaging data for secondary uses, such as clinical research, teaching, and AI algorithms training”.

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