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Feb 1, 2012

Median Provides Sanofi with Image Interpretation Software for Phase II Lung Cancer Study

  • Sanofi has contracted French firm Median Technologies to provide an end-to-end medical image interpretation and management solution for a Phase II study in small-cell lung cancer. Under terms of the deal Median will deploy its Median LMS (lesion management system) platform at all of the study’s 65 investigator and independent review sites.

    Median claims the deal represents the first time that image interpretation tools will be standardized across all sites involved in a study. The aim is to reduce variability in image interpretation, a factor that can ultimately result in hampering regulatory review.

    Installation of Median LMS at the Phase II trial sites will give investigators automated and semi-automated imaging processing capabilities through a standardized workflow. The firm says the sites will be able to carry out Recist 1.1 critera-based evaluations that comply with existing international recommendations, and transfer electronic imaging data from investigator sites to independent review sites in real time. End-to-end management will be carried out through Median CTIS (clinical trial imaging services). “Thanks to this first collaboration with Sanofi, we are now supporting four of the ten major pharmaceutical and biotech companies,” claims Jerome Windsor, vp business development and Median.

    Median’s web-based LMS solutions have been designed to detect, measure, evaluate, and follow up lesions identified using CT scans. The technology objectively measures and tracks cancerous or suspicious lesions, distributes a standardized oncologic report, and centralizes lesion information for multidisciplinary review. Three products are currently available. LMS-Lung and LMS-Lung/Track are clinical applications for the detection, evaluation, and follow-up of lesions identified in CT chest images. LMS-Liver is a clinical application for the initial evaluation and the follow-up of metastases and any other lesions identified in CT images of the liver. 


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