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European Consortium for the Study of a Topical Treatment of iCRVO to prevent Neovascular Glaucoma (STRONG)
Start date: Oct 1, 2012, End date: Mar 31, 2018 PROJECT  FINISHED 

Neovascular glaucoma (NVG) is a very aggressive and rare type of glaucoma: yet, it contributes disproportionately to blindness from all eye diseases. NVG is also the second most common cause for the removal of the eye-ball across all eye diseases, usually because of intractable pain. The major cause of NVG is Ischaemic Central Retinal Vein Occlusion (CRVO) leading to neovascularisation, obstruction of aqueous humour outflow and increased intraocular pressure. Today’s therapeutic approaches are insufficient: they include destruction of the retina by coagulation, or off-label anti-VEGF injection into the eye. It is proposed to develop a better treatment by assessing the topical administration of Aganirsen: it is an antisense oligonucleotide able to interrupt the production of Vascular Endothelial Growth Factor, which plays a major role in the pathogenesis of NVG. Aganirsen is developed by GENE SIGNAL, a SME with expertise in topical ophthalmic treatments for orphan diseases, and manufactured by UNITHER. Under the coordination of the Mainz University Medical Center, a Phase II/III randomised, double-masked, 3-group, placebo-controlled trial (STRONG) is therefore presented to assess Aganirsen’s efficacy in reducing the rate of anterior and posterior segment neovascularisation and NVG development after CRVO. Involving 333 subjects within more than 35 clinical sites, the study is operationalized via a disease specific network (EVICR.net) and a contract research organization managed by GENE SIGNAL. The study aims at assessing a new therapeutic approach for iCRVO to prevent NVG for which conditional authorization will be sought at the end of the project. STRONG also delivers new insights into the natural course of the disease and its risk factors, analysing one of the largest patient cohorts ever. It also allows for a novel classification of NVG, yields novel image analysis tools, and proposes biomarkers able to differentiate between high- and low-risk patients and drug responders.
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