Vipoglanstat is under clinical development by Gesynta Pharma and currently in Phase II for Systemic Sclerosis (Scleroderma). According to GlobalData, Phase II drugs for Systemic Sclerosis (Scleroderma) have a 24% phase transition success rate (PTSR) indication benchmark for progressing into Phase III. GlobalData’s report assesses how Vipoglanstat’s drug-specific PTSR and Likelihood of Approval (LoA) scores compare to the indication benchmarks. Buy the report here.

GlobalData tracks drug-specific phase transition and likelihood of approval scores, in addition to indication benchmarks based off 18 years of historical drug development data. Attributes of the drug, company and its clinical trials play a fundamental role in drug-specific PTSR and likelihood of approval.

Vipoglanstat overview

Vipoglanstat (GS-248, OX-MPI) is under development for the treatment of Raynaud's disease (microvascular disease), systemic sclerosis and endometriosis. It is microsomal prostaglandin E synthase-1 (mPGES-1) inhibitor. It is administered through the oral route.

Gesynta Pharma overview

Gesynta Pharma is a clinical-stage pharmaceutical company. It develops therapies that target chronic inflammation in a wide range of diseases. Its product pipeline includes a vipoglanstat (formerly GS-248) drug program with the ability to inhibit the mPGES-1 enzyme as a non-hormonal treatment for endometriosis. Gesynta Pharma is also investigating GS-073, a part of next-generation mPEGS-1 inhibitors for an undisclosed disease. The company’s research originated from Karolinska Institute. It was funded by Hadean Ventures, Industrifonden, and Linc. Gesynta Pharma is headquartered in Stockholm, Sweden.

For a complete picture of Vipoglanstat’s drug-specific PTSR and LoA scores, buy the report here.

This content was updated on 20 February 2024

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GlobalData, the leading provider of industry intelligence, provided the underlying data, research, and analysis used to produce this article.

GlobalData’s Likelihood of Approval analytics tool dynamically assesses and predicts how likely a drug will move to the next stage in clinical development (PTSR), as well as how likely the drug will be approved (LoA). This is based on a combination of machine learning and a proprietary algorithm to process data points from various databases found on GlobalData’s Pharmaceutical Intelligence Center.