Selvigaltin is under clinical development by Galecto and currently in Phase II for Metastatic Melanoma. According to GlobalData, Phase II drugs for Metastatic Melanoma have a 36% phase transition success rate (PTSR) indication benchmark for progressing into Phase III. GlobalData’s report assesses how Selvigaltin’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.
Selvigaltin overview
Selvigaltin is under development for the treatment of liver cirrhosis, decompensated cirrhosis (Child-Pugh B), metastatic melanoma, head and neck squamous cell carcinoma, non-alcoholic steatohepatitis and non-small cell lung cancer. The drug candidate is formulated as hard capsules administered through oral route. It acts by targeting galectin 3.
Galecto overview
Galecto is a drug development company that includes the development of galectin modulators for the treatment of cancer, fibrosis and inflammation. The company develops activators and inhibitors of galectins. Its pipeline products include GB1211 – liver fibrosis, GB2064 – oncology and fabrosis, GB1211 – oncology: NSCLC, GB1211 – oncology: melanoma and HNSCC. The company partners with various biotechnology companies for its drug development activities. Galecto is headquartered in Copenhagen, Massachusetts, Denmark.
For a complete picture of Selvigaltin’s drug-specific PTSR and LoA scores, buy the report here.
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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.
