Nizubaglustat is under clinical development by Azafaros and currently in Phase I for Tay-Sachs Disease. According to GlobalData, Phase I drugs for Tay-Sachs Disease does not have sufficient historical data to build an indication benchmark PTSR for Phase I. GlobalData uses proprietary data and analytics to create drugs-specific PTSR and LoA in the Nizubaglustat LoA Report. Buy the report here.
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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.
Nizubaglustat overview
AZ-3102 (nizubaglustat) is under development for the treatment of GM1 and GM2 gangliosidosis (Sandhoff disease and Tay-Sachs) in adults and pediatrics, Niemann-Pick disease type C. The drug candidates are administered through oral route as capsule formulation. These acts by targeting GLCT1.
Azafaros overview
Azafaros is a clinical-stage company that focuses on the development of innovative therapies for the treatment of rare metabolic disorders. It aims to develop small molecule compounds for lysosomal storage disorders (LSDs) and related diseases using aza-sugar compounds. These diseases are inherited, severe and at times, life-threatening, with significant unmet medical needs. The aza-sugar compounds act by interfering with glycolipid metabolism in affected patients and are aimed at counteracting the pathological effects. The compounds are licensed exclusively to Azafaros. The company is a spin-off from Leiden University and Amsterdam UMC. It is funded by BioGeneration Ventures. Azafaros is headquartered in Leiden, Zuid-Holland, the Netherlands.
For a complete picture of Nizubaglustat’s drug-specific PTSR and LoA scores, buy the report here.
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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.
