A-005 is under clinical development by Alumis and currently in Phase I for Multiple Sclerosis. According to GlobalData, Phase I drugs for Multiple Sclerosis have a 73% phase transition success rate (PTSR) indication benchmark for progressing into Phase II. GlobalData’s report assesses how A-005’s drug-specific PTSR and Likelihood of Approval (LoA) scores compare to the indication benchmarks. 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.
A-005 overview
A-005 is under development for the treatment of multiple sclerosis, Parkinson’s disease, autoimmune encephalomyelitis (EAE) and neurodegenerative disorders. The drug candidate is administered through oral route. It acts by targeting tyrosine kinase 2 (TYK2).
Alumis overview
Alumis, formerly Esker Therapeutics, is a precision medicines company that focuses on discovery, development and treatment of autoimmune diseases. The company’s product pipeline includes ESK-001, a tyrosine kinase 2 (TYK2) inhibitor for the treatment of Plaque Psoriasis. It focuses to build a pipeline of therapeutics based on genetically approved targets for application in the treatment of inflammations and multiple autoimmune diseases. The company utilizes its proprietary analytics platform with curated genetic, clinical and health records data to develop its products. Alumis is headquartered in South San Francisco, California, the US.
For a complete picture of A-005’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.
