Anti-Neutrophil Cytoplasmic Antibody-Associated Vasculitis (ANCA Vasculitis) is an indication for drug development with over 30 pipeline drugs currently active. According to GlobalData, preregistered drugs for Anti-Neutrophil Cytoplasmic Antibody-Associated Vasculitis (ANCA Vasculitis) have a 85.71% likelihood of approval (LoA) indication benchmark. GlobalData’s report assesses how phase transition success rate (PTSR) and likelihood of approval (LoA) scores for pipeline drugs in Anti-Neutrophil Cytoplasmic Antibody-Associated Vasculitis (ANCA Vasculitis) compared to historical 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.
Anti-Neutrophil Cytoplasmic Antibody-Associated Vasculitis (ANCA Vasculitis) overview
Anti-neutrophil cytoplasmic antibody-associated (ANCA) vasculitis is a group of autoimmune diseases that cause inflammation and damage to small blood vessels. It is triggered by autoantibodies called ANCAs that target and attack neutrophils, a type of white blood cell. ANCA vasculitis can affect different organs or parts of the body, such as the skin, kidney, or lung. The symptoms, diagnosis, and treatment of this condition depend on the type and severity of vasculitis, as well as the organs involved. Some common types of ANCA vasculitis are granulomatosis with polyangiitis, microscopic polyangiitis, and eosinophilic granulomatosis with polyangiitis.
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For a complete picture of PTSR and LoA scores for drugs in Anti-Neutrophil Cytoplasmic Antibody-Associated Vasculitis (ANCA Vasculitis), 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.
