Acquired (Autoimmune) Hemolytic Anemia is an indication for drug development with over 90 pipeline drugs currently active. According to GlobalData, preregistered drugs for Acquired (Autoimmune) Hemolytic Anemia have a 90% 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 Acquired (Autoimmune) Hemolytic Anemia 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.
Acquired (Autoimmune) Hemolytic Anemia overview
Acquired autoimmune hemolytic anemia (AIHA) is a rare blood disorder characterized by the immune system mistakenly attacking and destroying red blood cells. Red blood cells carry oxygen throughout the body, and their destruction leads to anemia (low red blood cell count), causing fatigue, pale skin, and other symptoms. AIHA can be classified into “warm” and “cold” types, depending on the temperature at which the antibodies bind to red blood cells. Warm AIHA is more common and occurs at body temperature, while cold AIHA happens at lower temperatures. Treatment may involve corticosteroids, immunosuppressive drugs, blood transfusions, and, in severe cases, splenectomy. Management aims to control the immune response and alleviate anemia-related symptoms.
For a complete picture of PTSR and LoA scores for drugs in Acquired (Autoimmune) Hemolytic Anemia, 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.
