Cryopyrin-Associated Periodic Syndromes is an indication for drug development with over 10 pipeline drugs currently active. According to GlobalData, preregistered drugs for Cryopyrin-Associated Periodic Syndromes have a 100% 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 Cryopyrin-Associated Periodic Syndromes 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.
Cryopyrin-Associated Periodic Syndromes overview
cryopyrin-associated periodic syndromes are a group of autoimmune diseases caused by a defect in the cryopyrin protein. Genetic mutations on the NLRP3 gene result in overproduction of interleukin 1 beta due to excessive inflammasome activation. This is generally seen in children and is a rare form. It includes Neonatal Onset Multisystem Inflammatory Disease (NOMID), Muckle-Wells Syndrome (MWS) and Familial Cold Autoinflammatory Syndrome (FCAS). Symptoms are variable based on the individual conditions. Cold, fatigue, painful or burning rash, fever, joint pains, headache, and nausea are common symptoms. Diagnosis is difficult but based on physical examination and complete blood count to find out the levels of inflammatory mediators, skin biopsy and other lab examinations done. Anti inflammatory drugs to treat inflammation and supportive care are management steps.
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For a complete picture of PTSR and LoA scores for drugs in Cryopyrin-Associated Periodic Syndromes, 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.
