Cellular Immunotherapy to Target NY-ESO-1 for Metastatic Melanoma is under clinical development by Avalia Immunotherapies and currently in Phase II for Metastatic Melanoma. According to GlobalData, Phase II drugs for Metastatic Melanoma have a 36% phase transition success rate (PTSR) indication benchmark for progressing into Phase III. GlobalData’s report assesses how Cellular Immunotherapy to Target NY-ESO-1 for Metastatic Melanoma’s drug-specific PTSR and Likelihood of Approval (LoA) scores compare to the indication benchmarks. Buy the report here.
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.
Cellular Immunotherapy to Target NY-ESO-1 for Metastatic Melanoma overview
Cellular immunotherapy is under development for the treatment of metastatic melanoma. It is administered by intravenous route. The therapeutic candidate constitutes autologous dendritic cells (DC) loaded with alpha-galactosylceramide and NY-ESO1 peptides.
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Avalia Immunotherapies overview
Avalia Immunotherapies develop immunotherapies designed to support cancer treatment. The company immunotherapies support the treatment of cancer, influenza, allergy, and other diseases and also offers therapeutic vaccines, enabling healthcare providers to activate immune cells in the patient body. It is headquartered in Lower Hutt, Porirua, New Zealand.
For a complete picture of Cellular Immunotherapy to Target NY-ESO-1 for Metastatic Melanoma’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.
