Danburstotug is under clinical development by ImmuneOncia Therapeutics and currently in Phase I for Metastatic Melanoma. According to GlobalData, Phase I drugs for Metastatic Melanoma have an 81% phase transition success rate (PTSR) indication benchmark for progressing into Phase II. GlobalData’s report assesses how Danburstotug’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.
Danburstotug overview
STIA-1015 is under development for the treatment of solid tumors including colon cancer, gastric adenocarcinoma, esophageal squamous cell carcinoma, advanced urothelial carcinoma, in-transit metastatic melanoma, hepatocellular carcinoma and relapsed or refractory extranodal NK/T Cell Lymphoma. It is administered through intravenous and intralymphatic route. The drug candidate is a monoclonal antibody targeting PD-L1 (programmed cell death 1 ligand 1).
It was under development for solid tumor including periferal T cell lymphoma, anplastic large cell lymphoma, diffuse large b-cell lymphoma, bile duct cancer, transitional cell carcinoma.
ImmuneOncia Therapeutics overview
ImmuneOncia Therapeutics is an immuno-oncology-centric biopharmaceutical company that engaged in drug development and antibody engineering. It is headquartered in Seongnam, South Korea.
For a complete picture of Danburstotug’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.
