SNB-101 is under clinical development by SN BioScience and currently in Phase I for Pancreatic Cancer. According to GlobalData, Phase I drugs for Pancreatic Cancer have a 74% phase transition success rate (PTSR) indication benchmark for progressing into Phase II. GlobalData’s report assesses how SNB-101’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.
SNB-101 overview
SNB-101 is under development for the treatment of pancreatic, ovarian, gastric, colorectal, breast, head and neck, rectal cancer, non-small cell lung cancer, biliary tract cancer and small cell lung cancer. The drug candidate is administered through intravenous and intratumor route. It comprises of SN-38 glucuronide as active ingredient. SN-38 glucuronide is a metabolite of irinotecan. It acts by targeting topoisomerase I. The drug candidate is developed based on Double Core-Shell Micelle and Micelle-Liposome Hybrid Cell technology.
It was also under development for the treatment of prostate cancer.
SN BioScience overview
SN BioScience is a research and development of drug delivery technology such as liposome, micelle and nanoparticle in the pharmaceutical sector and led the commercialize anticancer and metabolic disease drugs. The company is headquartered in Seongnam, South Korea.
For a complete picture of SNB-101’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.
