SGT-53 is under clinical development by SynerGene Therapeutics and currently in Phase II for Metastatic Adenocarcinoma of The Pancreas. According to GlobalData, Phase II drugs for Metastatic Adenocarcinoma of The Pancreas have a 42% phase transition success rate (PTSR) indication benchmark for progressing into Phase III. GlobalData’s report assesses how SGT-53’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.
SGT-53 overview
SGT-53 is under development for the treatment of metastatic pancreatic cancer (pancreatic adenocarcinoma), solid tumors and central nervous system (CNS) tumor. The drug candidate is administered through intravenous route. SGT-53 is a cationic liposomal, tumor-targeting p53 (TP53) gene delivery system. SGT-53 acts by targeting the transferrin receptor, by means of an anti-transferrin receptor single-chain antibody fragment (TfRscFv), attached to the outside of the liposome.
The drug candidate under development for the treatment of triple negative breast cancer, recurrent glioblastoma and gliosarcoma.
SynerGene Therapeutics overview
SynerGene Therapeutics (SynerGene) is a biopharmaceutical company. It is engaged in development of gene-based nanotech cancer therapeutics and diagnostics. It is headquartered in Potomac, Maryland, the US.
For a complete picture of SGT-53’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.
