Olaptesed pegol is under clinical development by TME Pharma and currently in Phase II for Glioblastoma Multiforme (GBM). According to GlobalData, Phase II drugs for Glioblastoma Multiforme (GBM) have a 23% phase transition success rate (PTSR) indication benchmark for progressing into Phase III. GlobalData’s report assesses how Olaptesed pegol’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.
Olaptesed pegol overview
Olaptesed pegol (NOX-A12) is under development for the treatment of metastatic pancreatic cancer, solid tumors including glioblastoma multiforme, glioma and unspecified indication. The drug candidate is administered parenterally and intravenous route and acts by targeting stromal cell-derived factor-1 (SDF-1). It is being developed based on Spiegelmers technology platform.
It was also under development for the treatment of hematopoietic stem cell transplantation, lupus nephritis, diabetic nephropathy, relapsed B-cell chronic lymphocytic leukemia (CLL) refractory/relapsed multiple myeloma, non-small cell lung cancer, metastatic colorectal cancer and pancreatic ductal adenocarcinoma.
TME Pharma overview
TME Pharma, a subsidiary of TME Pharma NV, is a clinical and anti-cancer drug development company. It is headquartered in Berlin, Germany.
For a complete picture of Olaptesed pegol’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.
