Oberotatug ravtansine is under clinical development by Oxford BioTherapeutics and currently in Phase I for Ovarian Cancer. According to GlobalData, Phase I drugs for Ovarian Cancer have a 73% phase transition success rate (PTSR) indication benchmark for progressing into Phase II. GlobalData’s report assesses how Oberotatug ravtansine’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.
Oberotatug ravtansine overview
It was also pancreatic cancer, triple negative breast cancer and diffuse large B-cell lymphoma (DLBCL) and adenoid cystic carcinoma (ACC) of the head and neck.
Oxford BioTherapeutics overview
Oxford BioTherapeutics (OBT) is a clinical-stage oncology company that develops immuno-oncology (IO) and antibody-drug conjugate (ADC) drugs to treat cancers. The company’s pipeline product include OBT076, which treats solid tumors, including gastric, bladder, ovarian and lung cancer. Its products are designed to address unmet patient needs in cancer therapeutics, including bispecific, chimeric antigen receptor T Cell (CAR-T), antibody-drug conjugate (ADC) and antibody-dependent cell-mediated cytotoxicity (ADCC) therapeutics. Its OGAP discovery platform is a cancer membrane proteomic database and IO discovery platform that provides insights into the cancer-immune cell synapse. Oxford BioTherapeutics is headquartered in Abingdon, the UK.
For a complete picture of Oberotatug ravtansine’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.
