STAR-0602 by Marengo Therapeutics for Oropharyngeal Cancer: Likelihood of Approval

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.

STAR-0602 overview

STAR-0602 is under development for the treatment of hematological malignancies, solid tumors, triple negative breast cancer, epithelial ovarian cancer, metastatic castration-resistance prostate cancer,  merkel cell carcinoma, cervical cancer, oropharyngeal cancer, anal cancer, penile cancer, vaginal cancer, vulvar cancer, metastatic colorectal cancer and non-small cell lung cancer. The drug candidate is developed based on universal targeted immunotherapy (UniTI) platform and STAR (Selective T Cell Activation Repertoire) platform. The drug candidate is administered through intravenous route.

Marengo Therapeutics overview

Marengo Therapeutics (Marengo) formerly, Elstar Therapeutics is developing first-in-class immuno-oncology therapeutics. The company utilizes its Universal Targeted Immunotherapy (UniTI) drug discovery platform to develop cancer immunotherapy pipeline programs. UniTI produces bi-, tri-, and tetra-functional antibody-based molecules which can employ dual-targeting of independent cell surface tumor antigens and engage multiple innate and adaptive immunological mechanisms to attack diseased cells. The company is funded by Apple Tree Partners. Marengo is headquartered in Cambridge, Massachusetts, the US.

For a complete picture of STAR-0602’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.