CUSP-06 is under clinical development by OnCusp Therapeutics 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 CUSP-06’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.

CUSP-06 overview

CUSP-06 (AMT-707) is under development for the treatment of solid tumors, kidney (renal), ovarian cancer and cholangiocarcinoma. It is administered by parenteral route.The drug candidate is a antibody drug conjugate composed of a proprietary antibody with high CDH6 binding affinity, a protease cleavable linker, and an exatecan payload (a potent and clinically validated topoisomerase-1 inhibitor) and is being developed based on MabArrayTM technology. It acts by targeting tumor cells expressing cadherin 6 (CDH6) and acts as topoisomerase-1 inhibitor.

OnCusp Therapeutics overview

OnCusp Therapeutics is a biopharmaceutical company developing oncology therapeutics for the treatment of cancer patients. The company is headquartered in New York City, New York, the US.

For a complete picture of CUSP-06’s drug-specific PTSR and LoA scores, buy the report here.

This content was updated on 18 April 2024

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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.