Bezuclastinib by Cogent Biosciences for Systemic Mastocytosis: 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.

Bezuclastinib overview

Bezuclastinib (CGT-9486) is under development for gastrointestinal stromal tumor, advanced systemic mastocytosis (ASM), indolent systemic mastocytosis (ISM) and mast cell leukemia. It is a small molecule administered through oral route in the form of the tablet. The drug candidate acts by targeting KIT activation loop mutation exon 17 D816V. It is developed based on the scaffold-based drug discovery platform.

It was under development for the treatment of solid tumors including gastrointestinal stromal tumor.

Cogent Biosciences overview

Cogent Biosciences formerly, Unum Therapeutics is a clinical-stage biopharmaceutical company that develops and commercializes precision therapies for genetically defined diseases. The company’s pipeline product portfolio includes CGT9486 which is a selective tyrosine kinase inhibitor designed to potently inhibit the KIT D816V mutation as well as other mutations in KIT exon 17. In the vast majority of cases, KIT D816V is responsible for driving Systemic Mastocytosis, a serious disease caused by the unchecked proliferation of mast cells. It carries out clinical trials such as Apex, Summit and Peak. Cogent Biosciences is headquartered in Cambridge, Massachusetts, the US.

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

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.