MT-302 is under clinical development by Myeloid Therapeutics and currently in Phase I for Gastric Cancer. According to GlobalData, Phase I drugs for Gastric Cancer have a 74% phase transition success rate (PTSR) indication benchmark for progressing into Phase II. GlobalData’s report assesses how MT-302’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.

MT-302 overview

MT-302 is under development for the treatment of metastatic colorectal cancer, non-small cell lung cancer, urothelial cancer, cervical cancer, epithelial ovarian cancer, HER2 negative breast cancer, pancreatic ductal adenocarcinoma, gastric adenocarcinoma, esophageal carcinoma, and triple negative breast cancer. The therapeutic candidate comprises mRNA delivered through lipid nanoparticles (LNPs), for modifying myeloid cells in vivo to express chimeric antigen receptors (CAR) targeting TROP2 expressing cancer cells. It is administered through intravenous route. It is being developed based on CRISPR-Enabled Autonomous Transposable Element (CREATE) platform.

Myeloid Therapeutics overview

Myeloid Therapeutics, Inc., a US based company harnessing and reprogramming myeloid cells to treat cancers.

For a complete picture of MT-302’s drug-specific PTSR and LoA scores, buy the report here.

This content was updated on 16 July 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.