Fb-PMT is under clinical development by NanoPharmaceuticals and currently in Phase I for Recurrent Glioblastoma Multiforme (GBM). According to GlobalData, Phase I drugs for Recurrent Glioblastoma Multiforme (GBM) have an 87% phase transition success rate (PTSR) indication benchmark for progressing into Phase II. GlobalData’s report assesses how Fb-PMT’s drug-specific PTSR and Likelihood of Approval (LoA) scores compare to the indication benchmarks. Buy the report here.

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.

Fb-PMT overview

The small molecule is under development for the treatment of glioblastoma multiforme, pancreatic cancer, recurrent glioblastoma and acute myelocytic leukemia (AML). It is a polyethylene glycol derivative. It is administered by subcutaneous route.

NanoPharmaceuticals overview

NanoPharmaceuticals discovers, develops and commercializes molecularly-targeted drugs to treat cancer, eye and skin diseases. The company is investigating fb-PMT program for glioblastoma, acute myeloid leukemia, and pancreatic cancer; and BG-P-TAT compound against neuroblastoma and other neuroendocrine cancers. It is also evaluating HP-TAT for the treatment of macular degeneration and diabetic retinopathy; and P-TET program targeting psoriasis and rosacea. NanoPharmaceuticals is headquartered in New York, the US.

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

This content was updated on 2 September 2023

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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.