Tindupepimut is under clinical development by Enterome Bioscience and currently in Phase II for Recurrent Glioblastoma Multiforme (GBM). According to GlobalData, Phase II drugs for Recurrent Glioblastoma Multiforme (GBM) have a 24% phase transition success rate (PTSR) indication benchmark for progressing into Phase III. GlobalData’s report assesses how Tindupepimut’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.

Tindupepimut overview

Tindupepimut (EO-2401) is under development for the treatment of recurrent glioblastoma multiforme, adrenocortical carcinoma, pheochromocytoma and paraganglioma. The drug candidate is next-generation microbiome-derived vaccines acts by targeting novel antigens (BIRC5, FOXM1, IL13Ra2) named onco-mimics. It is administered through subcutaneous route. It is developed based on quantitative metagenomics and functional metagenomics platform.

Enterome Bioscience overview

Enterome Bioscience (Enterome) is a clinical-stage biopharmaceutical company that develops immunomodulatory drugs for the treatment of cancer and immune diseases. The company’s pipeline products include memory T cell therapy and bioactives. Its pipeline candidates treat EO2401 +nivolumab, recurrent glioblastoma; EO2463, B-cell malignancies; EO2040, CRC ctDNA MRD; EO4010, CRC; EB1010, IBD and food allergy; EA300, food allergy. Its brands include OncoMimics, EndoMimics and AllerMimics. Enterome is headquartered in Paris, Ile-de-France, France.

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

This content was updated on 10 June 2024

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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.