Recurrent Glioblastoma Multiforme (GBM) is an indication for drug development with over 160 pipeline drugs currently active. According to GlobalData, preregistered drugs for Recurrent Glioblastoma Multiforme (GBM) have a 80% likelihood of approval (LoA) indication benchmark. GlobalData’s report assesses how phase transition success rate (PTSR) and likelihood of approval (LoA) scores for pipeline drugs in Recurrent Glioblastoma Multiforme (GBM) compared to historical 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.

Recurrent Glioblastoma Multiforme (GBM) overview

Recurrent glioblastoma multiforme (GBM) refers to the return of aggressive brain tumors known as glioblastomas after initial treatment. GBM is the most malignant type of glioma, characterized by rapid growth and infiltrative behavior. Despite aggressive therapies like surgery, radiation, and chemotherapy, GBM often recurs due to its invasive nature and resistance to treatment. Management of recurrent GBM poses significant challenges. Treatment options may include additional surgery, re-irradiation, or alternative chemotherapy regimens. Clinical trials exploring novel therapies, immunotherapy, and targeted approaches aim to improve outcomes for patients facing recurrent GBM. However, the prognosis remains generally poor, emphasizing the critical need for ongoing research and innovative treatments in the field of neuro-oncology.

For a complete picture of PTSR and LoA scores for drugs in Recurrent Glioblastoma Multiforme (GBM), buy the report here.

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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.