Vemurafenib is under clinical development by F. Hoffmann-La Roche and currently in Phase II for Lymphoma. According to GlobalData, Phase II drugs for Lymphoma have a 35% phase transition success rate (PTSR) indication benchmark for progressing into Phase III. GlobalData’s report assesses how Vemurafenib’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.
Vemurafenib overview
Vemurafenib (Zelboraf, RG7204, PLX4032, RO5185426) is a phenylpyridine derivative, acts as an antineoplastic agent. It is formulated as film-coated tablets for oral route of administration. Zelboraf tablets are indicated in monotherapy for the treatment of adult patients with BRAF V600 mutation-positive unresectable or metastatic melanoma.
It is under development for the treatment of solid tumor including craniopharyngioma, lung adenocarcinoma, pancreatic cancer, papillary thyroid cancer, non-small cell lung cancer, neuroblastoma, lymphomas, ovarian cancer, cholangiocarcinoma, prostate cancer, bladder cancer, sarcoma, stages I-III non-small cell lung cancer with ALK, ROS1, NTRK, or BRAF v600E molecular alterations, thyroid cancer, gastrointestinal stromal tumor (GIST) and chronic lymphocytic leukemia (CLL), refractory and relapsed multiple myeloma, refractory and relapsed hairy cell leukemia. It was also under development for metastatic melanoma, colorectal cancer and pediatric gliomas.
For a complete picture of Vemurafenib’s drug-specific PTSR and LoA scores, 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.
