Givastomig is under clinical development by I-Mab and currently in Phase I for Solid Tumor. According to GlobalData, Phase I drugs for Solid Tumor have a 70% phase transition success rate (PTSR) indication benchmark for progressing into Phase II. GlobalData’s report assesses how Givastomig’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.
Givastomig overview
I-Mab overview
I-Mab is a biopharmaceutical company. It develops transformational medicines for therapeutic areas of immuno-oncology and autoimmune diseases. Its pipeline product portfolio comprises TJ202, a CD38 antibody for treating multiple myeloma; TJ101, a recombinant human growth hormone (rhGH) used in pediatric patients with growth hormone deficiency; TJ301, an IL-6 inhibitor for ulcerative colitis; enoblituzumab, a B7-H3 antibody against tumors; and TJ107, an oncology care agent to treat cancer treatment-related lymphopenia. I-Mab utilizes various molecular engineering platforms to develop drug molecules with defined biological properties. The company collaborates with biotechnology companies, CROs, and CMOs to advance the clinical development of its pipeline assets and out-licensing opportunities. It operates in China, Hong Kong and the US. I-Mab is headquartered in Shanghai, China.
For a complete picture of Givastomig’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.
