Likelihood of Approval and Phase Transition Success Rate Model – Zilovertamab Vedotin in Solid Tumor
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This report provides you with the data that allows you to track and predict the specific likelihood of approval (LOA) and phase transition success rate (PTSR) of a drug using GlobalData’s proprietary machine learning algorithms developed using over 10 years of historical data.


Zilovertamab Vedotin in Solid Tumor Drug Details:
Zilovertamab vedotin is under development for the treatment of solid tumors, neuroblastoma, Ewing sarcoma, b-cell acute lymphoblastic leukemia, blood cancer including advanced or metastatic urothelial carcinoma of renal pelvis, ureter (upper urinary tract), bladder, or urethra, relapsed or refractory chronic lymphocytic leukemia/small lymphocytic lymphoma, mantle cell lymphoma, follicular lymphoma, marginal zone lymphoma, diffuse large B-cell lymphoma, or Richter transformation lymphoma, Burkitt lymphoma, lymphoplasmacytoid lymphoma, Waldenström macroglobulinemia, T-cell non-Hodgkin lymphoma, acute lymphoid leukemia, or acute myeloid leukemia. It is administered through intravenous route of administration. It acts by targeting ROR1 antigens expressing cells. The drug candidate is linked to UC-961-linker-monomethyl auristatin E (MMAE) ADC that preserves the high-affinity binding and specificity of UC-961 and allows for ROR1-targeted intracellular release of MMAE. The drug candidate was also under development for triple-negative breast cancer (TNBC), non-squamous non-small-cell lung cancer, metastatic breast cancer, estrogen receptor (ER)-positive, progesterone receptor (PR)-positive, or human epidermal growth factor receptor 2 negative breast cancer (HER2- breast cancer), ovarian cancer and pancreatic cancer.
Report Coverage
The data is segmented by drug name per indication and shows the current likelihood of approval for the drug compared to the indication benchmark and the industry benchmark.
The Likelihood of Approval data is updated regularly based on events that take place which impact the clinical development process and regulatory considerations. GlobalData’s proprietary machine learning models consider these events in real time, to produce quantitative changes to the LOA and PTSR along with qualitative reasoning why the likelihood of approval has changed.
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Reasons to Buy
- Precise Likelihood of Approval and Phase Transition Success Rates: Our machine learning and proprietary models provide accurate predictions, helping you gauge the potential success of a drug in the regulatory process.
- Competitive Strategy Planning: Access information on LOA and PTSR for competitors’ drugs, allowing you to plan your clinical development, commercialisation and marketing strategies
- Event-driven Updates: Track event-driven changes in LOA and PTSR benchmarked against indication LOA/PTSR. Get the latest insights to adapt your strategies promptly!
- Well-informed Investment Decisions: This data helps you navigate the dynamic landscape of drug development and regulatory considerations.
Scope
- Drug Details: Drug name, Drug type, Intervention type
- Administration Pathway
- Therapeutic Areas
- Key Manufacturers
- Drug Development Status
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