Likelihood of Approval and Phase Transition Success Rate Model – Foscenvivint in Ovarian Cancer
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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.


Foscenvivint in Ovarian Cancer Drug Details:
Foscenvivint is under development for the treatment of HCV or HBV or NASH-induced decompensated cirrhosis, leukemia such as acute myeloid leukemia (AML), neuroendocrine tumors, chronic myeloid leukemia (CML), metastatic colorectal cancer, retinal fibrosis, adrenocortical carcinoma (ACC), gastrointestinal tumors such as small bowel carcinoma and gastrointestinal neuroendocrine tumors, desmoid tumors, anaplastic thyroid cancer (ATC), endometrial cancer, melanoma, myelodysplastic syndrome, colorectal cancer (CRC), hepatocellular carcinoma (HCC), pancreatic cancer, prostate cancer and ovarian cancer. The drug candidate is administered through intravenous and oral route. PRI-724 is a new chemical entity. It acts by targeting CBP/beta-catenin complex formation, and modulates the beta-catenin dependent pathway of Wnt signaling to provide a selective cell anti-proliferative effect. PRI-724 is generated by using the PRISM’s proprietary optimization technology. It was also under development for the treatment of primary biliary cholangitis, choroidal neovascularization, proliferative vitreoretinopathy (PVR), idiopathic pulmonary fibrosis, hematological cancer, colorectal cancer (third line therapy), advanced or metastatic pancreatic adenocarcinoma and metastatic colorectal cancer (first line therapy).
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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