CLL1-CD33 cCAR T Cells is under clinical development by ICell Gene Therapeutics and currently in Phase I for Chronic Myelocytic Leukemia (CML, Chronic Myeloid Leukemia). According to GlobalData, Phase I drugs for Chronic Myelocytic Leukemia (CML, Chronic Myeloid Leukemia) have a 69% phase transition success rate (PTSR) indication benchmark for progressing into Phase II. GlobalData’s report assesses how CLL1-CD33 cCAR T Cells’s drug-specific PTSR and Likelihood of Approval (LoA) scores compare to the indication benchmarks. Buy the report here.
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.
CLL1-CD33 cCAR T Cells overview
Gene therapy is under development for the treatment of relapsed/refractory, acute and chronic myeloid leukemia, myelodysplastic syndromes (MDS) and myeloproliferative neoplasms. The therapy comprises of T cells genetically modified by lentiviral transduction to express a chimeric antigen receptor (CAR) targeting the antigens CLL1 and CD33.
ICell Gene Therapeutics overview
iCell Gene Therapeutics is a clinical-stage biotechnology company that develop chimeric antigen receptor (CAR) immunotherapeutic for the treat treatment of cancer and autoimmune diseases. The company platforms include T-cell targeted CARs, compound CARs and universal CARs for the indication of T-cell malignancies, acute myeloid leukemia (AML), lupus (SLE) and multiple sclerosis and solid tumor. ICell Gene Therapeutics It includes anti-CLL1and anti-CD33 compound for treating acute myeloid leukemia. It has operations in the US and China. ICell Gene is headquartered in Brookhaven, New York, the US.
For a complete picture of CLL1-CD33 cCAR T Cells’s drug-specific PTSR and LoA scores, buy the report here.
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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.
