Gene Therapy to Target CD22 for Oncology is under clinical development by Kecellitics Biotech and currently in Phase II for Relapsed Chronic Lymphocytic Leukemia (CLL). According to GlobalData, Phase II drugs for Relapsed Chronic Lymphocytic Leukemia (CLL) have a 29% phase transition success rate (PTSR) indication benchmark for progressing into Phase III. GlobalData’s report assesses how Gene Therapy to Target CD22 for Oncology’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.
Gene Therapy to Target CD22 for Oncology overview
Gene therapy was under development for the treatment of relapsed and refractory B cell derived acute lymphoblastic leukemia (ALL), chronic lymphoblastic leukemia (CLL) and b-cell non-Hodgkin lymphoma. The therapeutic candidate comprises of autologous T cells genetically engineered to express chimeric antigen receptor that targets CD22. It is administered through parenteral route.
See Also:
For a complete picture of Gene Therapy to Target CD22 for Oncology’s drug-specific PTSR and LoA scores, buy the report here.
Premium Insights
From
The gold standard of business intelligence.
Blending expert knowledge with cutting-edge technology, GlobalData’s unrivalled proprietary data will enable you to decode what’s happening in your market. You can make better informed decisions and gain a future-proof advantage over your competitors.
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.
