CS1 plus BCMA CAR-T is under clinical development by BioSeedin and currently in Phase I for Multiple Myeloma (Kahler Disease). According to GlobalData, Phase I drugs for Multiple Myeloma (Kahler Disease) have a 75% phase transition success rate (PTSR) indication benchmark for progressing into Phase II. GlobalData’s report assesses how CS1 plus BCMA CAR-T’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.

CS1 plus BCMA CAR-T overview

The therapeutic candidate is under development for the treatment of multiple myeloma (MM). It comprises of T cells genetically engineered to express chimeric antigen receptor (CAR) targeting cells expressing CD2 subset 1 (CS1) and B cell maturation antigen (BCMA). 

BioSeedin overview

BioSeedin, a subsidiary of Acrobiosystems Co., Ltd, is a financial advisory firm engaged in offering advisory, asset management and public relations services. The company is headquartered in Beijing City, Beijing, China.

For a complete picture of CS1 plus BCMA CAR-T’s drug-specific PTSR and LoA scores, buy the report here.

Data Insights


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.