NKX-101 by Nkarta for Relapsed Acute Myeloid Leukemia: Likelihood of Approval

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.

NKX-101 overview

NKX-101 is under development for the treatment of relapsed or refractory acute myeloid leukemia, hepatocellular carcinoma, myelodysplastic syndrome, metastatic colorectal cancer, intrahepatic cholangiocarcinoma, osteosarcoma and other solid tumors. The therapeutic candidate is administered through intravenous and intra-arterial route. It comprises of chimeric antigen receptor Natural Killer Cells (NK Cells) modified with NKG2D-CD3Zeta-DAP10 which acts by targeting cells expressing NKG2D.

Nkarta overview

Nkarta a biopharmaceutical company that discovers, develops and commercialization allogeneic, off-the-shelf engineered natural killer (NK), cell therapies to treat cancer. The company product pipeline includes NKX101, NKX019 (CD19), CD70 and NK+T. Nkarta lead products candidate NKX101 is designed to enhance the power of innate NK biology to detect and kill cancerous cells and NKX019 to treat a variety of B-cell malignancies by targeting the clinically and commercially validated CD19 antigen that is found in different B-cell malignancies. The company also carries out research and development and clinical trials. Nkarta is headquartered in South San Francisco, California, the US.

For a complete picture of NKX-101’s drug-specific PTSR and LoA scores, buy the report here.

This content was updated on 1 January 1970

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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.