XKH-002 is under clinical development by Suzhou xinkanghe Biomedical Technology and currently in Phase I for Solid Tumor. According to GlobalData, Phase I drugs for Solid Tumor have a 70% phase transition success rate (PTSR) indication benchmark for progressing into Phase II. GlobalData’s report assesses how XKH-002’s drug-specific PTSR and Likelihood of Approval (LoA) scores compare to the indication benchmarks. Buy the report here.

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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.

XKH-002 overview

XKH-002 is under development for the treatment of solid tumor. The drug candidate is a recombinant humanized immunoglobulin (IgG4) monoclonal antibody which acts by targeting V-set domain containing T cell activation inhibitor 1 (B7S1). It is administered through intravenous route.

Suzhou xinkanghe Biomedical Technology overview

Suzhou xinkanghe Biomedical Technology (Kanova Biopharma) is a biotechnology company that develops antibodies for the treatment of cancer and autoimmune diseases. Its areas include immuno-oncology, anti-cancer antibody drugs against tumors and autoimmune inflammatory indications. It focuses on the development of new antibody drugs for the treatment of tumors and autoimmune inflammatory diseases. The company utilizes its proprietary antibody research and technology platforms to develop its therapies. The company has operations across China. Kanova Biopharma is headquartered in Beijing, China.

For a complete picture of XKH-002’s drug-specific PTSR and LoA scores, buy the report here.

This content was updated on 10 June 2024

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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.