Exarafenib by Kinnate Biopharma for Non-Small Cell Lung Cancer: 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.

Exarafenib overview

Exarafenib is under development for the treatment of solid tumors, non-small cell lung cancer (NSCLC), colon cancer, rectal cancer, bile duct cancer (cholangiocarcinoma), thyroid cancer, spindle cell squamous cell carcinoma, breast cancer, gastrointestinal stromal tumor (GIST) and melanoma. It acts by targeting proto oncogene B Raf (BRAF). It is administered through oral route.

Kinnate Biopharma overview

Kinnate Biopharma is a biotechnology company that develops the small molecule kinase inhibitor candidates for difficult-to-treat, cancers associated with genetic alterations. It advancing the development of its lead-targeted therapy FGFR and RAF candidates. The company also provide BRAF protein and biomarker-driven approach to drive the preclinical and clinical development of its translational research programs. Kinnate Biopharma also carries out small molecule development programs, such as Cyclin-Dependent Kinase 12 (CDK12) inhibitor in KIN004 program for the treatment of ovarian carcinoma (OC), triple-negative breast cancer (TNBC) and metastatic castration-resistant prostate cancer (mCRPC). It has operations in San Francisco, the US. Kinnate Biopharma is headquartered in San Diego, California, the US.

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

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.