TAS-117 by Taiho Pharmaceutical for Chondrosarcoma: 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.

TAS-117 overview

TAS-117 is under development for the treatment of solid tumors including FGFR1 squamous cell lung cancer, ovarian clear cell carcinoma, endometrial cancer, breast cancer, colon cancer, ovarian cancer, cervical cancer, head and neck cancer, thyroid cancer, chondrosarcoma and g-PTEN aberrations cancer. It is a small molecule administered by orally. The drug candidate acts as selective non-ATP competitive inhibitor of AKT. It was under development for the treatment of gastric cancer and multiple myeloma.

Taiho Pharmaceutical overview

Taiho Pharmaceutical (Taiho), a subsidiary of Otsuka Group, develops and markets pharmaceutical products in the field of cancer, immunology, allergy and urology. Its product portfolio includes pharmaceutical products such as anti-allergic agents, anti-tumor agents, H2 receptor antagonists, antibiotics and medical devices; and consumer health products such as herbal digestive medicine, topical analgesics, antifungal cream and herbal medicine powder, among others. Taiho has production facilities in Tokushima, Saitama, Okayama, Kitajima and Inuyama. It operates through its subsidiaries situated worldwide including Japan, China, Canada, Singapore, the UK and the US. Taiho is headquartered in Tokyo, Japan.

For a complete picture of TAS-117’s drug-specific PTSR and LoA scores, buy the report here.

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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.