IDE-161 is under clinical development by Ideaya Biosciences and currently in Phase II for Gastric Cancer. According to GlobalData, Phase II drugs for Gastric Cancer have a 28% phase transition success rate (PTSR) indication benchmark for progressing into Phase III. GlobalData’s report assesses how IDE-161’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.
IDE-161 overview
Ideaya Biosciences overview
Ideaya Biosciences (Ideaya) is a precision medicine company that develops oncology therapeutics. The company’s product pipeline includes darovasertib (IDE196), a protein kinase C (PKC) inhibitor that targets cancers with GNAQ and GNA11 mutations. It develops small molecule inhibitors based on synthetic lethality against known and novel targets. Ideaya also provides solutions for treating tumors with genetic mutations in homologous recombination deficiency(HRD) and high microsatellite instability (MSI). The company collaborates with Novartis Institute for Biomedical Research, Pfizer Inc, Boston Children’s Hospital, Cancer Research UK, and other academic and research institutes for cancer biology, immunology, and small molecule drug discovery. Ideaya is headquartered in South San Francisco, California, the US.
For a complete picture of IDE-161’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.
