Resiquimod is under clinical development by SURGE Therapeutics and currently in Phase II for Non Muscle Invasive Bladder Cancer (NMIBC) (Superficial Bladder Cancer). According to GlobalData, Phase II drugs for Non Muscle Invasive Bladder Cancer (NMIBC) (Superficial Bladder Cancer) have a 72% phase transition success rate (PTSR) indication benchmark for progressing into Phase III. GlobalData’s report assesses how Resiquimod’s drug-specific PTSR and Likelihood of Approval (LoA) scores compare to the indication benchmarks. Buy the report here.

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.

Resiquimod overview

Resiquimod (STM-416) is under development for the prevention of recurrence and/or progression after transurethral resection of bladder tumor (TURBT) in non-muscle invasive bladder cancer (NMIBC). The drug candidate is an imidazoquinolinamine which acts by targeting toll like receptor 7 (TLR7) and toll like receptor 8 (TLR8). It is administered intraoperatively.

SURGE Therapeutics overview

SURGE Therapeutics (SURGE) is a provider of intraoperative immunotherapy services for cancer patients that offers an injectable biodegradable hydrogel and allows prolonged, localized free-up of most cancers immunotherapy. The company is headquartered in Cambridge, Massachusetts, the US.

For a complete picture of Resiquimod’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.