AVA-6000 is under clinical development by Avacta Life Sciences and currently in Phase I for Pancreatic Ductal Adenocarcinoma. According to GlobalData, Phase I drugs for Pancreatic Ductal Adenocarcinoma does not have sufficient historical data to build an indication benchmark PTSR for Phase I. GlobalData uses proprietary data and analytics to create drugs-specific PTSR and LoA in the AVA-6000 LoA Report. 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.

AVA-6000 overview

AVA-6000 is under development for advanced or metastatic solid tumours which are known to be FAP positive including pancreatic, colorectal, breast, ovarian, bladder and non-small cell lung cancers, squamous cell carcinoma of the head and neck and soft-tissue sarcoma, salivary gland cancer, esophageal cancer, metastatic biliary tract cancer, undifferentiated pleomorphic sarcoma (UPS) and pancreatic ductal adenocarcinoma. The drug candidate is an affimer conjugated to pro-doxorubicin. It acts by targeting FAP. The drug candidate is developed based on the Tufts technology and pre|CISION technology . It is administered through intravenous route.

Avacta Life Sciences overview

Avacta Life Sciences operates within the pharmaceuticals and healthcare industry, specifically focusing on research and developing novel therapeutics and diagnostics for the treatment of cancer diseases. The company is headquartered in Wetherby, England, the UK.

For a complete picture of AVA-6000’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.