ALG-009 is under clinical development by Aligos Therapeutics and currently in Phase II for Liver Fibrosis. According to GlobalData, Phase II drugs for Liver Fibrosis does not have sufficient historical data to build an indication benchmark PTSR for Phase II. GlobalData uses proprietary data and analytics to create drugs-specific PTSR and LoA in the ALG-009 LoA Report. 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.

ALG-009 overview

ALG-055009 is under development for the treatment of non-alcoholic steatohepatitis (NASH) and liver fibrosis. The drug candidate act by targeting thyroid hormone receptor beta (THR-beta). It is administered orally.

Aligos Therapeutics overview

Aligos Therapeutics (Aligos) is a clinical-stage biopharmaceutical company developments therapeutics for liver and viral diseases. The company pipeline products include ALG-055009, a small molecule thyroid hormone receptor beta (THR-ß) agonist for metabolic dysfunction-associated steatohepatitis (MASH), and ALG-000184, a small molecule capsid assembly modulator for chronic hepatitis b (CHB). Aligo’s other pipeline products include ALG-097558 and ALG-125755. The company collaborates with various research institutes and biotech companies for drug development. It operates its offices in Belgium, the US and China. Aligos in headquartered in South San Francisco, California, the US.

For a complete picture of ALG-009’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.