EMA qualifies first AI tool to diagnose liver disease in trials
The European Medicine Agency’s (EMA’s) human medicines committee (CHMP) has issued the first Qualification Opinion (QO) on a development methodology based on artificial intelligence (AI).
The tool, called AIM-NASH, helps pathologists analyse liver biopsy scans to identify the severity of MASH (metabolic dysfunction associated steatohepatitis; formerly known as non-alcoholic steatohepatitis NASH).
The AIM-NASH tool is expected to enhance the reliability and efficiency of clinical trials for new MASH treatments by reducing variability in measuring disease activity (inflammation and fibrosis).
Following a public consultation, CHMP issued an opinion to qualify this method, which means that the committee can accept evidence generated by the tool as scientifically valid in future applications.
CHMP agreed that the tool can increase reproducibility and repeatability in assessments for new MASH treatments. It can help researchers obtain clearer evidence on the benefits of new treatments in clinical trials that include fewer patients.
Testing new MASH treatments often relies on liver biopsies. However, high variability in MASH/NASH clinical trials is a challenge, as specialists who review biopsy samples may not always agree on the severity of inflammation or scarring.
The evidence submitted to CHMP shows that AIM-NASH biopsy readings, verified by one expert pathologist, can reliably determine MASH disease activity with less variability than the current standard used in clinical trials, which relies on a consensus by three independent pathologists.
AIM-NASH is an AI-based system that employs a machine learning model trained on more than 100,000 annotations from 59 pathologists who assessed over 5,000 liver biopsies across nine large clinical trials.
The qualified tool is ‘locked,’ which means the machine learning model cannot be modified or replaced. CHMP encourages the optimisation of the model, acknowledging that major changes may require re-qualification of the tool.
Diana Spencer, Senior Digital Content Editor, DDW