Advancing The Use Of AI Tools In Hepatology Drug Development

Biotech companies developing hepatology therapies face a complex set of challenges — from identifying the most suitable trial sites and investigators to recruiting and retaining qualified patients, integrating data from multiple sources, and navigating intricate regulatory pathways.

A diverse panel of hepatology drug development experts remains optimistic that artificial intelligence (AI) can help overcome many of these barriers and significantly accelerate clinical progress. AI-powered tools can enhance site selection by analyzing performance and patient availability data, while improving patient matching through the precise application of inclusion and exclusion criteria. Generative AI can further boost patient engagement and retention by providing personalized, real-time responses to participant questions throughout the trial journey.

Looking ahead, AI’s potential extends to optimizing the use of real-world evidence, enabling more effective use of medical imaging, and potentially reducing the reliance on invasive tissue biopsies and animal testing. However, as the field embraces these innovations, it is essential to ensure that the underlying data is diverse, representative, and ethically sourced, while maintaining the highest standards of privacy, transparency, and regulatory compliance.