Last weekend’s NASH-TAG 2022 was the best-attended event in the conference’s six-year history, and probably the one that will have the greatest long-term impact on diagnosis, treatment, and monitoring of Fatty Liver patients. In this wrap-up conversation, our seven-person panel (including two Pharma execs and one diagnostics entrepreneur) discusses reactions to the closing conference session: two one-hour “fireside chats” exploring the potential to improve clinical endpoints for non-cirrhosis Advanced NASH and NASH cirrhosis clinical trials.
This conversation focuses on the two “fireside chats” that served both as climax and denouement to NASH-TAG 2022. The first fireside chat started with a presentation from Stephen Harrison titled, “Non-cirrhotic Trial Endpoints-Is It Time to Pivot?” and proceeded to discuss proper clinical endpoints for Advanced NASH trials. The second chat started with a presentation from Vlad Ratziu titled, “Cirrhotic Trial Endpoints-Are We Ready for NITs?” and focused on different strategies for endorsing clinical trial endpoints for cirrhosis trials. The first question to group members was about how optimistic they felt coming out of that session and why. The three commercial panelists all rated themselves “5” on a six-point scale, while Ian, the academic, rated himself “4” or perhaps even “3.” The commercial panelists focused on the value of having all key stakeholders, including FDA, in the same conversation and on the group’s practical problem-solving approach. Ian based his lower score on practical problems he anticipated in developing data that would move the field ahead quickly and confidently. Stephen noted that while we will need to rely on histopathology in the short run, FDA signaled clearly that they are open to data and suggestions on how to use these data more consistently and reliably in pursuit of drug analysis. He suggested first that researchers come forward with guidelines recommendations consistent with what FDA requested and also described the importance NAIL-NIT initiative in “breaking down the stovepipes” between companies to create a large, integrated data set for large, complex analyses.