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S3-E4.3 – NASH-TAG 2022 Wrap-up: NITs from The FDA and Patients’ Perspectives

First-timers Amy Articolo (Novo Nordisk), Erin Quirk (Terns Pharmaceuticals) and Rachel Zayas (AGED Diagnostics) join the Surfers and guest KOL Ian Rowe to explore messages for patients and regulators from the firecis NASH-TAG 2022.

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) considers how two key stakeholders — FDA regulators and patients — might respond to changes in clinical trial protocols that remove or de-emphasize biopsy-generated data.

This conversation is a continuation of 4.2, which focused on the NASH-TAG “fireside chats.” This one starts with Erin Quirk’s observation that events of the past year (presumably COVID-19 approvals) demonstrate that FDA is not slow to act when presented with clear need and high-quality data. Erin goes on to confirm that the statements FDA made during the fireside chat demonstrated a “real openness” to dialogue, which is what agencies do to signal that they consider it important to improve processes and/or solutions. Next, she suggests that a patient representative should be on future years’ panels. FInally, she harkens back to Dr. Toerner’s referral to HIV as a model for relatively fast, data driven change. The conversation shifts to focus on competing views on how to act in the patient’s interest, with Erin, Ian and Amy all expressing points of view. Toward the end of the conversation, Roger shifts to discuss the practical implications of Stephen’s suggestion that studies should review 3 H & E slides per patient instead of the current number (one) and the two of them discuss practical implications on screen fail rates and its flipside, patient acceptance rates in terms of study cost, timeliness and ability to standardize and simplify placebo response analyses.

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