
News|Podcasts|April 7, 2026
ACT Brief: AI Leadership and Organizational Adoption, Bayesian Methods in Drug Development, and NIH Budget Reductions
Author(s)Andy Studna, Senior Editor
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In today's ACT Brief, we explore the leadership priorities that enable meaningful AI gains in clinical research, how Bayesian methodologies are reshaping trial design and innovation, and proposed federal budget cuts threatening NIH research funding.
This is the Applied Clinical Trials Brief—your fast track to the latest insights shaping clinical operations and drug development.
- In part two of his video
interview , Krishna Cheriath, vice president and head of clinical research digital data and AI at Thermo Fisher Scientific, outlined the leadership priorities, team structures, and boundary-spanning capabilities that separate organizations realizing meaningful AI gains from those stuck in pilot mode. Success depends on clear governance, cross-functional alignment, and sustained commitment beyond initial implementation. - In a new
Q&A from Pharmaceutical Executive, Dr. Stacy Lindborg, CEO of Imunon, discussed the FDA's January 2026 draft guidance on Bayesian methodologies and their potential to reduce development costs and timelines. Bayesian approaches enable adaptive trial designs, incorporation of prior data, and continuous learning as evidence accumulates, particularly valuable in oncology and rare diseases where patient populations are small and heterogeneous. - The White House
proposed a $5 billion NIH reduction for fiscal year 2027, bringing the agency to $41 billion and eliminating several institutes including the National Institute on Minority Health and Health Disparities and the Fogarty International Center. The cuts represent structural retrenchment beyond topline reductions, though Congress ultimately controls appropriations and has previously rejected similar proposals.
That's all for today's ACT Brief. Join us tomorrow for more updates shaping clinical operations and drug development. Thanks for listening.
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