GUEST COLUMNISTS

• The FDA Plausible Mechanism Framework Just Changed Rare Disease Drug Development

  Discover how the new FDA Plausible Mechanism Framework changes the game for rare disease research by formalizing an approval pathway for individualized treatment of ultra-rare genetic diseases.

• Avoid Clinical Alignment Breakdowns With "Lateral Agility"

  Internal misalignment can stall the clinical timeline, erode the window of patent protection, and jeopardize funding. Learn why leadership can no longer be and instead must exhibit "lateral agility" across the enterprise.

• Outsourcing? When Both Sides Of The Table Are Investor-Backed, Everything Changes

  The outsourcing relationship is increasingly not sponsor versus provider. It is two investor-backed organizations navigating parallel pressures — with a shared program sitting in the middle.

• The Latest On RBM Uptake? Tufts Says Most, But Not All, Pharma On Board

  Tufts CSDD’s Beth Harper shares findings from the org's latest Impact Report and discusses how companies might better define risk, measure success, and understand central monitoring. 

• FDA's Draft Guidance On Bayesian Methods: Strategic Implications For Small Biotechs

  The FDA draft guidance on Bayesian methodology represents a major validation of statistical innovation in clinical development. Jessica Cordes summarizes the latest from the FDA and offers advice for small biotechs.

• Adapt Or Die: Best Practices In Designing An Adaptive, Open-Label RCT Phase 3 Oncology Trial

  Discover how adaptive trial design can deliver greater operational efficiency, improved efficacy outcomes, and enhanced sponsor affordability across the drug development life cycle.

• The Uncomfortable Conversation: AI And Data Use In Clinical Trials

  AI is quietly transforming clinical trials at the site level, boosting efficiency while creating hidden risks for patient data, protocols, and sponsor intellectual property.

• When A Clinical Trial Surfaces In An AI Chat, What Happens Next?

  AI is soon becoming the first interpreter of your clinical trial. Understand its implications for enrollment design, screening efficiency, and ultimately program predictability.