https://www.statnews.com/2026/01/13/richard-pazdur-jpm-fda-c...
Recent comments during JPM don't have me hopeful for smooth sailing at the FDA any time soon.
> He said he was also deeply troubled by agency staff “being trampled on.” He referred to one individual who was “writing inflammatory emails using the F bomb,” telling center directors and deputy center directors that “they will go after them, that they were going to lose their jobs if they did not play ball.”
> He would also not name this person. STAT has reported that employees have been fearful under Vinay Prasad, director of the Center for Biologics Evaluation and Research.
> “It’s terrible to see 25 years of work dismantled,” said Pazdur, who founded the FDA’s oncology center. He later added, “I did not leave because I wanted to leave.”
> “I think I have been consistently critical of parts of the FDA regardless of administration, but what’s emerged over the past few months is just reflective of complete and total disarray and a complete lack of functional leadership,” said Brian Skorney, an analyst at the investment bank Baird.
That would be nice, but my experience is there can be quite significant variability between reviewers in different teams/groups, even on topics you'd think were well-established for many years, and for which there is existing FDA guidance.
Bayesian methods enable using prior information and fancy adaptive trial designs, which have the potential to make drug development much cheaper. It's also easier to factor in utility functions and look at cost:benefit. But things move slowly.
They are used in some trials, but not the norm, and require rowing against the stream. This is actually a great niche for a startup. Leveraging prior knowledge to make target discovery, pre-clinical, and clinical trials more adaptive and efficient.
Journals are also conservative. But Bayesian methods are not that niche anymore. Even mainstream journals such as Nature or Nature Genetics include Bayesian-specific items in their standard submission checklists [1]. For example, they require you to indicate prior choice and MCMC parameters.
[1] https://www.nature.com/documents/nr-reporting-summary-flat.p...
Biggest benefit I see from this guidance is support for rare disease trials, where patients are harder to find. Also regulatory bodies will be taking a closer look at stratification groups when it comes time for approval, so sponsors need to keep a super close eye on ensuring even enrollment and preventing misstrats.
Been used since the 90s.