Moreover you can manipulate your results by disingenuous prior choices, and the smaller sample you have the stronger this effect is. I am not sold on the FDA's ability to objectively and carefully review Bayesian research designs, especially given the current administration's wanton disregard for the public good.

I would think there is less opportunity to manipulate your results with bayesian methods than with frequentist ones. Because the frequentist methods don't just require an alternate hypothesis, they depend on the exact set of outcomes possible given your experimental design. You can modify your experimental design afterwards and invisibly make your p-value be whatever you want