The tuning parameters are really important. @Funko_Unko found that the backwards tolerances are very important for performance. So lowering these did speed up things a lot for him. That can only be done “so much”, of course.
Also: The adjoint ODE method should work well when you have M >> N (so more parameters than states). At least this is my finding so far.