Help to program bayesian adaptive design sample size - one group, multiple looks, binary endpoint

[msecic]

I'm trying to program sample size for a bayesian adaptive design, with a binary performance goal of say, AE rate less than 20%.  Data will be analyzed after X subjects, and if needed after each subsequent Y subjects.  There are three possible outcomes after each stage until success, futility or max sample size of N is reached.  So I need to program simulations and probability required for determining study success at each analysis stage.

Note that success decision can be something like: "Termination of enrollment for success if the posterior probability using observed data was sufficient to meet the performance goal (99% probability or greater for 50 and 75 subject interim checks, 97.5% thereafter)"

Continued accrual due to reasonable predictive probability (10% or greater) that performance goal can be met with more subjects.

Futility if predictive probability the performance goal could be met with enrollment of more subjects was less than 10%

Thank you for any insight....

[Reeza]

I've done this once...it's not easy or straightforward.

You basically have to determine the math and then program it, but no procs in SAS to accomplish it