The only thing I can recommend at this point is to gather the data you have already, and organize it and run statistical analysis on it. If you don’t have a statistician in house, you might want to see about paying someone as a consultant to go through your data.
But you’ll absolutely have to give your statistician a list of potential critical parameters. These are called CPPs (critical process parameters in QbD talk). You will also have to give your statistician a list of critical quality attributes (CQAs).
Then the statistician will sift through the parameters to determine what affects your attributes. Basically it is figuring out what inputs affect your outputs. This might seem like a step backward, but it actually also helps ensure product quality, and it has the added benefit of potentially optimizing the process (so that it is faster, with less waste, and appropriate levels of control).
I think here, it would be nice to avoid redo-ing some studies, and hopefully you wont have to create more data.
Would it be possible to collect data during current manufacturing and then sorting it and sifting it statistically? That way you can continue with what you are doing, while performing ongoing “optimization studies”. The various agencies I’ve worked with (in audits) have been pleased when a company collects extra data to do further optimization, they call this process analytic or PAT, and continual improvement.
BUT, AND THIS IS CRITICAL… You cannot optimize a current process process using ongoing data analytics, if you process currently poses any kind of patient risk.
If your product is currently in control, but you’d like to improve it, work with a statistician, propose inputs/CPPs you would like to monitor, and outputs/CQAs which you would like to monitor. The statisticial will help you determine the relation between inputs and outputs.