Dear all,
Currently working for a medical devices manufacturing company, I was wondering if Bayes success run Theorem is considered by FDA or other EU notified body as a valid statistical methods to determine the sample size during process qualification stage (i.e. OQ and PQ). The below screenshot details the formula used. In other words, no matter the lot sample size, if one wants to prove with a 95% confidence level that the process is for instance 90% reliable a minimum of 29 sample with no defective (i.e c=number of failure =0). From my standpoint the interesting part with this approach is that
- it is pretty straightforward
- it does not depend on the lot size
- it is based on a consumer (=RQL=LTPD approach) risk approach.
- as it is a c=0 sampling plan the sampling size is much smaller than AQL ISO2859-1 approach (which by the way is a producer risk approach)
Many thanks in advance for your comments,
Best Regards,
Florent
Currently working for a medical devices manufacturing company, I was wondering if Bayes success run Theorem is considered by FDA or other EU notified body as a valid statistical methods to determine the sample size during process qualification stage (i.e. OQ and PQ). The below screenshot details the formula used. In other words, no matter the lot sample size, if one wants to prove with a 95% confidence level that the process is for instance 90% reliable a minimum of 29 sample with no defective (i.e c=number of failure =0). From my standpoint the interesting part with this approach is that
- it is pretty straightforward
- it does not depend on the lot size
- it is based on a consumer (=RQL=LTPD approach) risk approach.
- as it is a c=0 sampling plan the sampling size is much smaller than AQL ISO2859-1 approach (which by the way is a producer risk approach)

Many thanks in advance for your comments,
Best Regards,
Florent