Does anyone know of a guideline or from experience how you would set the number of ‘rejects’ to be tested.
The problem is that in the qualification of the packing line protocol to show that the weight is correct, they are testing ten overweight and underweight items to show that they are rejected.
Is there a minimum number of ‘bad product’ that need to be included dependent on the batch size and
Should the ‘bad products’ (clearly labelled) also be included randomly with the good products in the test?
I found the following statements from FDA -OOS guidance. May be they are applicable to your case. Iam not 100% sure.But Iam only trying to relate your question with that guidance statements.
FDA inspections have revealed that some firms use a strategy of repeated testing until a passing result is obtained, then disregarding the OOS results without scientific justification. This practice of “testing into compliance” is unscientific and objectionable under CGMPs. The maximum number of retests to be performed on a sample should be specified in advance in a written standard operating procedure (SOP). The number may vary depending upon the variability of the particular test method employed, but should be based on scientifically sound principles. The number of retests should not be adjusted depending on the results obtained. The firm’s predetermined retesting procedures should contain a point at which the additional testing ends and the batch is evaluated. If the results are unsatisfactory at this point, the batch is suspect and must be rejected or held pending further investigation (§ 211.165(f)). Any deviation from this SOP should be rare and done in accordance with § 211.160(a), which states that any deviations from written specifications, sampling plans, test procedures, or other laboratory control mechanisms shall be recorded and justified. In such cases, before starting additional retesting, a protocol should be prepared (subject to approval by the QCU) that describes the additional testing to be performed and specifies the scientific and/or technical handling of the data.