The application of skip testing to drug substance manufacture

Posted: 29 February 2016 | | No comments yet

Skip testing is a process employed to reduce the analytical drugs testing burden and lends itself to processes with high frequency batch production. Rather than test all batches within a given interval, pre-selected batches are assessed and the other batches ‘skipped’. This reduction is justified as it is shown that there is a low risk of any batches failing specification. In this article, a process is described (supported by an example) that could be followed to justify the use of skip testing. The process involves identifying attributes that are candidates for skip testing, performing a statistical evaluation to confirm there is a low risk of batch failure if skip testing is instigated and making ongoing assessments to confirm the process remains highly capable and the attribute(s) is predicted to be well within specification.

The application of skip testing to drug substance manufacture

Introduction Skip (or periodic) testing is defined by The International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH)1,2 as conducting ‘‘specified tests at release on pre-selected batches and/or at predetermined intervals, rather than on a batch-to-batch basis, with the understanding that those batches not tested should still meet all the acceptance criteria established for that product’’. This represents a less than full schedule of testing and therefore for registered tests this must be justified, presented to, and approved by regulatory authorities before implementation. Following the inclusion of skip testing in ICH guidance1,2 there has been much discussion in the literature relating to its use3,4,5. Skip testing must only be implemented for low risk scenarios. This could be based upon a strong scientific rationale detailing why the skip-test is inherently unlikely to fail and/or using process capability data to show that the process is under control. Ongoing verification should also be applied to confirm the process is still capable of meeting specification. In addition, the following should be documented prior to implementation:

  • Alternative measures which are in place to control the quality attribute if it is no longer to be confirmed through testing every batch;
  • Scientific rationale which shows that the quality attribute has a low impact on safety and/or efficacy;
  • Scientific rationale (supported by risk assessment) which demonstrates that the attribute is not critical to quality (i.e., it is not a Critical Quality Attribute7);
  • Justification of skip testing intervals and batch selection (where selection should be made randomly within each interval);
  • Process to be followed if a batch selected for testing fails to meet specification.

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