The FDA today released a technical reference document entitled, “Quality Metrics Technical Conformance Guide for the Implementation of the Draft FDA Guidance for Industry on Requests for Quality Metrics.”

This Guide supplements the above referenced draft Guidance and outlines how the FDA would like the information on quality metrics collected and reported.  Remember that, as stated in the new Conformance Guide, “FDA expects that quality metrics calculated from data that it collects will provide objective measures that, when used with additional internal data, will provide the Agency with indicators of the effectiveness of pharmaceutical manufacturing quality systems. The goal of these measures is to assure quality drug products are available to patients. The objectives of CDER’s quality metrics program can best be achieved through collaboration and a shared understanding of standards for metric indicators and data exchange/reporting.”

While not being a technical computer person myself, I find the guide useful as it provides a line-by-line concise description of what the FDA is looking for in each field and all of this on just a few pages!  For instance, while FDA talks about file transport and the need to use extensible mark-up language (XML), as well as maximum character length, what characters should or should not be used, etc., this Guide also provides brief and to-the-point examples of what reporting for each of the requested metrics should be.  A few illustrative examples are:

  • Description of the drug – whether Rx or OTC
  • Drug product type -The drug product type – Active Pharmaceutical Ingredient (API) or Finished Dosage Form (FDF). This field is restricted to two options; only one option can be selected.
  • Application type – The application type is New Drug Application (NDA), Abbreviated NDA (ANDA), Biologics License Application (BLA), Drug Master File (DMF), or Non-application product (NA).
  • Lots attempted – The number of lots attempted for the drug referenced above in 4.2.1 for each establishment. (see the Guide here for more detail and references)
  • Lots rejected – The number of specification-related lots rejected for the drug referenced above in 4.2.1 for each establishment.
  • Out-of-specification (OOS) results – The number of test results that fall outside the specifications or acceptance criteria for the drug referenced above in 4.2.1 for each establishment. (There is also another for OOS invalidated.)
  • Annual Product Reviews (APRs) and Product Quality Reviews (PQR) – Indication (yes/no) of whether the APR or PQR was performed within 30 days of the annual due date.

The above are just a few examples of what FDA is looking for to establish that a firm has a good quality program in place.  The results of collecting and analyzing this data will result in the FDA being able to establish both a baseline of quality performance for each firm; the Agency will then be able to use this data in determining potential inspectional frequency for a particular firm in a risk-based manner. FDA also hopes that this data collected will alert them, as well as the firms themselves, to potential deficiencies in their quality systems that may require corrective action.