The technical reference document released Friday from the US Food and Drug Administration (FDA) provides recommendations to pharmaceutical companies on the submission of records and other information to support FDA’s calculation of quality metrics as part of the process validation lifecycle and pharmaceutical quality system (PQS) assessment.
The 10-page guide follows the creation of an Office of Pharmaceutical Quality, the release of draft guidance for industry, known as "Request for Quality Metrics" from July 2015, and is intended to ensure clear expectations for industry on the submission of quality metrics data as described in the draft guidance, for which FDA said it is still reviewing comments and may update.
“Our goal is to institute efficient regulatory review, compliance oversight, and inspection policies established on risk-based methods, including quality metric reporting,” the agency said. “Due to the inherent variability among reporting establishments’ implementation of the process validation lifecycle and PQS assessment, it is difficult to identify and compare quality issues between firms. As such, FDA recognizes the importance of industry input and agreement regarding standardized indicators of manufacturing and product quality.”
In addition to information on the drug’s name, monograph, application number and other specifics, the agency is also seeking information on:
- The sum of product quality complaints received for product distributed in the US
- The number of lots attempted that are released for distribution or for the next stage of manufacturing for the finished drug product or active pharmaceutical ingredient (API)
- Whether the Annual Product Review (APR)/Product Quality Review (PQR) was performed within 30 days of the annual due date
- The number of specification-related lots rejected for the drug referenced
- The number of lots attempted pending disposition for more than 30 days on the last day of the time period within which the data being reported was collected.
- The number of test results that fall outside the specifications or acceptance criteria for the drug
- The number of lot release and stability tests conducted for the drug
- The number of invalidated out of specification (OOS) results for finished drug product or API and stability tests due to laboratory error for the drug
In terms of data validation, FDA says, “Standardized data do not ensure quality data, but they do make it easier to assess some aspects of data quality by facilitating the automation of various data checks. Data validation relies on a set of validation rules that are used to verify that the data conform to a minimum set of quality standards. The data validation process can identify data issues early in the review that may adversely affect the use of the data.”
But as far as setting validation rules, FDA says it recognizes that it is “impossible or impractical to define a priori all the relevant” rules for any given submission and sometimes “serious issues in the submitted data are only evident through manual inspection of the data and may only become evident once the review is well under way. Often these issues are due to problems in data content (i.e., what was or was not submitted, or issues with the collection of original source data), and not necessarily how the data were standardized.”
And when the draft guidance on quality metrics is published in final, FDA says the validation rules will be posted to the external FDA website.
“Establishments should validate their metric data before submission using the posted validation rules and correct any validation errors,” FDA says, noting that Extensible Markup Language (XML) is the recommended format for drug quality metrics submissions.
Quality Metrics Technical Conformance Guide