By: Sandra K. Rodriguez, Market Analyst
FDA “Encourages” Industry to Volunteer for e-Inspections Program
Based on Quality Metrics, FDA’s e-Inspections program is encouraging industry to implement state-of-the-art, innovative quality management systems for pharmaceutical manufacturing. In response to stakeholder feedback, the agency issued a revised draft guidance document in November 2016 titled “Submission of Quality Metrics Data[1].”
The draft guidance explains how the Center for Drug Evaluation and Research (CDER) and the Center for Biologics Evaluation and Research (CBER) intend to utilize submitted data and quality metrics to help ensure that their policies and practices continue to support continuous improvement and innovation in the pharmaceutical manufacturing industry. For more background on the evolution of this initiative see ISPE, FDA and the Metrics Future and FDA to Grade Industry on a Curve – Are You Ready?
Owners and operators of human drug establishments are encouraged to participate in the Quality Metrics Reporting Program in the voluntary reporting phase. By doing so, FDA will use information gathered from participating companies in its risk-based decision making as the quality metrics reporting program is further developed.
This is an opportunity for industry to begin improving on product quality, rather than focusing solely on compliance to regulatory requirements. As noted in the guidance document, “FDA does not intend to take enforcement action based on errors in a quality metrics data submission made to in this voluntary phase, provided the submission is made in good faith[2].”
FDA Intends to Calculate the Following Quality Metrics
Based on stakeholder input, FDA intends to calculate the set of quality metrics below based on industry reporting:
- Lot Acceptance Rate (LAR) as an indicator of manufacturing process performance. LAR = the number of accepted lots in a timeframe divided by the number of lots started by the same covered establishment in the current reporting timeframe.
- Product Quality Complaint Rate (PQCR) as an indicator of patient or customer feedback. PQCR = the number of product quality complaints received for the product divided by the total number of dosage units distributed in the current reporting timeframe.
- Invalidated Out-of-Specification (OOS) Rate (IOOSR) as an indicator of the operation of a laboratory. IOOSR = the number of OOS test results for lot release[3] and long-term stability testing invalidated by the covered establishment due to an aberration of the measurement process divided by the total number of lot release and long-term stability OOS test results in the current reporting timeframe[4],[5].
Reporting Quality Metrics for a Specific Product
When reporting data for a specific covered drug product, FDA would prefer that the product reporting establishment submit a single product report that includes data from all covered establishments. The compilation of these data into a single product report will facilitate data analysis and identification of product specific issues.
Furthermore, the Agency makes it clear that the Quality Control Unit (QCU) for a covered drug product, or API used in a covered drug product, would be best positioned to compile reports for submission to FDA. This is based on FDA’s assertion that the product reporting establishment has a responsibility for oversight and controls over the manufacture of drugs to ensure quality. As a result, the QCU at the product reporting establishment should already possess, or have access to, all of the quality metrics data needed to submit such reports.
Reporting establishments may submit quality metrics data reports on a quarterly basis throughout a single calendar year. FDA intends to open the electronic gateway in January 2018 to receive voluntary submissions of data generated in 2017. It expects to begin data analysis when the portal is closed and publish initial findings on its website. The results of the voluntary phase will be evaluated and FDA will then initiate a notice and comment rule making under its existing statutory authority to develop a mandatory quality metrics reporting program.
According to the revised Draft Guidance, Quality Metrics data will be used to:
- Establish a signal detection program as one factor in identifying establishments and products that may pose significant risk to consumers
- Identify situations in which there may be a risk for drug supply disruption
- Improve the effectiveness of establishment inspections
- Improve FDA’s evaluation of drug manufacturing and control operations
The guidance document specifically states FDA is continuing to encourage the adoption of emerging technology and will request comments on implementing new technology while maintaining a robust quality metrics program. A list of companies participating in the voluntary reporting phase will be published to show a demonstrated commitment to increasing transparency and improving quality monitory.
FDA’s e-Inspections program based on Quality Metrics is a key step in its objective to encourage industry to implement state-of-the-art, innovative quality management systems that drive industry to focus on improving in product quality, rather than simply ensuring compliance to regulatory requirements.
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For more articles on this topic, please see:
Intelligence Based E-Inspections
Can You Support Quality Metrics with Lobotomized Data?
FDA and Quality Metrics in Biopharma
ISPE, FDA and the Metrics Future
Is Compliance an Obstacle to Quality?
[1] http://www.fda.gov/downloads/drugs/guidancecomplianceregulatoryinformation/guidances/ucm455957.pdf [2] http://www.fda.gov/downloads/Drugs/DevelopmentApprovalProcess/SmallBusinessAssistance/UCM531066.pdf [3] This term does not refer to samples and protocols under 21 CFR 610.2. [4] 8 Reference this guidance’s Glossary for OOS result (e.g., lot release tests and long-term stability tests only). A single result (e.g., one value on a Certificate of Analysis) may result in only one OOS test result. [5] The metric measures invalidated lot release OOS results and long-term stability OOS results, separately