QA QC & Quality Metrics

As Quality Maturity evolves based on the FDA’s metrics strategy, it was documented the agency wanted “a maximally efficient, agile, flexible, pharmaceutical manufacturing sector. The goal included high quality drug products, a culture of QA QC, and reduced regulatory oversight. Industry and regulatory agencies continue to make progress in establishing quality metrics for the pharmaceutical industry.

 

The FDA’s Janet Woodcock stated her agency wanted “a maximally efficient, agile, flexible, pharmaceutical manufacturing sector that reliably produces high quality drug products without extensive regulatory oversight”.

 

The groundwork to achieve this realization started with the adoption of Title VII, Sections 705 and 706 of the Food and Drug Administration Safety and Innovation Act (FDASIA). It has been over a decade since Dr. Woodcock revealed her vision to establish quality metrics used to determine a manufacturer’s ability to provide quality products to the patient.

 

QA Metrics

 

So how far have FDA and the industry come in establishing a set of quality metrics applicable to the pharmaceutical industry? The aforementioned sections of FDASIA gave FDA the ability to establish criteria to perform a risk-based FDA inspection of bio/pharmaceutical manufacturers. Further, a certified auditor request certain documents be provided in advance or, in some cases, in lieu of inspections.

 

Quality Control Metrics

 

The FDA next published a notice in the Federal Register asking for assistance from industry in developing a strategic plan and quality metrics to prevent drug shortages. FDA’s objective seems to be to reduce companies’ regulatory burden allowing for innovation while protecting the public health.

 

Quality Metrics in Manufacturing

 

In response to the Federal Register notice, several manufacturing organizations have made recommendations to the agency on what they perceived as quality metrics. Organizations that independently participated in the development of quality metrics include:

 

 

These organizations held conferences and wrote white papers to define what specific quality metrics would be appropriate. Representatives from the above organizations, covering all aspects of the pharmaceutical industry, met to try and come to a consensus. Additionally, how quality metrics are used as an indicator to provide high quality medicine to patients.

 

First Pass Quality

 

The outcome of the meeting resulted in acceptance rate, product complaint rate, confirmed out-of-specification rate, and recall rate. The proceedings from the meeting clarified that the “consensus set of metrics are somewhat rudimentary, and provide limited information about the culture of quality at a given organization”.

 

According to the published proceedings, “many [participants] remarked that a strong quality culture is a critical component in driving the system and processes that underpin the quality control and assurance infrastructure at an organization. However, quality culture is also difficult to capture through metrics.”

 

Supplier Quality Metrics

 

It was at this point where industry took off in different directions; PDA and ISPE have been the most engaged organizations in subsequent efforts. ISPE designed and asked members to participate in a pilot program for quality metrics, while PDA held a conference on quality metrics that focused on how to define a mature quality culture.

 

The metrics used in the ISPE Quality Metrics Pilot Program include the consensus metrics from the Brookings meetings as well as others. Some of the unique metrics used by ISPE in their pilot include timeliness of annual product quality reviews, recurring deviations rate, corrective action and preventive action (CAPA) effectiveness rate, process capability, and quality culture.

 

Quality Assurance Measurements

 

A PDA quality culture metrics conference that was held focused on metrics in assessing quality assurance. The hypothesis for the meeting was that mature quality attributes have a strong relationship to positive quality culture behaviors. The consensus from the meeting was that measuring a quality culture is subjected and defined by a set of behaviors, beliefs, values, attitudes, and governance and that quality assurance goes beyond traditional quality systems in creating a framework for a strong quality culture.

 

Training Metrics Scorecard

 

PDA divided quality systems into three types:

 

 

PDA defined traditional quality systems by traditional metrics including deviations, complaints, CAPA, etc. Enhanced quality systems were defined as those that had advanced programs such as risk management, knowledge management, quality by design, quality manual, etc. The other quality systems were much more evolved and have programs like shared quality goals, rewards and recognition programs, and cost of quality awareness programs, etc.

 

Types of Quality Metrics

 

Conference attendees defined the top five mature quality attributes as the following:

 

 

FDA Quality Metrics

 

Meanwhile, FDA presented the following metrics for measuring a quality system:

 

• Lot acceptance rate (the number of lots rejected by the establishment in a year divided by the number of lots attempted by the same establishment in the same year)
• Right-first-time rate (the number of lots with at least one deviation by the establishment in a year divided by the number of lots attempted by the same establishment in the same year)
• Product quality complaint rate (the number of complaints received by the manufacturer of the product concerning any actual or potential failure of a unit of drug product to meet any of its specifications, divided by the total number of lots released by the manufacturer of the product in the same year)
• Invalidated out-of-specification (OOS) rate (the number of OOS test results invalidated by the establishment, or contracted establishment in a year divided by the total number of tests performed by the establishment in the same year).

 

Future of Quality Metrics

 

So what is the future of quality metrics? The most important part of the puzzle is important to keep in mind that there are no perfect answers and collaboration is imperative. The concept of unintended consequences needs to be addressed so everyone is on a level playing field. Data trending can be more valuable in determining the robustness of a quality system than direct comparisons. Finally, an open and honest quality culture will drive the data integrity of quality metrics.

 

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