QUALITY METRICS IN PHARMA
What are Quality Metrics?
Quality Metrics are the numbers or data that are used to measure the quality of product and quality system. It is used to monitor quality and to improve quality of manufacturing and processes.
According to FDA, Quality Metrics are defined as “Objective measures of the quality of a product or process”.
Earlier, quality was judged only by inspection. Now FDA wants to measure quality by data. Because quality cannot be improved if it cannot be measured.
Quality Metrics = A way to measure if your plant, your product and your system is under control or not, with numbers.
Why Quality Metrics? – FDA Quality Metrics Initiative
In 2015, US FDA started Quality Metrics Guidance for pharmaceutical companies. The reason was:
- Many drug shortages due to quality failures
- Recalls are increasing due to poor quality culture
- Inspection alone is not enough to know true quality of company
- FDA wants to predict if a company will fail in future, before inspection
So FDA asked companies to submit Quality Metrics data voluntarily. In future it may become mandatory.
Main objective of FDA Quality Metrics program:
- To ensure that products are of highest quality
- To reduce drug shortages
- To improve quality culture in industry
- To improve FDA inspection efficiency – Risk based inspections
Types of Quality Metrics – As per FDA Draft Guidance
FDA initially proposed 10 metrics, then revised to 4 main metrics + optional metrics.
A. FDA Proposed 4 Main Quality Metrics:
Formula = (Number of lots accepted / Total number of lots manufactured) x 100
It shows how many batches were rejected due to quality issues. If LAR is low, it means manufacturing is not under control.
Example: If 95 out of 100 lots accepted, LAR = 95%. Good LAR is close to 100%.
Formula = (Number of product quality complaints received / Total number of dosage units distributed) x 1 million
It shows how many complaints received from market per million units. High PQCR means poor product quality in market.
Complaints can be – broken tablet, leaking, no effect, packaging defect etc.
Formula = (Number of OOS results invalidated due to lab error / Total number of OOS results) x 100
This is very important. If many OOS are invalidated as lab error, it means company is hiding manufacturing failure as lab error. FDA watches this very closely.
If IOOSR is high (e.g. 80% OOS shown as lab error), FDA will suspect data integrity issue.
Formula = (Number of APQR completed on time / Total number of APQRs required) x 100
APQR must be completed within 30 days of due date. If company is not doing APQR on time, it shows poor quality system.
B. Other Important Quality Metrics Used in Industry:
| Quality Metric | What it measures |
|---|---|
| Batch Rejection Rate | Number of batches rejected / Total batches manufactured |
| Right First Time (RFT) | Percentage of batches manufactured without any deviation. Good companies have RFT > 90% |
| Deviation Rate | Number of deviations per batch or per month |
| CAPA Effectiveness Rate | How many CAPA actually worked and prevented recurrence |
| Change Control On Time Closure | Change controls closed within target time |
| Environmental Monitoring Excursion Rate | EM failures in clean room – Shows aseptic control |
| Customer Complaints Closure On Time | Complaints closed within 30 days |
| Recall Rate | Number of recalls per year – Critical metric for management |
Importance of Quality Metrics in Pharma
- For Companies: To know where is the problem, to improve processes, to reduce cost of poor quality, to improve quality culture.
- For FDA: To do risk-based inspections. If metrics are poor, FDA will inspect that site early. If metrics are good, inspection can be delayed.
- For Patients: To ensure continuous supply of good quality medicines and avoid drug shortages.
- For Business: Good quality metrics = Less recalls, Less warning letters, More business and trust from clients.
Quality Culture and Quality Metrics
FDA says Quality Metrics is not just numbers, it shows Quality Culture of company.
Quality Culture means:
- Everyone in company is responsible for quality, not only QA
- People report problems openly, not hide them
- Management gives importance to quality than production target
- Data integrity is followed – ALCOA+ principles
If IOOSR is high, if lot rejection is hidden, if complaints are not investigated properly – it shows poor quality culture.
So FDA now during inspection asks about quality culture, not only documents.
Collect Data (LAR, PQCR, IOOSR) -> Analyze Trend -> Find Root Cause -> CAPA -> Improve Quality Culture -> Better Product Quality
How to Implement Quality Metrics Program in Company
- Step 1 – Identify which metrics to track (Start with FDA 4 metrics + 4-5 internal metrics like RFT, Deviation Rate)
- Step 2 – Define formula and source of data (LIMS, QMS, ERP)
- Step 3 – Collect data monthly or quarterly
- Step 4 – Make trend charts – Is metric improving or worsening?
- Step 5 – Review in Quality Management Review (QMR) meeting with management
- Step 6 – Take CAPA if metric is not meeting target
- Step 7 – Set targets – e.g. LAR > 98%, PQCR < 100 per million, RFT > 90%
Challenges in Quality Metrics
- Different sites calculate metrics differently – need harmonization
- Manual data collection leads to errors – need automation
- Fear of sharing data with FDA – Companies think FDA will use data against them
- Focusing only on numbers and not on improvement
Conclusion: Quality Metrics is future of pharma quality. Inspection shows what happened in past 2-3 days of inspection. Quality Metrics shows trend of last 2-3 years. FDA wants to move from inspection-based quality to data-based quality. Companies with good metrics and good quality culture will have less regulatory risk and less shortages.
The information provided on this page is for educational and informational purposes only. It is not intended to provide regulatory, legal, or compliance advice.
Pharmaceutical regulations including FDA 21 CFR, EU GMP Annexes, ICH Guidelines, EDQM, WHO, and CDSCO requirements are subject to frequent updates and interpretation by regulatory authorities.
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About the Author
Mahummed Asif is a experienced pharmaceutical Quality Assurance professional and publisher of Pharmashare. He has worked with leading Pharmaceutical organizations and has developed extensive expertise in Quality Assurance, deviation management, investigations, CAPA, QMS, Product Life Cycle Management, change control, risk management, validation, product complaints, product recalls, and regulatory compliance. He is passionate about sharing practical pharmaceutical knowledge with professionals, students, and quality practitioners across the industry.