Demonstrating Non-Inferiority Of BFPCs Vs. Traditional Air Monitoring

By BioPhorum

Demonstrating non-inferiority at local sites is essential for implementing bio-fluorescent particle counter (BFPC) technology. Non-inferiority testing is one of the key parameters that biomanufacturers should include in their user-specific validation when adopting the BFPC method.

We suggest that conducting equivalence testing in aseptic grade A environments is scientifically inappropriate due to the stochastic nature of particle detection and the statistical limitations of zero-dominated datasets, which prevent meaningful comparisons. Instead, we propose performing non-inferiority testing in lower-grade cleanroom environments (e.g., grade C/D), where controlled low-level contamination enables robust comparative analysis. This approach supports a scientifically rigorous validation strategy that is consistent with regulatory expectations and supports the broader adoption of BFPC technology.

This article shares industry-agreed best practices for demonstrating, through testing in lower-grade cleanroom environments, that BFPCs are non-inferior to traditional active air-sampling methods. It outlines key considerations for non-inferiority testing of BFPCs compared to active air samplers and is designed to support end users in meeting regulatory requirements for demonstrating non-inferiority as part of BFPC validation, including validation for use in grade A environments.

Location And Activities Considerations

Below are high-level principles for selecting rooms or areas suitable for non-inferiority testing of BFPCs compared to active air-monitoring methods.

• Recovery Rate And Colony Range

When determining the testing area, priority should be given to areas with a consistently high contamination recovery rate (CRR) to ensure sufficient data for comparison. We recommend that the CRR of the chosen location be close to 10%. The testing area should also be selected based on the expected range of colony-forming units (CFUs). Colony counts should be within the recommended range of 50–200 CFU per plate.

• Classified And Non-Classified Areas

Classified areas offer the advantage of consistent environmental controls, which is important for obtaining reliable and comparable data during testing. Grade D areas are recommended since they typically provide higher recovery rates than grade C or cleaner areas, which may not yield sufficient recoveries. If recovery rates in classified areas are too low, controlled non-classified spaces should be considered.

• Routine Activities And Operational Considerations

Routine activities within the selected area also play a critical role. Locations with frequent personnel movement and material handling are ideal because they provide a source of potential contamination. In-operations conditions are preferred for conducting the study, as they capture a realistic CRR and range of CFU counts.

Equipment Positioning

Since the two instruments will never collect the exact same air, and because identical set ups may not always be feasible, the goal is not identical sampling but rather reducing systematic bias introduced by the placement of the instruments and their possible interaction. The BFPC and traditional air sampler should be positioned close to each other while ensuring that the exhaust of one instrument does not affect the results of the other. To reduce systematic bias, the placement of BFPC and traditional air samplers can be alternated during the study.

Sampling Considerations

Below are high-level principles for collecting samples from BFPC and traditional air samplers to ensure a statistically meaningful comparison.

• Different Flow Rates

The difference in flow rates is an important factor that will influence how results are compared and affect the overall assessment of the data. Traditional active air-monitoring methods typically sample at higher flow rates than BFPCs. Users should operate their available traditional air sampler at the optimal flow rate recommended by the manufacturer.

• Preferred Sampling Approach

Perform parallel testing of BFPC and active air samplers using a time-based collection strategy. This means that sampling commences simultaneously for a predefined, identical time interval, ensuring both devices capture the same environmental activities and events.

• Sampling Duration

Sampling duration should be determined by the need to achieve statistically meaningful results. Factors such as the recommended range of 50–200 CFU per plate from a traditional air sampler, the flow-rate differences, and the ability to sustain activities during sampling should be considered when selecting the appropriate sampling duration. Sampling should be long enough to ensure robust comparison and statistical significance, while allowing organizations to adapt the duration to their procedures, equipment, and operational constraints.

• Sample Size

One sample refers to collecting data for x minutes, with x being the sampling duration chosen in the previous paragraph. Sample size (i.e., the number of samples) should be calculated using power analysis based on these key considerations:

• Variability of data
• Statistical power level
• Non-inferiority margin
• Distribution.

Analysis

Data Analysis Strategy

For the statistical analysis, one auto-fluorescent unit (AFU) detected by the BFPC and one CFU detected by the traditional active air-sampling method will be treated the same. We recognize that this simplification does not fully capture the biological differences in the detection and measurement principles.

AFU and CFU are fundamentally different units and not directly comparable, as AFU measures real-time fluorescent particles while CFU depends on microbial growth, which can vary by organism and media. We acknowledge that there is currently no established correlation between AFU and CFU. BFPC not only detects culturable organisms but also physically damaged or stressed cells, potential interferents, and “viable but non-cultivable” organisms, whose presence is variable and whose detection is unquantifiable.

We acknowledge a lack of scientific accuracy in treating a single AFU the same as a single CFU; however, it provides a pragmatic framework for statistical comparison in the context of instrument validation only.

Pattern Comparison

During analysis of the non-inferiority testing results, it is essential to incorporate pattern comparison to enable critical evaluation of the results before drawing conclusions. This means closely examining the trends and relationships between AFU counts obtained from the BFPC system and CFU counts from the traditional air sampler. Focusing on these comparative trends allows an effective assessment of AFU signal validity and supports robust conclusions rather than relying on the simplistic notion that “more AFU counts are better.”

Calculations And Results Comparison

For each device (BFPC and traditional air sampler), the average count of all samples collected should be calculated as follows:

• Flow rate factor calculation using the flow rate for each device to account for the differences in flow rates between the BFPC and the traditional sampler
• Adjustment of non-inferiority margin to account for the flow rate differences between devices
• Statistical analysis using a two-sided 90% confidence interval for the ratio of average counts.

Post‑Implementation Verification

After BFPC implementation and once new alert levels and action limits have been adjusted to the target environment, the decision equivalence principle can be applied to compare the number of events detected by the BFPC with those observed using the traditional method, demonstrating that both approaches support equivalent decision-making and control.

Conclusion

The non‑inferiority of BFPC compared to traditional air-monitoring methods can be robustly demonstrated when testing strategies are grounded in realistic environmental conditions, statistically meaningful sampling, and thoughtful interpretation of AFU–CFU relationships.

By applying this structured approach, biomanufacturers can gain confidence that BFPC technology supports reliable microbial air‑monitoring decisions and aligns with regulatory expectations for implementation. As BFPC adoption expands, continued cross‑industry collaboration and data sharing will help refine analytical approaches and further strengthen the scientific foundation for next‑generation monitoring strategies.

This article summarizes the main points from a recent BioPhorum paper on this topic. To learn more, check out the full paper, Demonstrating non-inferiority of BFPCs versus traditional air monitoring: Industry agreed considerations and best practices